Podcasts about influxdata

In this episode of the IoT For All Podcast, Evan Kaplan, CEO of InfluxData, joins Ryan Chacon to discuss time series data in IoT. The conversation covers the challenges of managing time series data, architecture and design considerations for handling time series data, optimizing data ingestion, organization, and querying, the integration of time series data with machine learning models, and the growing role of sensors and data in creating intelligent, autonomous systems. Evan Kaplan is a passionate entrepreneur and technology leader with nearly 25 years of experience in the CEO role. Evan's career spans from creating startups in his own garage to leading NASDAQ-listed companies generating nearly $200M in annual revenue. Prior to InfluxData, Evan served as Executive in Residence at Trinity Ventures, President and CEO at iPass Corporation (the leader in global Wi-Fi connectivity), and Founder, Chairman, and CEO at Aventail Corporation (the pioneer of SSLVPNs, now part of the Dell Corporation). InfluxData is the creator of InfluxDB, the leading time series platform used to collect, store, and analyze all time series data at any scale. Developers can query and analyze their time-stamped data in real-time to discover, interpret, and share new insights to gain a competitive edge. InfluxData is a remote-first company with a globally distributed workforce. Discover more about IoT at https://www.iotforall.com Find IoT solutions: https://marketplace.iotforall.com More about InfluxData: https://www.influxdata.com Connect with Evan: https://www.linkedin.com/in/kaplanevan/ (00:00) Intro (00:09) Evan Kaplan and InfluxData (00:47) What is time series data? (03:57) Managing time series data and challenges (09:15) What IoT applications use time series data? (12:04) Trends in data management (13:28) Future outlook on sensors and data (15:28) Learn more and follow up Subscribe to the Channel: https://bit.ly/2NlcEwm Join Our Newsletter: https://newsletter.iotforall.com Follow Us on Social: https://linktr.ee/iot4all

Esse é a tradução do programa sobre Times-Series database que gravamos, caso queira conferir a versão original você pode conferir no segundo link abaixo. Espero que gostem, o tema é bem interessante e aprendemos muito com o Ning Sun. Assuntos discutidos Introdução sobre Ning Sun  Introdução sobre Greptime  Introdução sobre bancos de dados temporiais  Quais as características dos bancos de dados temporiais? Quais são os bancos TSDB mais populares? Discussão sobre key features e benefícios de usar bancos de dados temporiais em aplicações modernas Monitoramento em Infraestrutura com IOT: aplicações, servidores observabilidade e métricas Exemplos específicos de como implementar TSDB em projetos e na industria Discussões sobre escalabilidade e desafios dos bancos temporiais Time-Series Database ferramentas: InfluxData, Prometheus and TimescaleDB Links https://hazelcast.com/glossary/time-series-database/ Introduction Time series database video  https://www.youtube.com/watch?v=4Dh6ytwB-no https://www.influxdata.com/ https://www.timescale.com/ https://tdengine.com/what-is-a-time-series-database/ https://www.youtube.com/watch?v=cgTZvJTQuuQ https://www.timescale.com/blog/time-series-analysis-what-is-it-how-to-use-it/ Soluções de hospedagem acesse https://king.host/ Participantes Jéssica Nathany (Software Developer  and  host) LinkedIn: https://www.linkedin.com/in/jessica-nathany-carvalho-freitas-38260868/Weslley Fratini (Software Engineer and co-host) LinkedIn: https://www.linkedin.com/in/weslley-fratini/ Ning Sun (Greptime Co-founder. Observability/Time-Series Database for Scalability)LinkedIn: https://www.linkedin.com/in/sunning87/Github: https://github.com/sunng87 Taymor Taymure (Enterprise Account Executive)LinkedIn: https://www.linkedin.com/in/taytaymuree/ Edited by: AGO Movies https://thiagocarvalhofotografia.wordpress.com/question, suggestions or advertising send to: debugcafe@gmail.comSee omnystudio.com/listener for privacy information.

In this episode we speak to Evan Kaplan, CEO of InfluxData, a pioneer and leader of time series data.Key talking points: Why specialized databases are needed for collecting time series dataThe challenges of storage and compressionIntegration of time series data with training AI

Allen Wyma talks with Andrew Lamb about InfluxDB's rewrite. InfluxDB is an open-source time series database. As a Staff Engineer at InfluxData, he works on InfluxDB 3.0, a new time series database written in Rust, focusing on query processing and the Apache Arrow DataFusion and Apache Arrow ecosystems. In that capacity, he is a member and past chair of the Apache Arrow PMC and actively contributes to Apache Arrow DataFusion and the Apache Rust implementation query engine. Andrew was a professional C/C++ programmer for 10 years before switching to Rust. His experience ranges from startups to large multinational corporations and distributed open source projects, and has paid leadership dues as an architect and manager/VP. He holds an SB and MEng from MIT in Electrical Engineering and Computer Science. Contributing to Rustacean Station Rustacean Station is a community project; get in touch with us if you'd like to suggest an idea for an episode or offer your services as a host or audio editor! Twitter: @rustaceanfm Discord: Rustacean Station Github: @rustacean-station Email: hello@rustacean-station.org Timestamps [@0:52] - Meet Andrew Lamb, Staff Engineer at InfluxData, working on InfluxDB IOx [@2:57] - Transitioning from C++ to Rust: Andrew's story [@11:24] - InfluxDB rewrite and its use cases [@22:13] - Compatibility of InfluxDB [@26:58] - Downsides of using Rust and other languages [@32:40] - Plans for the 3.0 alpha/beta release and different versions [@34:54] - Unique use of the async runtime Tokio [@55:28] - Rust as a tool for recruitment [@58:16] - Closing discussion Other links Andrew's X Account Using Rustlang's Async Tokio Runtime for CPU-Bound Tasks Using the FDAP Architecture to build InfluxDB 3.0 RustASIA Conf 2025 Credits Intro Theme: Aerocity Audio Editing: Plangora Hosting Infrastructure: Jon Gjengset Show Notes: Plangora Hosts: Allen Wyma

In this episode, Evan Kaplan, CEO of InfluxData, and Rick Bullotta, CTO and co-founder of ThingWorx, discuss the growing importance of time series data in the industrial sector with Contributing Lead Editor, Amy Bryson. They highlight the emerging trends and technologies enabling better data management and storage. They cover topics such as the role of time series data in AI and machine learning, the impact of edge data management and storage, recent technological advancements in IIoT analytics and operations, and the future outlook for time series data in the industrial sector.

In the push to integrate data into development, time series databases have gained significant importance. These databases capture time-stamped data from servers and sensors, enabling the collection and storage of valuable information. InfluxDB, a leading open-source time series database technology by InfluxData, has partnered with Amazon Web Services (AWS) to offer a managed open-source service for time series databases. Brad Bebee, General Manager of Amazon Neptune and Amazon Timestream highlighted the challenges faced by customers managing open-source Influx database instances, despite appreciating its API and performance. To address this, AWS initiated a private beta offering a managed service tailored to customer needs. Paul Dix, Co-founder and CTO of InfluxData joined Bebee, and highlighted Influx's prized utility in tracking measurements, metrics, and sensor data in real-time. AWS's Timestream complements this by providing managed time series database services, including TimesTen for Live Analytics and Timestream for Influx DB. Bebee emphasized the growing relevance of time series data and customers' preference for managed open-source databases, aligning with AWS's strategy of offering such services. This partnership aims to simplify database management and enhance performance for customers utilizing time series databases. Learn more from The New Stack about time series databases:What Are Time Series Databases, and Why Do You Need Them?Amazon Timestream: Managed InfluxDB for Time Series Data Install the InfluxDB Time-Series Database on Ubuntu Server 22.04Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

In this episode, Smart Manufacturing Contributing Lead Editor Amy Bryson speaks with Evan Kaplan, CEO of InfluxData, about how to turn time series data into actionable intelligence for swifter, better decision making in smart manufacturing environments. 

Highlights from this week's conversation include:The Evolution of Data Systems (0:47)The Role of Open Source Software (2:39)Challenges of Time Series Data (6:38)Architecting InfluxDB (9:34)High Cardinality Concepts (11:36)Trade-Offs in Time Series Databases (15:35)High Cardinality Data (18:24)Evolution to InfluxDB 3.0 (21:06)Modern Data Stack (23:04)Evolution of Database Systems (29:48)InfluxDB Re-Architecture (33:14)Building an Analytic System with Data Fusion (37:33)Challenges of Mapping Time Series Data into Relational Model (44:55)Adoption and Future of Data Fusion (46:51)Externalized Joins and Technical Challenges (51:11)Exciting Opportunities in Data Tooling (55:20)Emergence of New Architectures (56:35)Final thoughts and takeaways (57:47)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

rqlite is a lightweight, distributed relational database built on Raft and SQLite. Founder Philip O'Toole (@general_order24) decided to combine these technologies while working at a startup years ago. The startup no longer exists, but rqlite is going strong. Today, Philip is an engineering manager at Google, while he continues to be the driving force behind the open development of rqlite. Contributor is looking for a community manager! If you want to know more, shoot us an email at eric@scalevp.com. Subscribe to Contributor on Substack for email notifications! In this episode we discuss: The biggest misconceptions about how rqlite differs from SQLite Why writing databases is more interesting than new programmers might think The tradeoff between a large community versus smaller, more focused leadership Reasons why open-source development progresses in bursts of energy How to really pronounce “rqlite” Links: rqlite InfluxData dqlite Litestream libSQL Turso OpenTelemetry People: Ben Johnson (@benbjohnson) Other episodes: libSQL with Glauber Costa

For our very first episode, we welcome a special guest, Paul Dix, the CTO of InfluxData.He starts by giving us an overview of InfluxDB, an open source time series database used by developers to track server and application data. He takes us back to the early days of InfluxDB and explains how it came into existence, starting with the challenges they faced with their initial SaaS application and how they made the decision to repurpose their infrastructure and create this open source database. Paul also sheds light on the popularity of the programming language Go, which had a significant influence on their decision to use it for their project.He takes us through the journey of InfluxDB's development and the improvements that have been made over the years. He emphasizes the enhancements made in versions 0.11 and 1.0 to improve performance and query capabilities. Moreover, he shares their decision to explore using Rust for certain parts of the project and the positive impact it has had. Moving forward, the conversation delves into the challenges of managing high volumes of data in time series databases.Paul talks about the solutions they implemented, such as using BoltDB and developing the time-structured merge tree storage engine. We then dive into the decision to rewrite InfluxDB in Rust and the benefits it offers. He explains the improved performance, concurrency, and error handling that Rust brings to the table. Paul goes on to discuss the development process and how the engineering team has embraced Rust across their projects.As the conversation progresses, we touch on the performance improvements in InfluxDB 3 and the future plans for the database. Paul shares their vision of incorporating additional features and integrating with other tools and languages. He also mentions InfluxDB's involvement in open-source projects like Apache Aero Rust and Data Fusion, highlighting their ambition to extend beyond metric data. Paul concludes the conversation by discussing the standards and libraries in analytics, the role of Apache Iceberg, and the collaboration among data and analytics companies. He provides advice for getting started with Rust and InfluxDB, urging listeners to engage in hands-on projects and learn from books and online documentation.Thank you, Paul, for sharing your insights and expertise.

This is Rust in Production, a podcast about companies who use Rust to shape the future of infrastructure. We follow their journey in pursuit of more reliable and efficient software as they solve some of the most challenging technical problems in the world.I'm your host, Matthias Endler, and I'm a software engineer at corrode, a consultancy that helps companies make the most of Rust. I've been using Rust since 2015, have been a member of the Rust Cologne meetup since Rust 1.0 and ran a YouTube channel called "Hello Rust".There are plenty of great podcasts about Rust, but I felt that there was a missing piece. I wanted to hear more about how companies who use Rust in production. What are the challenges they face? How do they overcome them? What are the benefits of using Rust? How does the company find and hire Rust developers? And what advice would they give to other companies who want to use Rust.I sit down with decision-makers from companies that bet big on Rust and ask them in-depth questions about what they learned along the way. New episodes air every two weeks on Thursdays at 4pm UTC. If you don't want to miss out, please subscribe on Spotify, Apple Podcasts, or wherever you listen to podcasts. This helps other people find the show and supports our work.If you want to learn more about the show, please visit corrode.dev/podcast. Stay tuned for the first episode, where I talk to Paul Dix from InfluxData about how they use Rust in the latest version of InfluxDB.

Dan Nguyen is a Partner at Decibel where he focuses on helping founders build the next-generation of disruptive ML / AI, cloud infrastructure and cybersecurity companies. Prior to joining Decibel, he was a Vice President at Battery Ventures where he led investments in Databricks, SumoLogic, Expel, Contrast Security and InfluxData. Earlier in his career, Dan worked at VMware and spent time at UBS in the technology investment banking group. In this episode, we talk about: - Dan's story & how he started investing?- The origin story of Decibel and how they raised a $225 Million debut fund at the back of strong track record- How they pick companies to back?- Use of AI on both the good and bad side- How has Dan's investing approach evolved over the years?and much more.. Links: Decibel website - https://www.decibel.vc/ Follow Dan on X - https://twitter.com/dannguyenhuu Follow Dan on Linkedin - https://www.linkedin.com/in/dan-nguyen-huu-11502719/ Hosted by Prashant Choubey - https://www.linkedin.com/in/choubeysahab/ Subscribe to VC10X for more insightful episodes!

In this special episode of The SaaS SEO Show, we collected all the tidbits our guests shared about the future of SEO and the changes happening in the industry.************************Timestamps: (00:00) - Intro (01:35) - Brian Shumway, Director of SEO Product at Upwork. (03:50) - Neil Patel, Co-Founder at NP Digital. (05:04) - Jason Barnard, CEO and Founder at Kalicube. (07:30) - Josh Garofalo, SaaS Product Marketing Consultant & Copywriter at SwayCopy.com. (09:08) - Nigel Stevens, CEO and Growth Lead at Organic Growth Marketing. (13:09) - Jeremy Galante, SEO Lead at ClickUp. (15:44) - Eli Schwartz, Growth Advisor and SEO Strategic Consultant. (19:44) - Jitesh Patil, SEO & Content Specialist at Toggl. (22:09) - Bethany Fagan, Head of Content Marketing at PandaDoc (24:16) - Eric Hoover, Organic Search Director at Jellyfish. (25:16) - Caitlin Burns, Content and SEO Lead at Dovetail. (28:50) - Bernard Meyer, Sr. Director of Content & Creative at Omnisend. (32:48) - Lindsay Germain, Growth Product Manager at InfluxData. (37:29) - Outro ************************Stay Tuned:► Website: https://minuttia.com/► YouTube: https://bit.ly/2DHaJNr► LinkedIn: https://bit.ly/2BZJmhb************************Don't forget to leave us a five-star review and subscribe to our YouTube channel.This episode is brought to you by Minuttia.

In today's episode of Category Visionaries, we speak with Evan Kaplan, CEO of InfluxData, a time series data platform that's raised over $170 Million in funding. Topics Discussed: Evan's background and his unconventional path to CEO as someone with an environmental science degree The excitement and challenges of being a first-time CEO and the disappointment of a failed IPO due to a market crash The increasing demand for data and AI, and InfluxData's position as a market leader in the time series database space InfluxData's growth prospects and their rise as a market leader in the sector Overcoming challenges and seizing opportunities as the foundation for moving forward in business   Favorite book:  When Things Fall Apart: Heart Advice for Difficult Times

Paul Dix is Cofounder & CTO of open source time series data company InfluxData. The company's open source datastore, InfluxDB, has 26K stars on GitHub. InfluxData has raised over $200M from investors including Norwest, Battery, and Sapphire Ventures. In this episode, we dig into building the category of time series data, how an open source company's monetization plan should tie to fundraising, some of the hardest decisions the team had to make during InfluxData's journey so far & more!

In this episode, Lindsay Patton interviews Carolyn Moore, Chief People Officer at Influx Data, about her journey in HR and the importance of empathy in leadership. They discuss the negative impact of traditional performance management systems and the need to shift towards a feedback-driven approach with open communication and support. They also highlight the evolving nature of HR, with a focus on empathy, strategy, and data fluency. The episode explores how HR professionals are becoming more involved in understanding the business and driving strategic processes, envisioning the future of the HR landscape.Carolyn Moore is a seasoned HR executive and consultant with a passion for building strong leaders and nurturing winning cultures. With extensive experience in global communications and people leadership roles, including her current position as Chief Member at Chief and Chief People Officer at InfluxData, Carolyn brings expertise in driving organizational growth and creating positive workplace environments. She also owns CultureFluence Consulting, where she assists companies in transforming their workplaces through leadership development, culture alignment, and talent acquisition strategies. Here are a few of the topics we'll discuss on this episode of People Analytics: HR plays a vital role in shaping and preserving company culture. Traditional performance management models instill fear and hinder growth in the workplace. Emphasizing career discussions and supporting employees' long-term goals enhances loyalty. Understanding employees on a personal level promotes engagement and meaningful connections. Empathy is a running theme in HR, influencing how HR professionals are shaking things up and helping the field evolve. There will be a need for more oversight around innovation and creativity, especially regarding the balance between pushing boundaries and potentially putting employees at risk. HR professionals should prioritize building credibility and connections within the company to effectively push strategy and contribute to overall business success. Resources: Chief InfluxData StaffGeek  The Advantage Connecting with Carolyn Moore:LinkedInConnecting with Lindsay Patton: LinkedIn  Email Quotables: 07:01 - “I think the words are important, but the words have to be meaningful, and you have to be able to ensure that it's sort of ingrained in you as an employee as well as, you know, any of the executives across the company.” 10:30 - “And I've been really working very hard leadership development wise, particularly with, with, you know, first level and second level managers to make sure that they take that and kind of sweep that away and think more about being empathetic, understanding what the employee is bringing to the party, and helping them to figure out what to do. Not by telling, but by coaching, by asking good questions. And I think that that's a, you know, that's, that's a skill that needs to be developed, but what I find is once leaders have got the hang of it, if you will, it makes it so much easier on them, honestly.” 11:54 - “One boss told me you need to do whatever I say because I'm the owner of the company. Another one said, and that didn't really motivate me to want to do a good job at all.” 20:16 - “I think a habit in the workforce is loyalty and expecting that, and, you know, getting ego in when people do choose to leave and grow and, you know, you can't, you can't fault someone for wanting to do something for themselves.” 14:25 - Lindsay: “And it just made me realize how much fear there is in the workplace in general. So, yeah. Can we talk about that a little bit? Because it's something that I think is, you know, is too prevalent.”.. Carolyn: “I've been thinking a lot about that, about fear in the workplace. And I, I think that just the structure of the workplace has driven that we've as a society for a long time have driven a model in into the workplace that's very militaristic.”

Barbara Nelson, VP of Engineering @ InfluxData, joins us to share her eng leadership philosophies on career adaptation and helping teams adapt to meet both business needs & individual interests / strengths. We cover how her leadership journey has shaped her perspective on adapting to new career opportunities, implementing boundaries within eng teams to foster creativity, approaching problem sets with eng teams, and building a healthy relationship between product & eng orgs. Additionally, Barbara shares strategies for adapting a team based on personality dynamics, meeting developers where they are, and why she's built her career on building products with purpose.ABOUT BARBARA NELSONBarbara leads the engineering team at InfluxData. She has extensive experience leading globally distributed teams in designing, developing, deploying, and supporting products and services that are delivered on a cloud-based service platform and on a range of client platforms. Prior to InfluxData, Barbara had a variety of engineering and technical leadership roles, including VP of Engineering at iPass, CTO at Cirrent, and Principal Architect at eBay. Barbara has a Bachelor's degree in Computer Science from University College Dublin, Ireland."There was an assumption that we had more shared context than we really had. So the engineers kind of thought, 'Well, it'll be obvious to the operations folks that this thing is deployed correctly or incorrectly.' There was no reason for it to be obvious to the operation folks. What would've made it obvious to the operations folks?”- Barbara Nelson   Join us at ELC Annual 2023!ELC Annual is our flagship conference for engineering leaders. You'll learn from experts in engineering and leadership, gain mentorship and support from like-minded professionals, expand your perspectives, build relationships across the tech industry, and leave with practical prove strategies.Join us this August 30-31 at the Fort Mason Center in San FranciscoFor tickets, head to https://sfelc.com/annual2023SHOW NOTES:Barbara's favorite leadership dilemma – job efficiency vs. enjoyment (1:57)How Barbara has adapted to various roles throughout her leadership journey (3:42)Lessons learned from diving into the role of Interim VP of Operations (6:19)Formal & informal frameworks for making / communicating adjustments (9:03)Barbara's perspective on pursuing new opportunities & the “career ladder” (11:33)Advice for those who feel stuck on that ladder (13:25)How Barbara's experience at General Magic impacted her leadership philosophy (15:07)Why boundaries help foster creativity (17:30)Barbara's approach to introducing problem sets to eng teams (19:14)Strategies for aligning eng teams to reach an intended output (21:55)Driving a healthy relationship between product & eng teams (23:58)Recommendations for bridging the gap between product & engineering (26:02)Adapt a team based on personality dynamics & what gets them excited (28:49)The power of building a product with purpose (36:31)How AI trends will impact eng team adaptation & alignment (38:12)Rapid fire questions (39:45)LINKS AND RESOURCESBuild: An Unorthodox Guide to Making Things Worth Making - Written for anyone who wants to grow at work—from young grads navigating their first jobs to CEOs deciding whether to sell their company—Tony Fadell's Build is full of personal stories, practical advice, and fascinating insights into some of the most impactful products and people of the 20th century.This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

Watch on YouTube About the show Sponsored by InfluxDB from Influxdata. Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Ask me anything episode: Submit your question(s) for our upcoming AMA episode: form here. Thank you! Brian #1: PythonGUIS Martin Fitzpatrick A site with a collection of resources, guides, books, comparisons, etc, around GUIs in Python. Martin recommends starting with PyQT6 However, there are tutorials covering PyQT6 PySide6 PyQT5 TkInter PySide even Kivy Michael #2: JupyterLab 4.0 is Here The next major release of our full-featured development environment You can upgrade by running pip install --upgrade jupyterlab or conda install -c conda-forge jupyterlab. JupyterLab is now faster, thanks to improvements such as CSS rules optimization, CodeMirror 6, MathJax 3, and notebook windowing. JupyterLab 3 was when working with large notebooks. There are additional performance improvements available via opt-in settings: Faster tab-switching on Chromium browsers: “Settings” → “JupyterLab Shell” → switch “Hidden mode” to “contentVisibility” Better performance with long notebooks: “Settings” → “Notebook” → switch “Windowing mode” to “full” An upgraded text editor. Better real time collaboration. Bug fixes. More than 100 bugs have been addressed and resolved, enhancing JupyterLab's stability and performance. Brian #3: Proposing a struct syntax for Python Brett Cannon This would be a cool syntax for a data only type: struct Point(x: int, y: int) No positional only parameters No inheritance No methods Instances would be immutable, so p = Point(1, 2) would create an object that could be used as a key. A data only focused set of types. Michael #4: Python 3.13 Removes 20 Stdlib Modules via PyCoders From PEP 594 – Removing dead batteries from the standard library we're saying goodbye to aifc, audioop, cgi, cgitb, chunk, crypt, imghdr, mailcap, msilib, nis, nntplib, ossaudiodev, pipes, sndhdr, spwd, sunau, telnetlib, uu, xdrlib As well as the 2to3 program and lib2to3 module in Python. Python 3.12 final release is scheduled in 4 months (October 2023) and Python 3.13 final release is scheduled in 1 year and 4 months (October 2024). Extras Brian: Affirming your PSF Membership voting status You have until June 15 to affirm your voting rights in the upcoming Board Election, if you care about such things. Michael: 5 Career Tips for Budding Python Developers video PyCon US 2023 videos are up Python 3.11.4, 3.10.12, 3.9.17, 3.8.17, 3.7.17, and 3.12.0 beta 2 are now available Joke: Snorkel not included

Watch on YouTube About the show Sponsored by InfluxDB from Influxdata. Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Michael #1: pystack PyStack is a tool that uses forbidden magic to let you inspect the stack frames of a running Python process or a Python core dump, helping you quickly and easily learn what it's doing. PyStack has the following amazing features:

Watch on YouTube About the show Sponsored by InfluxDB from Influxdata. Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Brian #1: Python's Missing Batteries: Essential Libraries You're Missing Out On Martin Heinz Fun collection of a bunch of libraries you may not know about (or forgot about), with code examples. Utilities boltons : iterate through json and dates, quickly grab data out of nested structures, and convert nested data with jsonutils, timeutils, and iterutils sh : conveniently call shell funcitons Data Validation validators : validate email addresses, credit cars, IP addresses, and more. the fuzz : fuzzy string comparisons Debugging stackprinter : nice stack traces with exception messages higlighted Testing freezegun : stop time, change dates, … dirty_equals : comparing things that are kinda equal CLI tqdm : add a progress bar to command line apps Michael #2: awesome-polars A curated list of Polars talks, tools, examples & articles. Mostly articles and tutorials however. Brian #3: Running Headless Selenium in Python (2023) Siddiqi First off, if you are doing automated testing with Selenium, I hope you already know about headless. It's awesome and speeds up testing. Next, there's changes to how you code headless, as of Selenium 4.8.0 (Jan. 2023). Old: options.headless` `**=**` `True New: options.add_argument('--headless=new') for Chrome options.add_argument('--headless') for Firefox Reasons: Read Headless is Going Away! post on Selenium blog. Subtitle: “Now that we got your attention, headless is not actually going away, just the convenience method to set it in Selenium” Michael #4: Gracy Gracy helps you handle failures, logging, retries, throttling, and tracking for all your HTTP interactions. Has support for Parsing per status code Throttling Retries Custom validation Record/replay for testing A bit non-pythonic but perhaps inspriation for some out there Extras Michael: Mobile apps are finally out Take the git course for free for a limited time. Michael's blog post announcing the apps Joke: It's practice

Watch on YouTube About the show Sponsored by InfluxDB from Influxdata. Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Michael #1: Introducing 'Trusted Publishers' PyPI package maintainers can adopt a new, more secure publishing method that does not require long-lived passwords or API tokens to be shared with external systems. Our term for using the OpenID Connect (OIDC) standard to exchange short-lived identity tokens between a trusted third-party service and PyPI. Instead, PyPI maintainers can configure PyPI to trust an identity provided by a given OpenID Connect Identity Provider (IdP). These API tokens never need to be stored or shared rotate automatically by expiring quickly provide a verifiable link between a published package and its source Additional security hardening is available Brian #2: Mojo : a new programming language for all AI developers. Mojo may be the biggest programming language advance in decades - fast.ai blog Suggested by many listeners “Mojo combines the usability of Python with the performance of C, unlocking unparalleled programmability of AI hardware and extensibility of AI models.” A programming language compatible with Python, with performance similar to C++/Rust. “Mojo is designed to become a superset of Python over time by preserving Python's dynamic features while adding new primitives for systems programming.” - emphasis from Brian It's not there yet, but still super cool Built on a MLIR, not LLVM “How compatible is Mojo with Python really? Mojo already supports many core features of Python including async/await, error handling, variadics, etc, but… it is still very early and missing many features - so today it isn't very compatible. Mojo doesn't even support classes yet!” Michael #3: django-prose Wonderful rich-text editing for your Django project. Rendering rich-text in templates Small rich-text content (as model fields) Django Prose is using Bleach to only allow certain tags and attributes See the website for a screenshot of it in action Brian #4: pylyzer is a static code analyzer / language server for Python, written in Rust. Shunsuke Shibayama Suggested by Owen Features fast detailed analysis type checking plus things like out-of-bounds accesses to lists, and non-existent key references to dicts more readable reports and a VS Code extension pylyzer vs ruff “Ruff, like pylyzer, is a static code analysis tool for Python written in Rust, but Ruff is a linter and pylyzer is a type checker & language server. pylyzer does not perform linting, and Ruff does not perform type checking.” Some limitations and incomplete “todo list”. See README for more details. Joke: Escape Room

Watch on YouTube About the show Sponsored by InfluxDB from Influxdata. Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Brian #1: huak - A Python package manager written in Rust. Inspired by Cargo Suggested by Owen Tons of workflows activate - activate a virtual environment add add a dependency to a project pip install it into your virtual environment, and add it to the dependency list in pyproject.toml test - run pytest update update dependencies lint - run ruff, installing it first if necessary fix - autofix fixable lint conflicts build - build wheel in isolated virtual environment using hatchling Honestly I was considering building my own workflow tool, but this is darned close to what I want. Even though it's still “in an experimental state”. There are rough edges (ruff edges, get it), but still, way cool. I just don't know how to pronounce it. Is it like “walk”, or more like “whack”? Michael #2: PSF expresses concerns about a proposed EU law that may make it impossible to continue providing Python and PyPI to the European public After reviewing the proposed Cyber Resilience Act and Product Liability Act, the PSF has found issues that put the mission of our organization and the health of the open-source software community at risk. As currently written, the authors of open-source components might bear legal and financial responsibility for the way their components are applied in someone else's commercial product. The risk of huge potential costs would make it impossible in practice for us to continue to provide Python and PyPI to the European public. Brian #3: ChaosToolkit Suggested by the maintainer, Sylvain Hellegouarch Declare and store your Chaos Engineering experiments as JSON/YAML files so you can collaborate and orchestrate them as any other piece of code. Extensible through an Open API Can be automated in CI/CD pipeline Michael #4: PEP 711 – PyBI: a standard format for distributing Python Binaries “Like wheels, but instead of a pre-built python package, it's a pre-built python interpreter” Joke: It's the effort that counts

Watch on YouTube About the show Sponsored by InfluxDB from Influxdata. Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Michael #1: makeapp via Felix Ingram Simplifies Python application rollout and publishing. Link to its mention on Talk Python. Simplifies Python application rollout and publishing: Make a skeleton for your new application with one console command Automatically create a VCS repository for your application. Automatically check whether the chosen application name is not already in use. Customize new application layouts with skeleton templates. Put some skeleton default settings into a configuration file not to mess with command line switches anymore. Easily add entries to your changelog. Publish your application to remotes (VCS, PyPI) with single command. Brian #2: Looking forward to Python 3.12 We're on 3.12.0a7 now, the last alpha, final is scheduled for October schedule So far, in 3.12.0a7 What's new in Python 3.12 page has some examples of the Improved Error Messages Recent addition, PEP 684 - A Per-Interpreter GIL was approved recently “… sufficient isolation would facilitate true multi-core parallelism …” seems like a good thing. But also, “… this is an advanced feature meant for a narrow set of users of the C-API. “, so not really sure how this will affect us. Still, seems cool. Michael #3: Python 3.11.3 is out Fixes a HIGH level CVE in OpenSSL (so patch it) Lots of changes in Core and Builtins Brian #4: How to Make a Great Conference Talk Sebastian Witowski Lots of great advice for tech conf talks. Don't skip the last half of this, getting your talk accepted is really when the work starts. Good sections to make sure you don't miss Live demos “First of all - do you really need a demo? …” Rehearsing Don't skip this. Do this. A lot. Out loud. With a timer. While standing. Memorize the first few minutes, and the last few. Know how you're going to open and close. Night before get enough sleep Day of eat well. Don't drink too much liquids. Be comfortable. Sebastian was honest in saying this stuff works for him, but do what works for you. From Brian: I deviate from Sebastian in quite a few places, but still don't disagree with his advice. I can't give a talk without slides, as I use them for prompts to know what I'm talking about next. My talks usually have a lot of code snippets. Obviously, that would be difficult without slides. I write my talk and my slides in Markdown. Sebastian writes in something else, then builds slides as visual aids. That's cool. Do what works for you. Bonus tool from the article: demo-magic - If I'm ever tempted to live code again, I think I'll try this instead. Extras Michael: NOW the CDN course is out. Django 4.2 released. Joke: Using A.I. for Efficiency

Linda and Dave chat again with Jay Clifford, Developer Advocate at InfluxData. InfluxData are the makers of InfluxDB, a popular open-source platform for simplifying time series data management. Designed to handle high speed and high volume data ingest and real-time data analysis, InfluxDB's robust data collectors, common API across the entire platform, highly performant time series engine, and optimized storage lets you build once and deploy across multiple products and environments. In part two of this conversation, Jay gives us a pop quiz on time series data, offers best practices for developers on handling time series data, shares some real-world customer success stories, and covers handling visualization with time series data. If you missed part one, you can listen in with Episode 76. Follow Jay on LinkedIn: https://www.linkedin.com/in/jaymand13/ Jay on Git: https://github.com/Jayclifford345 Linda on Twitter: https://twitter.com/lindavivah Linda's Website: https://lindavivah.com/ Linda on TikTok: https://www.tiktok.com/@lindavivah Linda on Instagram: https://www.instagram.com/lindavivah/ Linda's Medium: https://medium.com/@LindaVivah [DOCS] InfluxDB Cloud Powered by IOX -https://docs.influxdata.com/influxdb/cloud-iox/get-started/ [GIT] InfluxData Telegraf Plugins & Integrations - https://github.com/influxdata/telegraf [GIT] InfluxDB OSS - https://github.com/influxdata/influxdb [PORTAL] InfluxData Website - https://www.influxdata.com [PORTAL] InfluxData Cloud Signup - https://cloud2.influxdata.com/signup [PORTAL] InfluxDB Use Cases - https://www.influxdata.com/customers/ [PORTAL] Pandas - https://pandas.pydata.org/ [SLACK] InfluxData Community Slack - https://www.influxdata.com/slack (connect with Jay @JayClifford) [TRAINING] InfluxDB University (Free InfluxDB Training) - https://university.influxdata.com Subscribe: Amazon Music: https://music.amazon.com/podcasts/f8bf7630-2521-4b40-be90-c46a9222c159/aws-developers-podcast Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-developers-podcast/id1574162669 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zb3VuZGNsb3VkLmNvbS91c2Vycy9zb3VuZGNsb3VkOnVzZXJzOjk5NDM2MzU0OS9zb3VuZHMucnNz Spotify: https://open.spotify.com/show/7rQjgnBvuyr18K03tnEHBI TuneIn: https://tunein.com/podcasts/Technology-Podcasts/AWS-Developers-Podcast-p1461814/ RSS Feed: https://feeds.soundcloud

In this episode, Linda and Dave chat with Jay Clifford, Developer Advocate at InfluxData. InfluxData are the makers of InfluxDB, a popular open-source platform for simplifying time series data management. Designed to handle high speed and high volume data ingest and real-time data analysis, InfluxDB's robust data collectors, common API across the entire platform, highly performant time series engine, and optimized storage lets you build once and deploy across multiple products and environments. Jay shares his journey to the cloud, gives us a developer introduction to time series data management, how to compare it to relational data and databases, how developers should think about this kind of data, and shares some real world customer success stories. Follow Jay on LinkedIn: https://www.linkedin.com/in/jaymand13/ Jay on Git: https://github.com/Jayclifford345 Linda on Twitter: https://twitter.com/lindavivah Linda's Website: https://lindavivah.com/ Linda on TikTok: https://www.tiktok.com/@lindavivah Linda on Instagram: https://www.instagram.com/lindavivah/ Linda's Medium: https://medium.com/@LindaVivah [DAVES COLLECTION] Rick and Morty - https://awsdeveloperspodcast.s3.amazonaws.com/RickMorty.PNG [DAVES COLLECTION] World of Warcraft Collectors Editions – https://awsdeveloperspodcast.s3.amazonaws.com/WoWCollectorsEditions.PNG [DOCS] InfluxDB Cloud Powered by IOX -https://docs.influxdata.com/influxdb/cloud-iox/get-started/ [GIT] InfluxData Telegraf Plugins & Integrations - https://github.com/influxdata/telegraf [GIT] InfluxDB OSS - https://github.com/influxdata/influxdb [PORTAL] InfluxData Website - https://www.influxdata.com [PORTAL] InfluxData Cloud Signup - https://cloud2.influxdata.com/signup [PORTAL] InfluxDB Use Cases - https://www.influxdata.com/customers/ [PORTAL] Pandas - https://pandas.pydata.org/ [SLACK] InfluxData Community Slack - https://www.influxdata.com/slack (connect with Jay @JayClifford) [TRAINING] InfluxDB University (Free InfluxDB Training) - https://university.influxdata.com Subscribe: Amazon Music: https://music.amazon.com/podcasts/f8bf7630-2521-4b40-be90-c46a9222c159/aws-developers-podcast Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-developers-podcast/id1574162669 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zb3VuZGNsb3VkLmNvbS91c2Vycy9zb3VuZGNsb3VkOnVzZXJzOjk5NDM2MzU0OS9zb3VuZHMucnNz Spotify: https://open.spotify.com/show/7rQjgnBvuyr18K03tnEHBI TuneIn: https://tunein.com/podcasts/Technology-Podcasts/AWS-Developers-Podcast-p1461814/ RSS Feed: https://feeds.soundcloud

Redis, best known as a data cache or real-time data platform, is evolving into much more, Tim Hall, chief of product at the company told The New Stack in a recent TNS Makers podcast. Redis is an in-memory database or memory-first database, which means the data lands there and people are using us for both caching and persistence. However, these days, the company has a number of flexible data models, but one of the brand promises of Redis is developers can store the data as they're working with it. So as opposed to a SQL database where you might have to turn your data structures into columns and tables, you can actually store the data structures that you're working with directly into Redis, Hall said.  Primary Database? “About 40% of our customers today are using us as a primary database technology,” he said. “That may surprise some people if you're sort of a classic Redis user and you knew us from in-memory caching, you probably didn't realize we added a variety of mechanisms for persistence over the years.” Meanwhile, to store the data, Redis does store it on disk, sort of behind the scenes while keeping a copy in memory. So if there's any sort of failure, Redis can recover the data off of disk and replay it into memory and get you back up and running. That's a mechanism that has been around about half a decade now. Yet, Redis is playing what Hall called the ‘long game', particularly in terms of continuing to reach out to developers and showing them what the latest capabilities are. “If you look at the top 10 databases on the planet, they've all moved into the multimodal category. And Redis is no different from that perspective” Hall said. “So if you look at Oracle it was traditionally a relational database, Mongo is traditionally JSON documents store only, and obviously Redis is a key-value store. We've all moved down the field now. Now, why would we do that? We're all looking to simplify the developer's world, right?” Yet, each vendor is really trying to leverage their core differentiation and expand out from there. And the good news for Redis is speed is its core differentiation. “Why would you want a slow data platform? You don't, Hall said. “So the more that we can offer those extended capabilities for working with things like JSON, or we just launched a data structure called t-digest, that people can use along and we've had support for Bloom filter, which is a probabilistic data structure like all of these things, we kind of expand our footprint, we're saying if you need speed, and reducing latency, and having high interactivity is your goal Redis should be your starting point. If you want some esoteric edge case functionality where you need to manipulate JSON in some very strange way, you probably should go with Mongo. I probably won't support that for a long time. But if you're just working with the basic data structures, you need to be able to query, you need to be able to update your JSON document. Those straightforward use cases we support very, very well, and we support them at speed and scale.” Customer View As a Redis customer, Alain Russell, CEO at Blackpepper, a digital e-commerce agency in Auckland, New Zealand, said his firm has undergone the same transition. “We started off as a Redis as a cache, that helped us speed up traditional data that was slower than we wanted it,” he said. “And then we went down a cloud path a couple of years ago. Part of that migration included us becoming, you know, what's deemed as ‘cloud native.' And we started using all of these different data stores and data structures and dealing with all of them is actually complicated. You know, and from a developer perspective, it can be a bit painful.” So, Blackpepper started looking for how to make things simpler, but also keep their platform very fast and they looked at the Redis Stack. “And honestly, it filled all of our needs in one platform. And we're kind of in this path at the moment, we were using the basics of it. And we're very early on in our journey, right? We're still learning how things work and how to use it properly. But we also have a big list of things that we're using other data stores for traditional data, and working out, okay, this will be something that we will migrate to, you know, because we use persistent heavily now, in Redis.” Twenty-year-old Blackpepper works with predominantly traditional retailers and helps them in their omni-channel journey. Commercial vs. Open Source Hall said there are three modes of access to the Redis technology: the Redis open source project, the Redis Stack – which the company recommends that developers start with today -- and then there's Redis Enterprise Edition, which is available as software or in the cloud. “It's the most popular NoSQL database on the planet six years running,” Hall said. “And people love it because of its simplicity.” Meanwhile, it takes effort to maintain both the commercial product and the open source effort. Allen, who has worked at Hortonworks, InfluxData, said “Not every open source company is the same in terms of how you make decisions about what lands in your commercial offering and what lands in open source and where the contributions come from and who's involved.” For instance, “if there was something that somebody wanted to contribute that was going to go against our commercial interest, we probably not would not merge that,” Hall said. Redis was run by project founder Salvatore Sanfilippo, for many, many years, and he was the sole arbiter of what landed and what did not land in Redis itself. Then, over the last couple of years, Redis created a core steering committee. It's made up of one individual from AWS, one individual from Alibaba, and three Redis employees who look after the contributions that are coming in from the Redis open source community members who want to contribute those things. “And then we reconcile what we want from a commercial interest perspective, either upstream, or things that, frankly, may have been commoditized and that we want to push downstream into the open source offering, Hall said. “And so the thing that you're asking about is sort of my core existential challenge all the time, that is figuring out where we're going from a commercial perspective. What do we want to land there first? And how can we create a conveyor belt of commercial opportunity that keeps us in business as a software company, creating differentiation against potential competitors show up? And then over time, making sure that those things that do become commoditized, or maybe are not as differentiating anymore, I want to release those to the open source community. But this upstream/downstream kind of challenge is something that we're constantly working through.” Blackpepper was an open source Redis user initially, but they started a journey where they used Memcached to speed up data. Then they migrated to Redis when they moved to the AWS cloud, Russell said. Listen to the Podcast The Redis TNS Makers podcast goes on to look at the use of AI/ML in the platform, the acquisition of RESP.app, the importance of JSON and RediSearch, and where Redis is headed in the future.

About BrianBrian is an accomplished dealmaker with experience ranging from developer platforms to mobile services. Before InfluxData, Brian led business development at Twilio. Joining at just thirty-five employees, he built over 150 partnerships globally from the company's infancy through its IPO in 2016. He led the company's international expansion, hiring its first teams in Europe, Asia, and Latin America. Prior to Twilio Brian was VP of Business Development at Clearwire and held management roles at Amp'd Mobile, Kivera, and PlaceWare.Links Referenced:InfluxData: https://www.influxdata.com/ TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is bought to you in part by our friends at Veeam. Do you care about backups? Of course you don't. Nobody cares about backups. Stop lying to yourselves! You care about restores, usually right after you didn't care enough about backups.  If you're tired of the vulnerabilities, costs and slow recoveries when using snapshots to restore your data, assuming you even have them at all living in AWS-land, there is an alternative for you. Check out Veeam, thats V-E-E-A-M for secure, zero-fuss AWS backup that won't leave you high and dry when it's time to restore. Stop taking chances with your data. Talk to Veeam. My thanks to them for sponsoring this ridiculous podcast.Corey: This episode is brought to us by our friends at Pinecone. They believe that all anyone really wants is to be understood, and that includes your users. AI models combined with the Pinecone vector database let your applications understand and act on what your users want… without making them spell it out.Make your search application find results by meaning instead of just keywords, your personalization system make picks based on relevance instead of just tags, and your security applications match threats by resemblance instead of just regular expressions. Pinecone provides the cloud infrastructure that makes this easy, fast, and scalable. Thanks to my friends at Pinecone for sponsoring this episode. Visit Pinecone.io to understand more.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. It's been a year, which means it's once again time to have a promoted guest episode brought to us by our friends at InfluxData. Joining me for a second time is Brian Mullen, CMO over at InfluxData. Brian, thank you for agreeing to do this a second time. You're braver than most.Brian: Thanks, Corey. I'm happy to be here. Second time is the charm.Corey: So, it's been an interesting year to put it mildly and I tend to have the attention span of a goldfish of most days, so for those who are similarly flighty, let's start at the very top. What is an InfluxDB slash InfluxData slash Influx—when you're not sure which one to use, just shorten it and call it good—and why might someone need it?Brian: Sure. So, InfluxDB is what most people understand our product as, a pretty popular open-source product, been out for quite a while. And then our company, InfluxData is the company behind InfluxDB. And InfluxDB is where developers build IoT real-time analytics and cloud applications, typically all based on time series. It's a time-series data platform specifically built to handle time-series data, which we think about is any type of data that is stamped in time in some way.It could be metrics, like, taken every one second, every two seconds, every three seconds, or some kind of event that occurs and is stamped in time in some way. So, our product and platform is really specialized to handle that technical problem.Corey: When last we spoke, I contextualized that in the realm of an IoT sensor that winds up reporting its device ID and its temperature at a given timestamp. That is sort of baseline stuff that I think aligns with what we're talking about. But over the past year, I started to see it in a bit of a different light, specifically viewing logs as time-series data, which hadn't occurred to me until relatively recently. And it makes perfect sense, on some level. It's weird to contextualize what Influx does as being a logging database, but there's absolutely no reason it couldn't be.Brian: Yeah, it certainly could. So typically, we see the world of time-series data in kind of two big realms. One is, as you mentioned the, you know, think of it as the hardware or, you know, physical realm: devices and sensors, these are things that are going to show up in a connected car, in a factory deployment, in renewable energy, you know, wind farm. And those are real devices and pieces of hardware that are out in the physical world, collecting data and emitting, you know, time-series every one second, or five seconds, or ten minutes, or whatever it might be.But it also, as you mentioned, applies to, call it the virtual world, which is really all of the software and infrastructure that is being stood up to run applications and services. And so, in that world, it could be the same—it's just a different type of source, but is really kind of the same technical problem. It's still time-series data being stamped, you know, data being stamped every, you know, one second, every five seconds, in some cases, every millisecond, but it is coming from a source that is actually in the infrastructure. Could be, you know, virtual machines, it could be containers, it could be microservices running within those containers. And so, all of those things together, both in the physical world and this infrastructure world are all emitting time-series data.Corey: When you take a look at the broader ecosystem, what is it that you see that has been the most misunderstood about time-series data as a whole? For example, when I saw AWS talking about a lot of things that they did in the realm of for your data lake, I talked to clients of mine about this and their response is, “Well, that'd be great genius, if we had a data lake.” It's, “What do you think those petabytes of nonsense in S3 are?” “Oh, those are the logs and the assets and a bunch of other nonsense.” “Yeah, that's what other people are calling a data lake.” “Oh.” Do you see similar lights-go-on moment when you talk to clients and prospective clients about what it is that they're doing that they just hadn't considered to be time-series data previously?Brian: Yeah. In fact, that's exactly what we see with many of our customers is they didn't realize that all of a sudden, they are now handling a pretty sizable time-series workload. And if you kind of take a step back and look at a couple of pretty obvious but sometimes unrecognized trends in technology, the first is cloud applications in general are expanding, they're both—horizontally and vertically. So, that means, like, the workloads that are being run in the Netflix's of the world, or all the different infrastructure that's being spun up in the cloud to run these various, you know, applications and services, those workloads are getting bigger and bigger, those companies and their subscriber bases, and the amount of data they're generating is getting bigger and bigger. They're also expanding horizontally by region and geography.So Netflix, for example, running not just in the US, but in every continent and probably every cloud region around the world. So, that's happening in the cloud world, and then also, in the IoT world, there's this massive growth of connected devices, both net-new devices that are being developed kind of, you know, the next Peloton or the next climate control unit that goes in an apartment or house, and also these longtime legacy devices that are been on the factory floor for a couple of decades, but now are being kind of modernized and coming online. So, if you look at all of that growth of the data sources now being built up in the cloud and you look at all that growth of these connected devices, both new and existing, that are kind of coming online, there's a huge now exponential growth in the sources of data. And all of these sources are emitting time-series data. You can just think about a connected car—not even a self-driving car, just a connected car, your everyday, kind of, 2022 model, and nearly every element of the car is emitting time-series data: its engine components, you know, your tires, like, what the climate inside of the car is, statuses of the engine itself, and it's all doing that in real-time, so every one second, every five seconds, whatever.So, I think in general, people just don't realize they're already dealing with a substantial workload of time series. And in most cases, unless they're using something like Influx, they're probably not, you know, especially tuned to handle it from a technology perspective.Corey: So, it's been a year. What has changed over on your side of the world since the last time we spoke? It seems that well, things continue and they're up and to the right. Well, sure, generally speaking, you're clearly still in business. Good job, always appreciative of your custom, as well as the fact that oh, good, even in a world where it seems like there's a macro recession in progress, that there are still companies out there that continue to persist and in some cases, dare I say, even thrive? What have you folks been up to?Brian: Yeah, it's been a big year. So first, we've seen quite a bit of expansion across the use cases. So, we've seen even further expansion in IoT, kind of expanding into consumer, industrial, and now sustainability and clean energy, and that pairs with what we've seen on FinTech and cryptocurrency, gaming and entertainment applications, network telemetry, including some of the biggest names in telecom, and then a little bit more on the cloud side with cloud services, infrastructure, and dev tools and APIs. So, quite a bit more broad set of use cases we're now seeing across the platform. And the second thing is—you might have seen it in the last month or so—is a pretty big announcement we had of our new storage engine.So, this was just announced earlier this month in November and was previously introduced to our community as what we call an IOx, which is how it was known in the open-source. And think of this really as a rebuilt and reimagined storage engine which is built on that open-source project, InfluxDB IOx that allows us to deliver faster queries, and now—pretty exciting for the first time—unlimited time-series, or cardinality as it's known in the space. And then also we introduced SQL for writing queries and BI tool support. And this is, for the first time we're introducing SQL, which is world's most popular data programming language to our platform, enabling developers to query via the API our language Flux, and InfluxQL in addition.Corey: A long time ago, it really seems that the cloud took a vote, for lack of a better term, and decided that when it comes to storage, object store is the way forward. It was a bit of a reimagining from how we all considered using storage previously, but the economics are at minimum of ten to one in favor of objects store, the latency is far better, the durability is off the charts better, you don't have to deal—at least in AWS-land—with the concept of availability zones and the rest, just from an economic and performance perspective, provided the use case embraces it, there's really no substitute.Brian: Yeah, I mean, the way we think about storage is, you know, obviously, it varies quite a bit from customer to customer with our use cases. Especially in IoT, we see some use cases where customers want to have data around for months and in some cases, years. So, it's a pretty substantial data set you're often looking at. And sometimes those customers want to downsample those, they don't necessarily need every single piece of minutia that they may need in real-time, but not in summary, looking backward. So, you really—we're in this kind of world where we're dealing with both hive fidelity—usually in the moment—data and lower fidelity, when people can downsample and have a little bit more of a summarized view of what happened.So, pretty unique for us and we have to kind of design the product in a way that is able to balance both of those because that's what, you know, the customer use cases demand. It's a super hard problem to solve. One of the reasons that you have a product like InfluxDB, which is specialized to handle this kind of thing, is so that you can actually manage that balance in your application service and setting your retention policy, et cetera.Corey: That's always been something that seemed a little on the odd side to me when I'm looking at a variety of different observability tools, where it seems that one of the key dimensions that they all tend to, I guess, operate on and price on is retention period. And I get it; you might not necessarily want to have your load balancer logs from 2012 readily available and paying for the privilege, but it does seem that given the dramatic fall of archival storage pricing, on some level, people do want to be able to retain that data just on the off chance that will be useful. Maybe that's my internal digital packrat chiming in at this point, but I do believe strongly that there is a correlation between how recent the data is and how useful it is, for a variety of different use cases. But that's also not a global truth. How do you view the divide? And what do you actually see people saying they want versus what they're actually using?Brian: It's a really good question and not a simple problem to solve. So, first of all, I would say it probably really depends on the use case and the extent to which that use case is touching real world applications and services. So, in a pure observability setting where you're looking at, perhaps more of a, kind of, operational view of infrastructure monitoring, you want to understand kind of what happened and when those tend to be a little bit more focused on real-time and recent. So, for example, you of course, want to know exactly what's happening in the moment, zero in on whatever anomaly and kind of surrounding data there is, perhaps that means you're digging into something that happened in you know, fairly recent time. So, those do tend to be, not all of them, but they do tend to be a little bit more real-time and recent-oriented.I think it's a little bit different when we look at IoT. Those generally tend to be longer timeframes that people are dealing with. Their physical out-in-the-field devices, you know, many times those devices are kind of coming online and offline, depending on the connectivity, depending on the environment, you can imagine a connected smart agriculture setup, I mean, those are a pretty wide array of devices out and in, you know, who knows what kind of climate and environment, so they tend to be a little bit longer in retention policy, kind of, being able to dig into the data, what's happening. The time frame that people are dealing with is just, in general, much longer in some of those situations.Corey: One story that I've heard a fair bit about observability data and event data is that they inevitably compose down into metrics rather than events or traces or logs, and I have a hard time getting there because I can definitely see a bunch of log entries showing the web servers return codes, okay, here's the number of 500 errors and number of different types of successes that we wind up seeing in the app. Yeah, all right, how many per minute, per second, per hour, whatever it is that makes sense that you can look at aberrations there. But in the development process at least, I find that having detailed log messages tell me about things I didn't see and need to understand or to continue building the dumb thing that I'm in the process of putting out. It feels like once something is productionalized and running, that its behavior is a lot more well understood, and at that point, metrics really seem to take over. How do you see it, given that you fundamentally live at that intersection where one can become the other?Brian: Yeah, we are right at that intersection and our answer probably would be both. Metrics are super important to understand and have that regular cadence and be kind of measuring that state over time, but you can miss things depending on how frequent those metrics are coming in. And increasingly, when you have the amount of data that you're dealing with coming from these various sources, the measurement is getting smaller and smaller. So, unless you have, you know, perfect metrics coming in every half-second, or you know, in some sub-partition of that, in milliseconds, you're likely to miss something. And so, events are really key to understand those things that pop up and then maybe come back down and in a pure metric setting, in your regular interval, you would have just completely missed. So, we see most of our use cases that are showing a balance of the two is kind of the most effective. And from a product perspective, that's how we think about solving the problem, addressing both.Corey: One of the things that I struggled with is it seems that—again, my approach to this is relatively outmoded. I was a systems administrator back when that title was not considered disparaging by a good portion of the technical community the way that it is today. Even though the job is the same, we call them something different now. Great. Okay, whatever smile, nod, and accept the larger paycheck.But my way of thinking about things are okay, you have the logs, they live on the server itself. And maybe if you want to be fancy, you wind up putting them to a centralized rsyslog cluster or whatnot. Yes, you might send them as well to some other processing system for visibility or a third-party monitoring system, but the canonical truth slash source of logs tends to live locally. That said, I got out of running production infrastructure before this idea of ephemeral containers or serverless functions really became a thing. Do you find that these days you are the source of truth slash custodian of record for these log entries, or do you find that you are more of a secondary source for better visibility and analysis, but not what they're going to bust out when the auditor comes calling in three years?Brian: I think, again, it—[laugh] I feel like I'm answering the same way [crosstalk 00:15:53]Corey: Yeah, oh, and of course, let's be clear, use cases are going to vary wildly. This is not advice on anyone's approach to compliance and the rest [laugh]. I don't want to get myself in trouble here.Brian: Exactly. Well, you know, we kind of think about it in terms of profiles. And we see a couple of different profiles of customers using InfluxDB. So, the first is, and this was kind of what we saw most often early on, still see quite a bit of them is kind of more of that operator profile. And these are folks who are going to—they're building some sort of monitor, kind of, source of truth for—that's internally facing to monitor applications or services, perhaps that other teams within their company built.And so that's, kind of like, a little bit more of your kind of pure operator. Yes, they're building up in the stack themselves, but it's to pay attention to essentially something that another team built. And then what we've seen more recently, especially as we've moved more prominently into the cloud and offered a usage-based service with a, you know, APIs and endpoint people can hit, as we see more people come into it from a builder's perspective. And similar in some ways, except that they're still building kind of a, you know, a source of truth for handling this kind of data. But they're also building the applications and services themselves are taken out to market that are in the hands of customers.And so, it's a little bit different mindset. Typically, there's, you know, a little bit more comfort with using one of many services to kind of, you know, be part of the thing that they're building. And so, we've seen a little bit more comfort from that type of profile, using our service running in the cloud, using the API, and not worrying too much about the kind of, you know, underlying setup of the implementation.Corey: Love how serverless helps you scale big and ship fast, but hate debugging your serverless apps? With Lumigo's serverless observability, it's fast and easy (and maybe a little fun, too). End-to-end distributed tracing gives developers full clarity into their most complex serverless and containerized applications, connecting every service from AWS Lambda and Amazon ECS to DynamoDB, API Gateways, Step Functions and more. Try Lumigo free and debug 3x faster, reduce error rate and speed up development. Visit snark.cloud/lumigo That's snark.cloud/L-U-M-I-G-OCorey: So, I've been on record a lot saying that the best database is TXT records stuffed into Route 53, which works super well as a gag, let's be clear, don't actually build something on top of this, that's a disaster waiting to happen. I don't want to destroy anyone's career as I do this. But you do have a much more viable competitive threat on the landscape. And that is quite simply using the open-source version of InfluxDB. What is the tipping point where, “Huh, I can run this myself,” turns into, “But I shouldn't. I should instead give money to other people to run it for me.”Because having been an engineer, where I believe I'm the world's greatest everything, when it comes to my environment—a fact provably untrue, but that hubris never quite goes away entirely—at what point am I basically being negligent not to start dealing with you in a more formalized business context?Brian: First of all, let me say that we have many customers, many developers out there who are running open-source and it works perfectly for them. The workload is just right, the deployment makes sense. And so, there are many production workloads we're using open-source. But typically, the kind of big turning point for people is on scale, scale, and overall performance related to that. And so, that's typically when they come and look at one of the two commercial offers.So, to start, open-source is a great place to, you know, kind of begin the journey, check it out, do that level of experimentation and kind of proof of concept. We also have 60,000-plus developers using our introductory cloud service, which is a free service. You simply sign up and can begin immediately putting data into the platform and building queries, and you don't have to worry about any of the setup and running servers to deploy software. So, both of those, the open-source and our cloud product are excellent ways to get started. And then when it comes time to really think about building in production and moving up in scale, we have our two commercial offers.And the first of those is InfluxDB Cloud, which is our cloud-native fully managed by InfluxData offering. We run this not only in AWS but also in Google Cloud and Microsoft Azure. It's a usage-based service, which means you pay exactly for what you use, and the three components that people pay for our data in, number of queries, and the amount of data you store in storage. We also for those who are interested in actually managing it themselves, we have InfluxDB Enterprise, which is a software subscription-base model, and it is self-managed by the customer in their environment. Now, that environment could be their own private cloud, it also could be on-premises in their own data center.And so, lots of fun people who are a little bit more oriented to kind of manage software themselves rather than using a service gear toward that. But both those commercial offers InfluxDB Cloud and InfluxDB Enterprise are really designed for, you know, massive scale. In the case of Cloud, I mentioned earlier with the new storage engine, you can hit unlimited cardinality, which means you have no limit on the number of time series you can put into the platform, which is a pretty big game-changing concept. And so, that means however many time-series sources you have and however many series they're emitting, you can run that without a problem without any sort of upper limit in our cloud product. Over on the enterprise side with our self-managed product, that means you can deploy a cluster of whatever size you want. It could be a two-by-four, it could be a four-by-eight, or something even larger. And so, it gives people that are managing in their own private cloud or in a data center environment, really their own options to kind of construct exactly what they need for their particular use case.Corey: Does your object storage layer make it easier to dynamically change clusters on the fly? I mean, historically, running things in a pre-provisioned cluster with EBS volumes or local disk was, “Oh, great. You want to resize something? Well, we're going to be either taking an outage or we're going to be building up something, migrating data live, and there's going to be a knife-switch cutover at some point that makes things relatively unfortunate.” It seems that once you abstract the storage layer away from anything resembling an instance that you would be able to get away from some of those architectural constraints.Brian: Yeah, that's really the promise, and what is delivered in our cloud product is that you no longer, as a developer, have to think about that if you're using that product. You don't have to think about how big the cluster is going to be, you don't have to think about these kind of disaster scenarios. It is all kind of pre-architected in the service. And so, the things that we really want to deliver to people, in addition to the elimination of that concern for what the underlying infrastructure looks like and how its operating. And so, with infrastructure concerns kind of out of the way, what we want to deliver on are kind of the things that people care most about: real-time query speed.So, now with this new storage engine, you can query data across any time series within milliseconds, 100 times faster queries against high cardinality data that was previously impossible. And we also have unlimited time-series volume. Again, any total number of time series you have, which is known as cardinality, is now able to run without a problem in the platform. And then we also have kind of opening up, we're opening up the aperture a bit for developers with SQL language support. And so, this is just a whole new world of flexibility for developers to begin building on the platform. And again, this is all in the way that people are using the product without having to worry about the underlying infrastructure.Corey: For most companies—and this does not apply to you—their core competency is not running time-series databases and the infrastructure attendant thereof, so it seems like it is absolutely a great candidate for, “You know, we really could make this someone else's problem and let us instead focus on the differentiated thing that we are doing or building or complaining about.”Brian: Yeah, that's a true statement. Typically what happens with time-series data is that people first of all, don't realize they have it, and then when they realize they have time-series data, you know, the first thing they'll do is look around and say, “Well, what do I have here?” You know, I have this relational database over here or this document database over here, maybe even this, kind of, search database over here, maybe that thing can handle time series. And in a light manner, it probably does the job. But like I said, the sources of data and just the volume of time series is expanding, really across all these different use cases, exponentially.And so, pretty quickly, people realize that thing that may be able to handle time series in some minor manner, is quickly no longer able to do it. They're just not purpose-built for it. And so, that's where really they come to a product like Influx to really handle this specific problem. We're built specifically for this purpose and so as the time-series workload expands when it kind of hits that tipping point, you really need a specialized tool.Corey: Last question, before I turn you loose to prepare for re:Invent, of course—well, I guess we'll ask you a little bit about that afterwards, but first, we can talk a lot theoretically about what your product could or might theoretically do. What are you actually seeing? What are the use cases that other than the stereotypical ones we've talked about, what have you seen people using it for that surprised you?Brian: Yeah, some of it is—it's just really interesting how it connects to, you know, things you see every day and/or use every day. I mean, chances are, many people listening have probably use InfluxDB and, you know, perhaps didn't know it. You know, if anyone has been to a home that has Tesla Powerwalls—Tesla is a customer of ours—then they've seen InfluxDB in action. Tesla's pulling time-series data from these connected Powerwalls that are in solar-powered homes, and they monitor things like health and availability and performance of those solar panels and the battery setup, et cetera. And they're collecting this at the edge and then sending that back into the hub where InfluxDB is running on their back end.So, if you've ever seen this deployed like that's InfluxDB running behind the scenes. Same goes, I'm sure many people have a Nest thermostat in their house. Nest monitors the infrastructure, actually the powers that collection of IoT data collection. So, you think of this as InfluxDB running behind the scenes to monitor what infrastructure is standing up that back-end Nest service. And this includes their use of Kubernetes and other software infrastructure that's run in their platform for collection, managing, transforming, and analyzing all of this aggregate device data that's out there.Another one, especially for those of us that streamed our minds out during the pandemic, Disney+ entertainment, streaming, and delivery of that to applications and to devices in the home. And so, you know, this hugely popular Disney+ streaming service is essentially a global content delivery network for distributing all these, you know, movies and video series to all the users worldwide. And they monitor the movement and performance of that video content through this global CDN using InfluxDB. So, those are a few where you probably walk by something like this multiple times a week, or in our case of Disney+ probably watching it once a day. And it's great to see InfluxDB kind of working behind the scenes there.Corey: It's one of those things where it's, I guess we'll call it plumbing, for lack of a better term. It's not the sort of thing that people are going to put front-and-center into any product or service that they wind up providing, you know, except for you folks. Instead, it's the thing that empowers a capability behind that product or service that is often taken for granted, just because until you understand the dizzying complexity, particularly at scale, of what these things have to do under the hood, it just—well yeah, of course, it works that way. Why shouldn't it? That's an expectation I have of the product because it's always had that. Yeah, but this is how it gets there.Brian: Our thesis really is that data is best understood through the lens of time. And as this data is expanding exponentially, time becomes increasingly the, kind of, common element, the common component that you're using to kind of view what happened. That could be what's running through a telecom network, what's happening with the devices that are connected that network, the movement of data through that network, and when, what's happening with subscribers and content pushing through a CDN on a streaming service, what's happening with climate and home data in hundreds of thousands, if not millions of homes through common device like a Nest thermostat. All of these things they attach to some real-world collection of data, and as long as that's happening, there's going to be a place for time-series data and tools that are optimized to handle it.Corey: So, my last question—for real this time—we are recording this the week before re:Invent 2022. What do you hope to see, what do you expect to see, what do you fear to see?Brian: No fears. Even though it's Vegas, no fears.Corey: I do have the super-spreader event fear, but that's a separate—Brian: [laugh].Corey: That's a separate issue. Neither one of us are deep into the epidemiology weeds, to my understanding. But yeah, let's just bound this to tech, let's be clear.Brian: Yeah, so first of all, we're really excited to go there. We'll have a pretty big presence. We have a few different locations where you can meet us. We'll have a booth on the main show floor, we'll be in the marketplace pavilion, as I mentioned, InfluxDB Cloud is offered across the marketplaces of each of the clouds, AWS, obviously in this case, but also in Azure and Google. But we'll be there in the AWS Marketplace pavilion, showcasing the new engine and a lot of the pretty exciting new use cases that we've been seeing.And we'll have our full team there, so if you're looking to kind of learn more about InfluxDB, or you've checked it out recently and want to understand kind of what the new capability is, we'll have many folks from our technical teams there, from our development team, some our field folks like the SEs and some of the product managers will be there as well. So, we'll have a pretty great collection of experts on InfluxDB to answer any questions and walk people through, you know, demonstrations and use cases.Corey: I look forward to it. I will be doing my traditional Wednesday afternoon tour through the expo halls and nature walk, so if you're listening to this and it's before Wednesday afternoon, come and find me. I am kicking off and ending at the [unintelligible 00:29:15] booth, but I will make it a point to come by the Influx booth and give you folks a hard time because that's what I do.Brian: We love it. Please. You know, being on the tour is—on the walking tour is excellent. We'll be mentally prepared. We'll have some comebacks ready for you.Corey: Therapists are standing by on both sides.Brian: Yes, exactly. Anyway, we're really looking forward to it. This will be my third year on your walking tour. So, the nature walk is one of my favorite parts of AWS re:Invent.Corey: Well, I appreciate that. Thank you. And thank you for your time today. I will let you get back to your no doubt frenzied preparations. At least they are on my side.Brian: We will. Thanks so much for having me and really excited to do it.Corey: Brian Mullen, CMO at InfluxData, I'm Cloud Economist Corey Quinn and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice, along with an insulting comment that you naively believe will be stored as a TXT record in a DNS server somewhere rather than what is almost certainly a time-series database.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

About PerryPerry Krug currently leads the Shared Services team which is focused on building tools and managing infrastructure and data to increase the productivity of Couchbase's Sales and Field organisations.  Perry has been with Couchbase for over 12 years and has served in many customer-facing technical roles, helping hundreds of customers understand, deploy, and maintain Couchbase's NoSQL database technology.  He has been working with high performance caching and database systems for over 15 years.Links Referenced: Couchbase: https://www.couchbase.com/ Perry's LinkedIn: https://www.linkedin.com/in/perrykrug/ TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is brought to us by our friends at Pinecone. They believe that all anyone really wants is to be understood, and that includes your users. AI models combined with the Pinecone vector database let your applications understand and act on what your users want… without making them spell it out. Make your search application find results by meaning instead of just keywords, your personalization system make picks based on relevance instead of just tags, and your security applications match threats by resemblance instead of just regular expressions. Pinecone provides the cloud infrastructure that makes this easy, fast, and scalable. Thanks to my friends at Pinecone for sponsoring this episode. Visit Pinecone.io to understand more.Corey: InfluxDB is the smart data platform for time series. It's built from the ground-up to handle the massive volumes and countless sources of time-stamped data produced by sensors, applications, and systems. You probably think of these as logs.InfluxDB is programmable and performant, has a common API across the platform, and handles high granularity data–at scale and with high availability. Use InfluxDB to build real-time applications for analytics, IoT, and cloud-native services, all in less time and with less code. So go ahead–turn your apps up to 11 and start your journey to Awesome for free at InfluxData.com/screaminginthecloudCorey: Welcome to Screaming in the Cloud. I'm Corey Quinn. Today's episode is a promoted guest episode brought to us by our friends at Couchbase. Now, I want to start off by saying that this week is AWS re:Invent. And there is Last Week in AWS swag available at their booth. More on that to come throughout the next half hour or so of conversation. But let's get right into it. My guest today is Perry Krug, Director of Shared Services over at Couchbase. Perry, thanks for joining me.Perry: Hey, Corey, thank you so much for having me. It's a pleasure.Corey: So, we're recording this before re:Invent, so the fact that we both have, you know, personality and haven't lost our voices yet should probably be a bit of a giveaway on this. But I want to start at the very beginning because unlike people who are academically successful, I tend to suck at doing the homework, across the board. Couchbase has been around for a long time. We've seen the company do a bunch of different things, most importantly and notably, sponsoring my ridiculous nonsense for which I thank you. But let's start at the beginning. What is Couchbase?Perry: Yeah, you're very welcome, Corey. And it's again, it's a pleasure to be here. So, Couchbase is an enterprise database company at the very top level. We make database software and we distribute that to our customers. We have two flavors, two ways of getting your hands on it.One is the kind of legacy, what we call self-managed, where you the user, the customer, downloads the software, installs it themselves, sets it up, manages the cluster monitoring, scaling all of that. And that's, you know, a big part of our business. Over the last few years we've identified, and certainly others in the industry have, as well the desire for users to access database and other technology in a hosted Software-as-a-Service pay-as-you-go, cloud-native, buzzword, et cetera, et cetera, vehicle. And so, we've released the Couchbase Capella, which is our fully managed, fully hosted database-as-a-service, running in—currently—Amazon and Google, soon to be Azure as well. And it wraps and extends our core Couchbase Server product into a, as I mentioned, hosted and managed platform that our users can now come to and consume as developers and build their applications while leaving all of the operational and administration—monitoring, managing failover expansion, all of that—to us as the experts.Corey: So, you folks are non-relational database, NoSQL in the common parlance, which is odd because they call it NoSQL, yet. They keep making more of them, so I feel like that's sort of the Hollywood model where okay, that was so good. We're going to do it again. Where did NoSQL come from? Because back when I was learning databases, when dinosaurs roamed the earth, it was all about relational models, like we're going to use a relational database because when the only tool you have is an axe, every problem looks like hours of fun. What gave rise to this, I guess, Cambrian explosion that we've seen of NoSQL options that proliferate o'er the land?Perry: Yeah, a really, really good question, and I like the axe-throwing metaphor. So sure, 20, 30, 40 now years ago, as digital applications needed a place to store their data, the world invented relational databases. And those were used and continue to be used very well for what they were designed for, for data that follows a very strict structure that doesn't need to be served at significant scale, does not need to be replicated geographically, does not need to handle data coming in from different sources and those sources changing their formats of things all the time. And so, I'm probably as old as you are and been around when the dinosaurs were there. We remember this term called ‘Web 2.0.' Kids, you're going to have to go look that up in the dictionary or TikTok it or something.But Web 2.0 really was the turning point when websites became web applications. And suddenly, there was the introduction of MySpace and Facebook and Amazon and Google and LinkedIn, and a number of others, and they realized that relational databases we're not going to meet their needs, whether it be performance, whether it be flexibility, whether it be changing of data models, whether it be introducing new features at a rapid pace. They tried; they stretched them, they added a bunch of different databases together, and really was not going to be a viable solution. So, 10 now, maybe 15 years ago, you started to see the rise of these tech giants—although we didn't call them tech giants back then but they were the precursors to today's—invent their own new databases.So, Amazon had theirs, Google has theirs, LinkedIn, and a number of others. These companies had reached a level of scale and reached a level of user base, had reached a level of data requirement, had reached a level of expectation with their customers. These customers, us, the users, us consumers, we expect things to be fast, we expect them to be always available. We expect Facebook to give us our news feed in milliseconds. We expect Google to give us our website or our search results in immediate, with more and more information coming along with them.And so, it was these companies that hit those requirements first. The only solution for them was to start from scratch and rewrite their own databases. Fast forward five, six, seven years, and we as consumers turned around and said, “Look, I really liked the way Facebook does things. I really like the way Google does things. I really like the way Amazon does things.“Bank of America, can you do the same? IRS, can you do the same? Health care vendor number one, two, three, and four, government body, can you all give me the same experience? I want my taxi to tell me exactly where it's going to take me from one place to another, I want it to give me a receipt immediately after I finish my ride. Actually, I want to be able to change my payment method after I paid for that ride because I used the wrong one.”All of these are expectations that we as consumers have taken from the tech giants—Apple, LinkedIn, Facebook—and turned around to nearly every other service that we interact with on a daily basis. And all of a sudden, the requirements that Facebook had, that Google had, that no other company had, you know, outside of the top five, suddenly were needed by every single industry, nearly every single company, in order to be competitive in their markets.Corey: And there's no way to scale relational to get to a point where it can wind up handling those type workloads efficiently?Perry: Correct, correct. And it's not just that the technology cannot do it—everything is technically feasible—but the cost both financially and time-to-market-wise in order to do that in a relational database was untenable. It either cost too much money, or it costs too much developers time, or cost too much of everybody's time to try to shoehorn something into it. And then you have the rise of cloud and containers, which relational databases, you know, never even had the inkling of a thought that they might need to be able to handle someday. And so, these requirements that consumers have been placed on everything else that they interact with really led to the rise of NoSQL as a commodity or as a database for the masses.LinkedIn is not in the business of developing a database and then selling it to everybody else to use as a database, right? They built it for themselves, they made their service better. And so, what you see is some of those founding fathers created databases, but then had no desire to sell them to others. And then after that followed the rise of companies like Couchbase and a number of others who said, “Look, we think we can provide those capabilities, we think we can meet those requirements for everybody.” And thereby rose the plethora of NoSQL databases because everybody had a little bit different of an approach to it.If you ask ten people what NoSQL is about, you're going to get eleven or twelve different answers. But you can kind of distill that into two categories. One is performance and operations. So, I need it to be faster, I need it to be scalable, I need it to be replicated geographically. And that's what NoSQL is to me. And that's the right answer.And so, you have things like Cassandra and Redis that are meant to be fast and scalable and replicated. You ask another group and they're going to tell you, “No, no, no. NoSQL needs to be flexible. I need to get rid of the rigid database schemas, I need to bring JSON or other data formats in and munge all this data together and create something cool and new out of it.” And thereby you have the rise of things like MongoDB, who focused nearly exclusively on the developer experience of working with data.And for a long time, those two were in opposite camps, where you have the databases that did performance and the databases that did flexibility. I'm not here to say that Couchbase is the ultimate kitchen sink for everything, but we've certainly tried to approach both of those challenges together so that you can have something that scales and performs and can be flexible enough in data model. And everybody else is trying to do the same thing, right? But all these databases are competing for that same nirvana of the best of both worlds.Corey: And it almost feels like there's a convergence play in place where everything now is trying to go away from the idea of, “Oh, yeah, we started off as a purpose-built database, but you can use this for everything.” And I don't necessarily know that is going to be the path that a lot of companies want to go down. What do you view Couchbase as I guess, falling down? In other words, what workloads is Couchbase inappropriate for?Perry: Yeah, that's a good question. And my [crosstalk 00:10:35]—Corey: Anyone who can't answer that one is a zealot and that's one of those okay, let's be very careful and not take our eyes off you for one second, while smiling and backing away slowly.Perry: Let's cut to commercial. No, I mean, there certainly are workloads that you know, in the past, we've not been good for that we've made improvements to address. There are workloads that we had not address well today that we will try to address in the future, and there are workloads that we may never see as fitting in our wheelhouse. The biggest category group that comes to mind is Couchbase is not an archival database. We are not meant to have data put in us that you don't care about, that you don't want to—that you just need to keep it around, but you don't ever need to access.And there are systems that do that well, they do that at a solid total cost of ownership. And Couchbase is meant for operational data. It's meant for data that needs to be interacted with, read and/or written, at scale and at a reasonable performance to serve a user-facing or system-facing application. And we call ourselves a general-purpose database. Bongo and others call themselves as well. Oracle calls itself a general-purpose database, and yet, not everybody uses Oracle for everything.So, there are reasons that you—Corey: Who could afford that?Perry: Who could? Exactly. It comes down to cost, ultimately. So, I'm not here to say that Couchbase does everything. We like to think, and we're trying to target and strive towards an 80%, right? If we can do 80% of an application or an organization's workloads, there is certainly room for 20% of other workloads, other applications, other requirements that can be met or need to be met by purpose-built databases.But if you rewind four or five years, there was this big push towards polyglot persistence. It's a buzzword that came and kind of has gone out of fashion, but it presented the idea that everybody is going to use 15 different databases and everybody is going to pick the right one for exactly the workload and they're going to somehow stitch them all together. And that really hasn't come to fruition either. So, I think there's some balance, where it's not one to rule them all, but it's also not 15 for every company. Some organizations just have a set of requirements that they want to be met and our database can do that.Corey: Let's continue our tour of the competitive landscape here now that we've handled the relational side of the world. The best database, as anyone who's listened to this show knows, is of course, Amazon's Route 53 TXT records stuffed into DNS, especially in the NoSQL land. Clearly, you're all fighting for second place after that. How do you stack up against the idea of legitimately using that approach? And for those who are not in on the joke, please don't do this. It is not the right answer. But I'm curious to get your take as to why DNS TXT records are an inappropriate NoSQL option.Perry: Well, it's a joke, right? And let's be clear about that. But—Corey: I have to say that because otherwise, someone tries it in production. I've gotten that wrong a few times, historically, so now I put a disclaimer in because yeah, it's only funny, so long as people are in on the joke. If not, and I lead someone down the primrose path to disaster, I feel bad. So, let's be very clear. We're kidding.Perry: And I'm laughing. I'm laughing here behind the camera. I am. I am.Corey: Yeah.Perry: So, the element of truth that I think Couchbase is in a position, or I'm in a position to kind of talk about is, 12 years ago, when Couchbase started, we were a key-value database and that's where we saw the best part of the market in those days, and where we were able to achieve the best scale and replication and performance, and fairly quickly realized that simple key-value, though extremely valuable and easy to manage, was not broad enough in requirements-meeting. And that's where we set our sights on and identified the larger, kind of, document database group, which is really just a derivative of key-value, where still everything is a key and a value; it's just now a document that you can reason about, that you can create an index on, that you can query, that you can run full-text search on, you can do much more with the data. So, at our core, we are still a key-value database. When that value is JSON, we become a document database. And so, if Route 53 decided that they wanted to enter into the document database market, they would need to be adding things that allowed you to introspect and ask questions of the data within that text which you can't, right?Corey: Well, not with that attitude. But yeah, I agree with you.Perry: [laugh].Corey: Moving up the stack, let's talk about a much more fearsome competitor here that I'm certain you see an awful lot of deals that you wind up closing, specifically your own open-source product. You historically have wound up selling software into environments, I believe, you referred to as your legacy offering where it's the hosted version of your commercial software. And now of course, you also have Capella, your cloud-hosted version. But open-source looks surprisingly compelling for an awful lot of use cases and an awful lot of folks. What's the distinction?Perry: Sure. Just to correct a little bit the distinction, we have Couchbase Server, which we provide as a what we call self-managed, where you can download it and install it yourself. Now, you could do that with the open-source version or you could do that with our Enterprise Edition. What we've then done is wrapped that Enterprise Edition in a hosted bottle, and that's Capella. So, the open-source version is something we've long been supporters of; it's been a core part of our go-to-market for the last 12 or 13 years or so and we still see it as a strong offering for organizations that don't need the added features, the added capabilities, don't need the support of the experts that wrote the software behind them.Certainly, we contribute and support our community through our forums and Discord and other channels, but that's a very big difference than two o'clock in the morning, something's not working and I need a ticket to track. We don't do that for our community edition. So, we see lots of users downloading that, picking it up building it into their applications, especially applications that are in their infancy or are with organizations that they simply can't afford the added cost and therefore they don't get the added benefit. We're not here to gouge and carve out every dollar that we can, but if you need the benefit that we can provide, we think there's value in that and that's what we're trying to run a business as.Corey: Oh, absolutely. It doesn't work when you're trying to wind up charging a license fee for something that someone is doing in their spare time project for funsies just to learn the technology. It's like, and then you show up. It's like, “That'll be $700. Surprise.”Yeah, that's sort of the AWS billing model approach, where—it's not a viable onramp for most folks. So, the open-source direction down there make sense. Counterpoint. If you're running a bank on top of it, “Well, we're running it ourselves and really hoping for the best. I mean, we have access to the code and all.” Great, but there are times you absolutely want some of the best minds in the world, with respect to that particular product, able to help troubleshoot so the ATM start working again before people riot in the streets.Perry: Yeah, yeah. And ultimately, it's a question of core competencies. Are you an organization that wants to be in the database development market? Great, by all means, we'd love to support you in that. If you want to focus on doing what you do best be at a bank or an e-commerce website, you worry about your application, you let us worry about the database and everybody gets along very well.Corey: There's definitely something to be said for outsourcing some of the pain, some of the challenge around an awful lot of it.Perry: There's a natural progression to the cloud for that and Software-as-a-Service, database-as-a-service where you're now outsourcing even more by running on our hosting platform. No longer do you have to download the binary and install yourself, no longer do you have to setup the cluster and watch it in case it has a blip or the statistic goes up too far. We're taking care of that for you. So yes, you're paying for that service, but you're getting the value of not having to be a database manager, let alone database developer for them.Corey: Love how serverless helps you scale big and ship fast, but hate debugging your serverless apps? With Lumigo's serverless observability, it's fast and easy (and maybe a little fun, too). End-to-end distributed tracing gives developers full clarity into their most complex serverless and containerized applications, connecting every service from AWS Lambda and Amazon ECS to DynamoDB, API Gateways, Step Functions and more. Try Lumigo free and debug 3x faster, reduce error rate and speed up development. Visit snark.cloud/lumigo That's snark.cloud/L-U-M-I-G-OCorey: What is the point of distinction between Couchbase Server and Couchbase Capella? To be clear, your self-hosted versus managed cloud offerings. When is one appropriate versus the other?Perry: Well, I'm supposed to say that Capella is always the appropriate choice, but there are currently a number of situations where Capella is not available in particular regions or cloud providers and so downloading running the software yourself certainly in your own—yes, there are people who still run their own data centers. I know it's taboo and we don't like to talk about that, but there are people who have on-premise. And so, Couchbase Capella is not available for them. But Couchbase Server is the original Couchbase database and it is the core of Couchbase Capella. So, wrapping is not giving it enough credit; we use Couchbase Server to power Couchbase Capella.And so, there's an enormous amount of value added around the core database, but ultimately, it's the behind the scenes of Couchbase Capella. Which I think is a nice benefit in that when an application is connecting to either one, it gets the same experience. You can point an application at one versus the other and because it's the same database running behind the scenes, the behavior, the data model, the query language, the APIs are all the same, so it adds a nice level of flexibility four customers that are either moving from one to another or have to have some sort of hybrid approach, which we see in the market today.Corey: Let's talk economics for a second. I can see scenarios where especially you have a high volume environment where you're sending tremendous amounts of data back and forth and as soon as it crosses an availability zone boundary or a region boundary, or God forbid, goes out to the internet via standard egress fees over in AWS-land, there's a radically different economic modeling that comes into play as opposed to having something in the same availability zone, in the same subnet just where that—or all traffic back and forth is free. Do you see that in your customer base, that that is a model that is driving people towards self-hosting?Perry: No. And I'd say no because Capella allows you to peer and run your application in the same availability zone as the as a database. And so, as long as that's an option for you that we have, you know, our offering in the right region, in the right AZ, and you can put your application there, then that's not a not an issue. We did have a customer not too long ago that didn't set that up correctly, they thought they did, and we noticed some high data transfer charges. Again, the benefit of running a hosted service, we detected that for them and were able to turn around and say, “Hmm, you might want to change this to over there so that we all save some money in doing so.”If we were not there watching it, they might not have noticed that themselves if they were running it self-managed; they might not have known what to do about it. And so, there's a benefit to working with us and using that hosted platform that we can keep an eye out. And we can apply all of our learning and best practices and bug fixes, we give that to everybody, rather than each person having to stumble across those hurdles themselves.Corey: That's one of those fun, weird corner-case trivia things about AWS data transfer. When you're transferring data within the same region between availability zones, it costs a penny on the sending side and a penny on the receiving side. Everything else is one side or the other that winds up getting the charge. And what makes this especially fun is that when it shows up on your bill, if you transfer a petabyte, it shows as cross-AZ data transfer: two petabytes.Perry: Two. Yeah.Corey: So, it double-counts so they can bill for it appropriately, but it leads to some really weird hunting it down, like, “Okay, well, we found half of it, but where's the other half hiding?” It's always obnoxious to trace this stuff down. The fact that you see it on your bill, well, that's testament to the fact that yeah, they're using the service. Good for them and good for you. Being able to track it down on a per-customer basis that does speak to your level of insight into what exactly is going on in your environment and where. As someone who does this for a living, let me confirm that is absolutely non-trivial.Perry: No, definitely not trivial. And you know, we've learned over the last four or five years, we've learned an enormous amount about how cloud providers work, how AWS works, but guess what, Google does it completely differently. And Azure does it—Corey: Yep.Perry: —completely differently. And so, on the surface level, they're all just cloud providers and they give you a VM, and you put some stuff on it, but integrating with the APIs, integrating with the different systems and naming of things, and then understanding the intricacies of the ins and outs, and, yeah, these cloud providers have their own bugs as well. And so, sometimes you stumble across that for them. And it's been a significant learning exercise that I think we're all better off for, having Couchbase gone through it for you.Corey: Let's get this a little bit more germane for this week for those of you who are listening to this during re:Invent. You folks are clearly here at the show—it's funny to talk about ‘here,' even though when we're recording this, it is not near here; we're actually home and enjoying ourselves, but welcome to temporal dislocation; here we are—here at the show, you folks are—among other things—being kind enough to pass out the Last Week in AWS swag from your booth, which, thank you. So, that is obviously the primary reason that you were at the show. What are the other reasons? What are the secondary reasons that you decided to come here?Perry: Yeah [laugh]. Well, I guess I have to think about this now since you already called out the primary reason.Corey: Exactly. Wait, we can have more than one reason for things? My God.Perry: Can we? Can we? AWS has long been a huge partner of ours, even before Capella itself was released. I remember sometime in, you know, five years or so ago, some 30% of our customers were running Couchbase inside of AWS, and some of our largest were some of your largest at times, like Viber, the messaging platform. And so, we've always had a very strong relationship with AWS, and the better that we can be presenting ourselves to your customers, and our customers can feel that we are jointly supporting them, the better. And so, you know, coming to re:Invent is a testament to that long-standing and very solid partnership, and also it's meant to get more exposure for us to let it be clear that Couchbase runs very well on AWS.Corey: It's one of those areas where when someone says, “Oh yeah, this is a great service offering, but it doesn't run super well on AWS.” It's like, “Okay, so are you bad computers or is what you have built so broken and Byzantine that it has to live somewhere else?” Or occasionally, the use case is absolutely not supported by AWS. Not to beat them up some more on their egress fees, but I'm absolutely about to if you're building a video streaming site, you don't want it living in AWS. It won't run super well there. Well, it'll run well, it'll just run extortionately expensively and that means that it's a non-starter.Perry: Yeah, why do you think Netflix raises their fees?Corey: Netflix, to their credit, has been really rather public about this, where they do all of their egress via their Open Connect, custom-built CDN appliances that they drop all over the place. They don't stream a single byte from AWS, and we know this from the outside because they are clearly still solvent.Perry: [laugh].Corey: I do the math on that. So, if I had been streaming at on-demand prices one month with my Netflix usage, I would have wound up spending four times my subscription fee just in their raw costs for data transfer. And I have it on good authority that is not just data transfer that is their only bill in the entire company; they also have to pay people and content and the analytics engine and whatnot. And it's kind of a weird, strange world.Perry: Real estate.Corey: Yeah. Because it's one of those strange stories because they are absolutely a showcase customer for AWS. They've been a marquee customer trotted out year after year to talk about what they're doing. But if you attempt to replicate their business purely on top of AWS, it will not work. Full stop. The economics preclude that happening.What is your philosophy these days on what historically has felt like an existential threat to most vendors that I've spoken to in a variety of ways: what if Amazon decides to enter your market? I'd ask you the same thing. Do you have fears that they're going to wind up effectively taking your open-source offering and turning it into Amazon Basics Couchbase, for lack of a better term? Is that something that is on your threat radar, or is that not really something you concern yourselves about?Perry: So, I mean, there's no arguing, there's no illusion that Amazon and Google and Microsoft are significant competitors in the database space, along with Oracle and IBM and Mongo and a handful of others.Corey: Anything's a database if you hold it wrong.Perry: This is true. This specific point of open-source is something that we have addressed in the same ways that others have addressed. And that's by choosing and changing our license model so that it precludes cloud providers from using the open-source database to produce their own service on the back of it. Let me be clear, it does not impact our existing open-source users and anybody that wants to use the Community Edition or download the software, the source code, and build it themselves. It's only targeted at Amazon because they have a track record of doing that to things like Elastic and Redis and Mongo, all of whom who have made similar to Couchbase moves to prevent that by the licensing of the open-source code.Corey: So, one of the things I do see at re:Invent every year is—and I believe wholeheartedly this comes historically from a lot of AWS's requirements for vendors on the show floor that have become public through a variety of different ways—where you for a long time, you are not allowed to mention multi-cloud or reference the fact that you work on any other cloud provider there. So, there's been a theme of this is why, for whatever it is we sell or claim to sell or hope one day to sell, AWS is the absolute best place for you to run it, full stop. And in some cases, that's absolutely true because people build primarily for a certain cloud provider and then when they find customers and other places, they learn to run it over there, too. If I'm approaching this from the perspective of I have a database problem—because looking at my philosophy on databases is hard to imagine I don't have database problems—then is my experience going to be better or even materially different between any of the cloud providers if I become a Couchbase Capella customer?Perry: I'd like to say no. We've done our best to abstract and to leverage the best of all of the cloud providers underneath to provide Couchbase in the best form that they will allow us to. And as far as I can see, there's no difference amongst those. Your application and what you do with the data, that may be better suited to one provider or another, but it's always been Couchbase is philosophy—sort of say, strategy—to make our software available to wherever our customers and users want to, to consume it. And that goes everything from physical hardware running in a data center, virtual machines on top of that, containers, cloud, and different cloud providers, different regions, different availability zones, all the way through to edge and other infrastructures. We're not in a position to say, “If you want Couchbase, you should use AWS.” We're in a position to say, “If you are using AWS, you can have Couchbase.”Corey: I really want to thank you for being so generous with your time, and of course, your sponsorship dollars, which are deeply appreciated. Once again, swag is available at the Couchbase booth this week at re:Invent. If people want to learn more and if for some unfathomable reason, they're not at re:Invent, probably because they make good life choices, where can they go to find you?Perry: couchbase.com. That'll to be the best place to land on. That takes you to our documentation, our resources, our getting help, our contact pages, directly into Capella if you want to sign in or login. I would go there.Corey: And we will, of course, put links to that in the show notes. Thank you so much for your time. I really appreciate it.Perry: Corey, it's been a pleasure. Thank you for your questions and banter, and I really appreciate the opportunity to come and share some time with you.Corey: We'll have to have you back in the near future. Perry Krug, Director of Shared Services at Couchbase. I'm Cloud Economist Corey Quinn and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice, along with an angry and insulting comment berating me for being nowhere near musical enough when referencing [singing] Couchbase Capella.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

ServiceNow, the leading digital workflow company making the world work better for everyone, has announced it has signed an agreement to acquire observability and log management innovator, Era Software. Combined with ServiceNow's acquisition of Lightstep in 2021, Era Software will help provide customers with a unified observability solution at scale. Customers will be able to gather actionable insights that deliver value across the business, all within a single solution purpose-built for the era of digital business. Observability is foundational to digital transformation as it provides developers with the necessary insights to understand the performance of strategic applications at scale and translate that data into business value. Yet within large enterprises, observability often remains siloed and costly, creating a fragmented and complex experience for DevOps and SRE teams. Era Software's innovative technology and customer-centric approach to log management complements and augments existing features within Lightstep, and accelerates ServiceNow's path toward unified telemetry (logs, metrics, traces). “Digital transformation succeeds or fails based on unified observability,” says Ben Sigelman, general manager of ServiceNow's Lightstep business unit and co-founder of Lightstep. “Together, ServiceNow and Era Software are set up to deliver a unified and seamless observability experience within one solution, designed to scale.” As a founding member of the OpenTelemetry project, Lightstep leads the industry in a vision toward unified telemetry. Together, Era Software and Lightstep will further extend critical, unified observability workflows, removing the confusing context switches that hinder DevOps and SRE productivity at most enterprises today. Unified telemetry allows teams to innovate fast with precision and control, helping modern organizations deliver better outcomes across all their technology investments, capitalizing on the promise of digital transformation. “At Era Software, we created solutions to simplify the complex challenges of managing large volumes of observability data, with a particular focus on log management,” said Todd Persen, CEO and co?founder at Era Software. “We have always believed that observability should span across the enterprise. We are excited to join ServiceNow, as we further build a customer-centric model of observability that can help transform the way people work.” Since its inception, the Era Software team has engineered new approaches to log data management that resolves scale, performance, and cost issues associated with running distributed applications on modern cloud-native architectures. Seattle?based Era Software was co?founded in 2019 by CEO Todd Persen and CTO Robert Winslow. Persen was previously a co-founder and CTO at InfluxData, where he helped engineer the InfluxDB time-series database. With IDC forecasting the growth of the observability market to reach $9.08 billion by 2025, this announcement underscores ServiceNow's organic growth strategy with a focus on talent and technologies that strengthen the Now Platform with new and enhanced features for customers. It follows other recent ServiceNow acquisitions, including Hitch Works, DotWalk, Mapwize, and Gekkobrain. ServiceNow expects to complete the acquisition of Era Software in Q4 2022. Financial terms of the deal were not disclosed. See more stories here.

Brian introduces himself, InfluxData, and what time series data is. He then talks about how it compares to other data and its unique value and benefits. Brian then connects it to the real world by telling us how customers engage with InfluxData's product and use cases with which time series data works well. Ryan and Brian then move into a high-level conversation around challenges in the IoT space and advice for companies trying to recognize where they need to improve.Brian Gilmore is Director of IoT and Emerging Technology at InfluxData, the creators of InfluxDB. He has focused the last decade of his career on working with organizations worldwide to drive the unification of industrial and enterprise IoT with machine learning, cloud, and other truly transformational technology trends.InfluxData is the creator of InfluxDB, the leading time series platform. They empower developers and organizations like Cisco, IBM, Siemens, and Tesla to build real-time IoT, analytics, and cloud applications with time-stamped data. Their technology is purpose-built to handle the massive volumes of data produced by sensors, systems, or applications that change over time. Easy to start and scale, InfluxDB gives developers time to focus on the features and functionalities that give their apps a competitive edge.

How fast can data be collected and used in current business models? Evan Kaplan, CEO of Influxdata, claims that in the era of smart products, an autonomous system can utilize data collected every millisecond for instant responses. Listen in to learn more about how collecting instant data can provide better service for products and create loyalty with customers.Tune in to learn:What Influxdata does (01:12)  Monitoring data to build real-time responses (08:17)How quickly data is being recorded (13:40)Types of projects built with Influxdata (16:28)Influxdata's popularity with student engineers (20:17)Mentions:Check out our previous episode with Paul Dix also from Influx Data.“Memorial Day Murph” Crossfit RoutineIT Visionaries is powered by Salesforce Platform and Dreamforce 2022. Catch the news and insights coming out of Dreamforce this year for free on salesforce.com/plus. Content will start rolling on September 20th.Mission.org is a media studio producing content for world-class clients. Learn more at mission.org.

In today's episode, we're talking to Rick Spencer. Rick is VP of Product at InfluxData, a platform to help developers build time series-based applications quickly and at scale.   We talk about Rick's background, how InfluxData got started, and the kinds of problems it solves today. Rick describes the differences between building a product for developers and one for non-developers.   We go on to discuss the difference between a time series database and a regular database, the benefits of a time series database, the idea of data gravity, and the interaction between engineering and product teams.   This episode is brought to you by Qrvey The tools you need to take action with your data, on a platform built for maximum scalability, security, and cost efficiencies. If you're ready to reduce complexity and dramatically lower costs, contact us today at qrvey.com. Qrvey, the modern no-code analytics solution for SaaS companies on AWS. 

Diverse teams perform better. But what does a high-performing, diverse sales team look like? Arwa Kaddoura has firsthand knowledge to spare. She knows how to recruit, serve, and motivate record-breaking sales teams – who just happen to be diverse. Arwa is the Chief Revenue Officer at InfluxData, the purpose-built open source time series platform made by and for developers. In this episode, Arwa speaks with Gong's Danny Wasserman on the why behind diversifying, and how to sustainably hire and retain top talent across the board. Sign up for the Edge newsletter: https://www.gong.io/the-edge/

In this episode, we interview Brian Gilmore, director of IoT and Emerging Technology at InfluxData. InfluxData is the creator of InfluxDB, a pioneering time series platform that allows developers to build real-time IoT, analytics, and cloud applications with time-stamped data. They handle massive volumes of data produced by sensors, applications, and systems that change over time.  Today, we discuss how next-generation databases create new opportunities by enabling organizations to seamlessly integrate real-time IoT data streams with cloud databases. We also dive deep into the relationships between database technology and adjacent innovations in AI, AR, and blockchain.   Key Questions:  What is the right way to think about “real time” from the perspective of a user?  What are the unique uses of time series data, and what challenges does it present?  How are AI, AR and blockchain being integrated into IoT systems?  What recent database developments are improving management of complex IoT systems?  

About Anadelia Anadelia is a B2B marketing leader passionate about building tech brands and growing revenue. She is currently the Sr. Director of Demand Generation at Teleport. In her spare time she enjoys live music and craft beer.Links Referenced: Teleport: https://goteleport.com/ @anadeliafadeev: https://twitter.com/anadeliafadeev LinkedIn: https://www.linkedin.com/in/anadeliafadeev/ TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: DoorDash had a problem. As their cloud-native environment scaled and developers delivered new features, their monitoring system kept breaking down. In an organization where data is used to make better decisions about technology and about the business, losing observability means the entire company loses their competitive edge. With Chronosphere, DoorDash is no longer losing visibility into their applications suite. The key? Chronosphere is an open-source compatible, scalable, and reliable observability solution that gives the observability lead at DoorDash business, confidence, and peace of mind. Read the full success story at snark.cloud/chronosphere. That's snark.cloud slash C-H-R-O-N-O-S-P-H-E-R-E.Corey: Let's face it, on-call firefighting at 2am is stressful! So there's good news and there's bad news. The bad news is that you probably can't prevent incidents from happening, but the good news is that incident.io makes incidents less stressful and a lot more valuable. incident.io is a Slack-native incident management platform that allows you to automate incident processes, focus on fixing the issues and learn from incident insights to improve site reliability and fix your vulnerabilities. Try incident.io, recover faster and sleep more.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. This may surprise some of you to realize, but every once in a while, I mention how these episodes are sponsored by different companies. Well, to peel back a little bit of the mystery behind that curtain, I should probably inform some of you that when I say that, that means that companies have paid me to talk about them. I know, shocking.This is a revelation that will topple the podcast industry if it gets out. That's why it's just between us. My guest today knows this better than most. Anadelia Fadeev is the Senior Director of Demand Generation at Teleport, who does in fact sponsor a number of different things that I do, but this is not a sponsored episode in that context. Anadelia, thank you for joining me today.Anadelia: Thank you for having me.Corey: It's interesting. I always have to double-check where it is that you happen to be working because when we first met you were a Senior Marketing Manager, also in Demand Gen, at InfluxData, then you were a Director of Demand Generation at LightStep, and then you became a Director of Demand Gen and Growth and then a Senior Director of Demand Gen, where you are now at Teleport. And the couple of things that I've noticed are, one, you seem to more or less be not only doing the same role, but advancing within it, and also—selfishly—it turns out that every time you wind up working somewhere, that company winds up sponsoring some of my nonsense. So first, thank you for your business. It's always appreciated. Now, what is demand gen exactly? Because I have to say, when I started podcasting and newslettering and shooting my mouth off on the internet, I had no clue.Anadelia: [laugh]. Well, to put it very simply, demand generation, our goal is to drive awareness and interest in your products or services. It's as simple as that. Now, how we do that, we could definitely dive into the specifics, but it's all about generating awareness and interest. Especially when you work for an early-stage startup, it's all about awareness, right? Just getting your name out there.Corey: Marketing is one of those things that I suspect in some ways is kind of like engineering, where you take a look at, “Oh, what do you do? I'm a software engineer.” Okay, great. For someone who is in that space, does that mean front-end? Does that mean back-end? Does that mean security? Oh, wait, you're crying and awake at weird hours and you're angry all the time. You're a DevOps, aren't you?And you start to realize that there are these breakdowns within engineering. And we realize this and we get offended when people in some cases miscategorize us as, “I am not that kind of engineer. How dare you?” Which I think is unwarranted and ridiculous, but it also sort of slips under our notice in the engineering space that marketing is every bit as divided into different functions, different roles, and the rest. For those of us who think of marketing in the naive approach, like I did when I started this place—“Oh, marketing. So basically, you do Super Bowl ads, right?” And it turns out, there might be more than one or two facets to marketing. What's your journey been like in the wide world of marketing? Where did you start? Where does it stop?Anadelia: Yeah. I have not gotten to the Super Bowl ads phase yet but on my way there. No, but when you think about the different core areas within marketing, right, you have your product marketing team, and this is the team that sets the positioning, the messaging, and the information about who your ideal audience is, what pain points are they having, and how is your product solving those pain points? Right, so they sort of set the direction for the rest of the team, you have another core function, which is the content team, right? So, with the direction from Product Marketing, now that we know what the pain points are and what our value prop for our product is, how do we tell that to the world in a compelling way, right? So, this is where content marketing really comes into play.And then you have your demand generation teams. And some companies might call it growth or revenue or… I guess those two are the ones that come to mind. But this team is taking the direction from Product Marketing, taking the content produced by the content team, and then just making sure that people actually see it, right? And across all those teams, you have a lot of support from operations making sure that there's processes and systems in place to support all of those marketing efforts, you have teams that help support web development and design, and brand.Corey: One of the challenges that I think people have when they don't really understand what marketing is they think back on what they know—maybe they've seen Mad Men, which to my understanding does not much resemble modern all workplaces, but then again, I've been on my own for five years, so one wonders—and they also see things in the context of companies that are targeting more mass-market, in some respects. If you're trying to advertise Coca-Cola, every person on the planet—give or take—knows what Coca-Cola is. And the job is just to resurface it, on some level, in people's awareness, so the correct marketing answer there apparently, is to slap the logo on a bunch of things, be it a stadium, be it a billboard, be it almost anything, whereas when we're talking about earlier stage companies—oh, I don't know Teleport, for example—if you were to slap the Teleport logo on a stadium somewhere for some sports game, I have the impression that most people looking at that, if they notice it at all, would instead respond to some level of confusion of, “Teleport, what is that exactly? Have scientists cracked the way of getting me to Miami from San Francisco in less than ten seconds? Because I feel like I would have heard about that.”There's a matter of targeting beyond just the general public or human beings walking around and starting to target people who might have a problem that you know how to solve. And then, of course, figuring out where those people are gathering and how to get in front of them in a way that resonates instead of being annoying. At least that has been my lived experience of watching the challenges that marketing people have talked to me about over the years. Is that directionally correct or are they all just shining me on and, like, “Oh, Corey, you're adorable, you almost understand how this stuff works. Now, go insult some more things on Twitter. It'll be fine.”Anadelia: [laugh]. The reality is that advertising is a big part of a demand generation program, but it's not all, right? So, good demand generation is meeting people where they are. So, the right channels, the right mediums, the right physical places. So, when you look at it from an inbound and outbound approach, inbound, you have a sign outside of your door inviting people to your house, right, and this is in the form of your website. And outbound is you go out to where people are and you knock on their door to introduce yourself.So, when we look at it from that approach, so on the inbound side, right, the goal is to get people to come to your website because that is where you are telling them what you do and giving them the option to start using your product. So, what reason are you giving people to come to you, right? How are you helping them become better at something or achieve certain results, right? So, understanding the motivations behind it is extremely important.And how are you driving people to you? Well, that's where SEO comes in, right? Search engine optimization.So, what content are you producing that is driving the right search results to get your website to show up and get people to come to you, right? There's also SEM or Search Engine Marketing. So, when people are searching for certain keywords that are relevant to you, are you showing up in those search results?And on the outbound side of things is, what do you do to contribute to existing communities, right? So, this is where things like advertising comes into play. So, I know you have a huge following and I want to be where you are. So, of course, I'm going to sponsor your podcast and your newsletters. And similarly, I'm looking for what events are out there where I know that our potential customers are spending their time and what can we do to join that conversation in a way that adds value?So, that can be in the form of supporting community events and meetups, giving community members a platform to share their experiences, and even supporting local businesses, right, it's all about adding value, and by doing so, you are building trust that will allow you to then talk about how your product can help these communities solve their problems.Corey: It's interesting because when we look at the places that you have been, you were at InfluxData, they are a time-series database company; you were at LightStep, which was effectively an observability company, and now you're at Teleport where you are an authentication and access company. And forgive me, none of these are your terms. These are my understandings of having talked to these folks. And on the one hand, from a product perspective, it sounds like you're hopping between this and that and doing all those other things, and yet, we had conversations about all three of those products and how the companies around them are structured and built, and you've advertised all three of those on this show and others and all three of those companies and products speak specifically to problems that I have dealt with personally in the way I go through my engineering existence as well. So, instead of specializing on a particular product or on a particular niche, it almost feels like you're specializing on a particular audience. Is that how you think about it, or is that just one of those happy accident, or in retrospect, we're just going to retcon everything, and, “Yeah, that's exactly why I did it.” And you're like, “Let we jot that down. That belongs on my resume somewhere.”Anadelia: [laugh]. No, so prior to me joining InfluxData, I was at other companies that were marketing to sales, HR, finance, different audiences, right? And the moment I joined Influx, it was really eye-opening for me to be part of a product that has an open-source community, and between that and marketing to a highly technical audience that probably very likely doesn't want to hear from marketers, I found that to be a really good challenge for myself because it challenged me to elevate my own technical knowledge. And also personally, I just want to be surrounded by people that are smarter than me, and so I know that by being part of a community that markets to a developer audience, I am putting myself in a position where I'm having to constantly continue to learn. So, it's a good challenge for a marketer in our industry. Just like in any others, there's always the latest buzzword or the latest trend, and so it's really easy to get caught up in those things. And I think that being a marketer whose audience is developers really forces you to kind of look at what you're doing and sort of remove the fluff. This happens everywhere.Corey: Well, I have to be careful about selling yourself too short on this because I've talked to a lot of different people who want to wind up promoting what it is that their companies do, and people come from all kinds of different places, and some of the less likely to be successful—in many cases, I turn the business down—are, “Well, this is our first real experience with marketing.” And the reason for that is people expect unrealistic things. I describe what I do as top-of-funnel where we get people's attention and we give them a glimpse and a hook of what it is the product does. And I do that by talking about the painful problem that the product solves. So, when people hear their pain reflected in what we talk about, then that gives them the little bit of a push to go and take a look and see if this solves it.And that's great, but there has to be a process on the other side, where oh, a prospect comes in and starts looking at what it is we do. Do we have a sales funnel that moves them from someone just idly browsing to someone who might sign up for a trial, or try this in their own time, or start to understand how the community views it and the rest because just dropping a bunch of traffic on someone's website doesn't, in isolation, achieve anything without a means to convert that traffic into something that's a bit more meaningful and material to the business? I've talked to other folks who are big on oh, well, we want to wind up just instrument in the living crap out of everything we put out there, so I want to know, when someone clicks on the ad, who they are, what they do for a living, what their signing authority is, et cetera, et cetera, et cetera. And my answer, that's super easy, “Cool. We don't do any of that.”Part of the reason that people like hearing from me, is because I generally tend to respect their time, I'm not supporting invasive tracking of what they do, they don't see my dumb face smiling with a open mouth grin as they travel across the internet on every property. Although one of these days I will see myself on the side of a bus; I'm just waiting for it. And it's really nice to be able to talk to people who get the nuances and the peculiarities of the audience that I tend to speak to the most. You've always had that unlocked, even since our first conversation.Anadelia: Yeah, well, first of all, thank you. And yeah, the reality is that, especially within my world, right—and demand generation, we are very metrics-driven because our goal [tends 00:13:00] to be pipeline, right? Pipeline for the sales team, so we want to generate sales opportunities, and in order to do that, we need to be able to measure what's working and what is not working. But the reality is that good marketing is all about building trust, right? So, that's why I stress the importance of providing something of value to your prospect so that you're not wasting their time, right? The message that you have for them is something that can help them in the future.And if building trust sometimes means I'm not able to measure the direct results of the activity that you're doing, then that is okay, right? Because when you're driving people to your website, there are things that you can measure, like, you have some web visits, and you know that percentage of those visitors might be interested in continue further, right? So, when you look at the journey across the buyer stages, you have to have a compelling offer for a person on each of the possible stages, right? So, if they are just learning about you today because this is the first time that heard your ad, it's probably not expected that they would immediately go to your website and fill out your form, right? They've just heard about you, and now you start building that recognition.Now, if all the stars align, and I actually have a need for a solution that's like yours today, then, of course, you can expect a conversion to happen in that time point. But the reality is that having offers that are aimed at every stage of the buyer's journey is important.Corey: I'm glad to hear you say this. And the reason is that I often feel like when I say it, it sounds incredibly self-serving. But if you imagine the ideal buyer and their journey, they have the exact problem that your product does and there's an ad on my podcast that mentions it. Well, I imagine—and maybe this isn't accurate, but it's how I engage with podcasts myself—I'm probably not sitting in front of a computer ready to type in whatever it is that gets talked about.I'm probably doing dishes or outside harassing a dog or something. And if it resonates is, “Oh, I should look into that.” In an ideal world. I'll remember the short URL that I can go to, but in practice, I might just Google the company name. And oh, this does solve the problem.If it's not just me and there's a team I have to have a buy-in on, I might very well mention it in our next group meeting. And, “Okay, we're going to go ahead and try it out with an open-source version or whatnot.” And, “Oh, this seems to be working. We'll have procurement reach out and see what it takes to wind up generating a longer-term deal.” And the original attribution of the engineer who heard it on a podcast, or the DevOps director who read it in my newsletter, or whatever it is, is long since lost. I've commiserated with marketing people over this, and the adage that I picked up that I love quoting is half your marketing budget is wasted, but you can spend an entire career trying to figure out which half and get nowhere by the end of it.Anadelia: And this sort of touches on the buyer's journey is not linear. On the other side of that ad, or that marketing offer is a human, right? So, of course, as marketers, we're going to try to build this path of once you landed on our website, we want to guide you through all the steps until you do the thing that we want you to do, but the reality is, that does not happen in your example, right? You see something, you come back to it later through another channel, there's no way for us to measure those. And that's okay because that's just the reality of how humans behave.And also, I think it's worth noting that it takes multiple touch points until a person is ready to even hear what you have to say, right? And it sort of goes back to that point of building trust, right? It takes many times until you've gained that person's trust enough for them to listen to what you have to say.Corey: Building trust is important.Anadelia: SIt is very important. And that's why I think that running brand awareness programs are an extremely important part of a marketing mix. And sometimes there's not going to be any direct attribution, and we just have to be okay with it.Corey: I come bearing ill tidings. Developers are responsible for more than ever these days. Not just the code that they write, but also the containers and the cloud infrastructure that their apps run on. Because serverless means it's still somebody's problem. And a big part of that responsibility is app security from code to cloud. And that's where our friend Snyk comes in. Snyk is a frictionless security platform that meets developers where they are - Finding and fixing vulnerabilities right from the CLI, IDEs, Repos, and Pipelines. Snyk integrates seamlessly with AWS offerings like code pipeline, EKS, ECR, and more! As well as things you're actually likely to be using. Deploy on AWS, secure with Snyk. Learn more at Snyk.co/scream That's S-N-Y-K.co/screamCorey: I tend to take a perspective that trust is paramount, on some level, where we have our standard rules of, you know, don't break the law, et cetera, et cetera, that we do require our sponsors to conform to, but there are really two rules that I have that I care about. The first is you're not allowed to lie to the audience. Because if I wind up saying something is true in an ad or whatnot, and it's not, that damages my credibility. And I take this old world approach of, well, I believe trust is built over time, and you continually demonstrate a pattern of doing the right thing, and people eventually are willing to extend a little bit of credulousness when you say something that sounds that might be a little bit beyond their experience.The other is, and this is very nebulous, and difficult to define so I don't think we even have this in writing, but you have to be able to convince me if you're going to advertise something in one of my shows, that it will not, when used as directed, leave the user worse off than they were when they started. And that is a very strange thing. Like, a security product that has a bunch of typos on its page and is rolling its own crypto, for example—if you want an easy example—is one of those things that I will very gracefully decline not to wind up engaging with, just because I have the sneaking suspicion that if you trust that thing, you might very well live to regret it. In other cases, though—and this is almost never a problem because most companies that you have heard of and have established themselves as brands in this space already instinctively get that you're not able to build a lasting business by lying to people and then ripping them off.So, it's a relatively straightforward approach, but every once in a while, I see something that makes me raise an eyebrow. And it's not always bad. Sometimes I think that's a little odd. Teleport is a good example of this because, “Oh, really? You wound up doing access and authentication? That sounds exactly like the kind of thing I want something old and boring, not new and exciting, around, so let's dig into this and figure out whether this might be the one company you work at that doesn't get to sponsor stuff that I do.”But of course you do. You're absolutely focusing on an area that is relevant, useful, and having talked to people on your side of the world, you're doing the right thing. And okay, I would absolutely not be opposed to deploying this in the right production environment. But having that credulousness, having that exploratory conversation, makes it clear that I'm talking to people who know what they're doing and not effectively shilling for the highest bidder, which is not really a position I ever want to find myself in.Anadelia: And look, you have only one opportunity to make a first impression, right? So, being clear about what it is that you can do, and also being clear about what it is that you cannot do is extremely important, right? It kind of goes back to the point of just be a good human, don't waste people's time. You want to provide something of value to your audience. And so, setting those expectations early on is extremely important.And I don't know anyone that does this, but if your goal is only to drive people to your website, you can do that, probably very easily, but nothing will come out of it unless you have the right message.Corey: Oh, all you do is write something incendiary and offensive, and you'll have a lot of traffic. They won't buy anything and they'll hate you, but you'll get traffic, so maybe you want to be a little bit more intentional. It's the same reason that the companies that advertise on what I do pick me to advertise with as opposed to other things. It is more expensive than the mass-market podcasts and whatnot that speak to everyone. But you take a look at those podcasts and the things that they're advertising are things that actually apply to an awful lot more people, things like mattresses, and click-and-design website services, and the baseline stuff that a lot of people would be interested in, whereas the things that advertise on what I do tend to look a lot more like B2B SaaS companies where they're talking to folks who spend a lot of time working in cloud computing.And one of the weird things to think about from that perspective, at least for me, is if one person is listening to a show that I'm putting out and they go through the journey and become a customer, well, at the size of some of these B2B contracts between large companies, that one customer has basically paid for everything I can sell for advertising for the next decade and change, just because the long-term value of some of these customers is enormous. But it's why, for example—and I kept expecting it to happen, but it didn't—I've never been subjected to outreach from the mattress companies of, “Hey, you want to go talk about that to your guests?” No, because for those folks, it is pure raw numbers: how many millions of subscribers do you have? Here, it's—the newsletter is the easy one to get numbers on because lies, damned lies, and podcast statistics. I have 31,000 people that receive emails. Great, that's not the biggest newsletter in the world by a longshot, but the people who are the type of person to sign up for cloud computing-style newsletters, that alone says something very specific about them and it doesn't require anyone do anything creepy to wind up reaching out from that perspective.It doesn't require spying on customers to intuit that, hmm, maybe people who care about what AWS is up to and have big AWS-sized problems might sign up to a newsletter called Last Week in AWS. That's the sort of easy thinking about advertising that I tend to go for, which yeah, admittedly sounds a lot like something out of that Mad Men era. But I think that we got a lot right back then, and everything's new all the time.Anadelia: [laugh]. And actually, that's exactly what demand generation is, right? We want to find the right channels to reach our audience. And so, for a consumer company that sells mattresses, right, anyone might be on the market for a mattress, right? You want to go as broad as possible. But for something that's more specific, you want to find what are the right channels to reach that audience where you know that there's—it might be a smaller audience size, but it's the right people.And we've talked about the other core areas of marketing. So, with demand generation, it's all about finding people where they are, right, and providing them their message to you and attracting them to come to you, right? It kind of goes back to that inbound and outbound motion that I mentioned earlier. But at the end of the day also, if you don't have the right messaging to keep them engaged, once you got them to your website, then that's a different problem, right? So, demand gen alone cannot be successful without really strong product marketing and without really strong content, and everything else that's needed to support that, right? I mentioned the—if your website is not loading fast enough, then you're losing people if your form is not working. So, there's so many, so many different factors that come into play.Corey: Oh, God, the forms. Don't get me started on the forms. Hey, we have a great report that's super useful. Okay, cool. I'll click the link and I'll follow that. I talk to sponsors about this all the time. And it's, you have 30 mandatory fields on that website that I need to fill out. I am never going to do that.What is the absolute bare minimum that you need in an ideal world? Don't put any sort of gateway in front of it and just make it that good that I will reach out to thank you for it or something, but just make it an email address or something and that's it. You don't need to know the size of my company, the industry we're in, the level of my signing authority, et cetera, et cetera, et cetera. Because if this is good, I might very well be in touch. And if it's not, all you're going to do is harass me forever with pointless calls and emails and whatnot, and I don't want to deal with that. There's something to be said for adding value early in the conversation and letting other people sometimes make the first move. But this is also, to be clear, a very inbound type of approach.Anadelia: It's a never-ending debate, to gate or not to gate. And I don't know if there is a right answer. My approach is that if your content is good, people will come back to you. They'll keep coming back, and they'll want to take the next step with you. And so, I have some gated assets, and I have some that are not, and—but—Corey: But your gates have also never been annoying of the type that I'm talking about where it's the, “Oh, great. You need to, like, put in, like, how big is your company? What's the budget?” It feels like I'm answering a survey at some point. AWS is notorious for this.I counted once; there are 19 mandatory fields I had to fill out in order to watch a webinar that AWS was putting on.Anadelia: [laugh].Corey: And the worst part is they asked me the same questions every time I want to watch a different webinar. It's like, for a company that says the data is so valuable, you'd really think they'd be better at managing it.Anadelia: You know, like, some of the questions keep getting stranger. Like, I would not be surprised if people start asking what's your favorite color, or what's the answer to your—Corey: The one they always ask now for, like, big data seminars and whatnot, is where this really gets me, is this in relation to your professional interests or your personal interests? It's… “What do you think my hobbies are over there? Oh, yeah, I like big enterprise software. That's my hobby.” “Okay, I guess.” But I really do wonder what happens if someone checks the personal interest [vibe 00:25:33]. Do they wind up just with various AWS employees showing up want to hang out on the weekends and go surfing or something? I don't know.Anadelia: As somebody who has been on the receiving end of lists like this—for example, we sponsor a conference and we get people stop by to talk to us, and now we get the list of those people. And there's 25 columns. Like, honestly, that data does not come in helpful because at the end of the day, whatever you've marked on the required question is not going to change how I am going to communicate to you after, right, because we just had a conversation in person at this event.Corey: My budget is not material to the reason I let you scan my badge. The reason I let you scan my badge because I really wanted one of those fun plastic toy things, so I waited in line for 45 minutes to get it. But that doesn't mean that I'm going to be a buyer; it just means that now I'm in your funnel, although I could not possibly care less about what you do. One thing I do at re:Invent and a couple other conferences, for example, is I will have swag at a booth—because I don't tend to get booths myself, I don't have the staff to man it and I'm bad at that type of thing. But when people come up to get a sticker for Last Week in AWS or when of our data transfer diagram things or whatnot, the rule that we've always put in place is, you're not going to mandate a badge scan for that.And the kind of company I like doing that with gets it because the people who walk by and are interested will say, “Hey, can you scan my badge as well?” But they don't want to pollute their own lead lists with a bunch of people who are only there to get a sticker featuring a sarcastic platypus, as opposed to getting them confused with people actually care about what it is that they're solving for. And that's a delicate balance to strike sometimes, but the nice thing about being me is I have customers who come back again and again and again. Although I will argue that I probably got better at being a service provider when I started also being a customer at the same time, where I hired out a marketing department here because it turns out that fixing the AWS bill is something that does a fair bit of marketing work. It's not something people talk about at large scale in public, so you have to be noisy enough so that inbound finds its path to you a bunch of times. That's always tricky.And learning about how no matter what it is you do, in the case of my consulting work, we are quite honestly selling money, bring us in for an engagement, you will turn a profit on that engagement and we don't come back with a whole bunch of extra add-ons after the fact to basically claw back more things. It's one of the easiest sales in the world. And it's still nuanced, and challenging, and finding the right way to talk about it to the right people at the right time explains why marketing is the industry that it is. It's hard. None of this is easy.Anadelia: It is. And you know, in your example, you're not scanning that badge, but giving the person the sticker, right? Like, it's all about making a good first impression, and if the person's not ready to talk to you, that is okay. But there are ways that you can stay top-of-mind so that the moment that they have a need, they'll come to you. It kind of goes back again to my earlier points of adding value in supporting existing communities, right? So, what are you doing to stay top-of-mind with that person that wasn't quite ready back then, but the moment they have a need, they'll think of you first because you made a good first impression.Corey: And that's really what it comes down to. It's nice to talk to people who actually work in marketing because a lot of what I do in the marketing space, I've got to be honest, is terrible. Because I've done the old engineering thing of, well, I'm no marketer, but I know how to write code, so how hard could marketing really be and I invent this theory of marketing from first principles, which not only is mostly wrong, but also has a way of being incredibly insulting to people who have actually made this their profession and excel at it. But it's an evolutionary process and trying to figure out the right way to do things and how to think about things from particular point of view has been transformative. Really easy example of this: when I first started selling sponsorships, I was constantly worried that a sponsor was going to reach out and say, “Well, hang on a second. We didn't get the number of clicks that we expected to on this campaign. What do you have to say about that?”Because I'm a consultant. I am used to clients not getting results that they expected having some harsh words for me. In practice, I don't believe I've ever had a deep conversation about that with a marketing person. I've talked to them and they've said, “Well, some of these things worked. Some of these things didn't. Here's what works; here's what didn't, and for our next round, here's what we want to try instead.” Those are the great constructive conversations.The ones that I was fearing somehow would assume that I held this iron grip of control over exactly how many people would be clicking on a thing in a newsletter, and I'm not. We barely provide click-tracking at this point in the aggregate, let alone anything more specific, just because it's so hard to actually tell and get value out of it. You talk as well, about there being brand awareness. Even if someone doesn't click an ad, they're potentially reading it, they're starting to associate your company with the problem space. That's one of those things that are effectively impossible to track, but it does pay dividends.When you suddenly have a problem in a particular area. And there's one or two companies off the top of your mind that you know work in that space. Well, what do you think marketing is? There has been huge money put into making that association in your mind. It's not just about click the link; it's not just about buy the thing; it's about shaping the way that we think about different things.Anadelia: And I spend a lot of time thinking about how people think we talk about what are the things that motivate you. When you have a problem, where do you go to look for a solution, or who do you go to, right? So, just understanding what the thought process is when someone is trying to solve a problem or making a purchasing decision, I think that a lot of demand generation is what are the different ways by which someone is trying to solve a problem that they're having? And I had an interest in psychology growing up; both my parents are psychologists, and I think that marketing tends to bring some aspects of that in business and creativity, which is what led me to a career in marketing.And you ended up being sort of a connector, right? Like your job was to connect to people who would benefit from meeting each other. Just one of them happens to be a product, or you know, it depends on your company, right, but you're just introducing people and making sure they know about each other because there's going to be a mutually beneficial relationship between them.Corey: That seems to be what so many jobs ultimately distilled down to in the final analysis of things. I really want to thank you for being so generous with your time and talking about how you view the world slash industry in which we live. If people want to learn more about what you're up to and how you think about these things, where's the best place to find you?Anadelia: You can follow me on Twitter at @anadeliafadeev, or connect with me on LinkedIn.Corey: Oh, you're one of the LinkedIn peoples. I used to do that a bit, and then I just started getting deluged with all kinds of nonsense, and let me adjust my notification settings, and there are 600 of them. And no, no, no, no, no. And I basically have quit the field, by and large, on LinkedIn. But power to you for not having done that. Links to that will of course be in the [show notes 00:32:38]. Thank you so much for being so generous with your time.Anadelia: Thank you for having me. I appreciate it.Corey: Anadelia Fadeev, Senior Director of Demand Generation at Teleport. I'm Cloud Economist Corey Quinn and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry ranting comment about how we got it completely wrong and that marketing does not work on you in the least. And by the way, when you close out that ranting comment, tell me what kind of brand of shoes you're wearing today.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

Brian Gilmore (@BrianMGilmore, Director IoT/Emerging Technology @InfluxDB) talks about Edge and Industrial Edge Computing, as well as application and data challenges at the edge.SHOW: 634CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:CloudZero - Cloud Cost Intelligence for Engineering TeamsStreamline on-call, collaboration, incident management, and automation with a free 30-day trial of Lightstep Incident Response, built on ServiceNow. Listeners of The Cloudcast will also receive a free Lightstep Incident Response T-shirt after firing an alert or incident.Pay for the services you use, not the number of people on your team with Lightstep Incident Response. Try free for 30 days. Fire an alert or incident today and receive a free Lightstep Incident Response t-shirt.Datadog Application Monitoring: Modern Application Performance MonitoringGet started monitoring service dependencies to eliminate latency and errors and enhance your users app experience with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.SHOW NOTES:InfluxData (homepage) - InfluxDB - Time Series PlatformUnderstanding Time Series Database Platforms (Cloudcast Eps:394)Topic 1 - Welcome to the show. Before we get into the fascinating world of Edge and IoT, tell us a little bit about your background, and then where you focus these days with InfluxData.Topic 2 - It's been a little while since we covered IoT and IIoT. In the past it was somewhat of a fragmented market segment (lots of definitions, lots of different use-cases). How do you summarize the IoT and IIoT markets in 2022? Topic 3 - We've always said that the sensor part of IoT isn't very interesting, but what a company does with the data is very interesting (and complicated). How do companies think about edge data these days – what aspects of the data are valuable? Topic 4 - Time Series databases seem like the perfect fit for IoT and IIoT use-cases because they are designed to be both real-time and give historical context (from a time perspective). Is this the case, and why do companies ever consider other types of databases at the edge?Topic 5 - What are the current best practices about managing data at the edge, in terms of long-term retention and what they eventually do with the data (analysis, analytics, etc.) to better optimize those edge applications? Topic 6 - What are some of the emerging trends you're starting to see happen at the edge, that maybe weren't on the industry radar a few years ago? FEEDBACK?Email: show at the cloudcast dot netTwitter: @thecloudcastnet

In this episode, Ryan and Bhavin interview Rick Spencer, VP of Products at InfluxData, previously the VP of Platforms for InfluxData. The discussion focuses on InfluxData, creator of InfluxDB, and how they help customers looking for a Time-Series database solution. Rick talks about the interesting IoT and Edge computing use cases, and how getting that real-time sensor information can be transformational for customers. In the second half of the discussion, we focus on how InfluxDB cloud runs across three major cloud providers, running on top of Kubernetes itself. Rick focuses on their Kubernetes adoption journey and talks about their architecture today. We also talk about how users can leverage InfluxDB for monitoring their large-scale Kubernetes deployments too! Show Links: Datastax raises a private equity round of $115M valuring the company at $1.6B to focus more on Astra DB and Astra streaming - https://techcrunch.com/2022/06/15/datastax-proves-its-still-possible-to-raise-nine-figures-at-higher-valuation-in-2022/ Platform9 raises $26M bringing the total money raised across all the rounds to $100M - https://techcrunch.com/2022/06/14/platform9-raises-26m-to-help-manage-distributed-cloud-clusters/ Finout raised $14M Series A funding to help organizations break down the cost of each Kubernetes namespace, each folder in the S3 bucket, each Snowflake Query, etc. - https://www.geektime.com/finout-wants-to-reduce-your-cloud-costs-with-a-mega-bill-and-14m-in-a-round-funding/ Mercedez Benz runs 900 K8s clusters - https://www.infoworld.com/article/3664052/why-mercedes-benz-runs-on-900-kubernetes-clusters.html Weave Policy Library for HIPAA compliance - https://www.weave.works/blog/weave-policy-library-introducing-hipaa-policies Kanister Webinar - https://community.cncf.io/events/details/cncf-cncf-online-programs-presents-cncf-on-demand-webinar-kanister-application-level-data-protection-on-kubernetes Cloud-native storage - Kubernetes Podcast - https://kubernetespodcast.com/episode/182-cloud-native-storage/ 2021 K8s Annual Report - https://www.cncf.io/reports/kubernetes-annual-report-2021/ Enhancements#3337: KEP-3333 Retroactive default StorageClass assignment

This week's show kicks off with another look at Ring's potential to become a surveillance tool, this time prompted by a letter from Senator Ed Markey who wants Amazon to answer some questions. We then talk about a new capability for InfluxData's time series database and explain why it matters before encouraging everyone who listens … Continue reading Episode 376: Senator calls out video doorbells … again The post Episode 376: Senator calls out video doorbells … again appeared first on IoT Podcast - Internet of Things.

The solution many turn to for capturing their streaming data is InfluxDB.  In this episode, I interview Brian Gilmore, Director of Product Management at InfluxData, about how real time applications achieve success built on top of InfluxDB. When most people hear the phrase Internet of Things, it typically evokes an image of connected devices we The post Time Series IoT on InfluxDB with Brian Gilmore appeared first on Software Engineering Daily.

The solution many turn to for capturing their streaming data is InfluxDB.  In this episode, I interview Brian Gilmore, Director of Product Management at InfluxData, about how real time applications achieve success built on top of InfluxDB. When most people hear the phrase Internet of Things, it typically evokes an image of connected devices we The post Time Series IoT on InfluxDB with Brian Gilmore appeared first on Software Engineering Daily.

InfluxDB is an open-source time-series database.  It's maintained by InfuxData who offers a suite of products that help organizations gain insights from time-series data.  In this episode, I interview Zoe Steinkamp, Software Engineering and Developer Advocate at InfluxData.  We explore some of the common use cases for time-series databases such as IoT and some recent

InfluxDB is an open-source time-series database.  It's maintained by InfuxData who offers a suite of products that help organizations gain insights from time-series data.  In this episode, I interview Zoe Steinkamp, Software Engineering and Developer Advocate at InfluxData.  We explore some of the common use cases for time-series databases such as IoT and some recent The post InfluxData with Zoe Steinkamp appeared first on Software Engineering Daily.

InfluxDB is an open-source time-series database.  It's maintained by InfuxData who offers a suite of products that help organizations gain insights from time-series data.  In this episode, I interview Zoe Steinkamp, Software Engineering and Developer Advocate at InfluxData.  We explore some of the common use cases for time-series databases such as IoT and some recent The post InfluxData with Zoe Steinkamp appeared first on Software Engineering Daily.

In episode 19 of The Kubelist Podcast, Marc Campbell speaks with Rick Spencer about InfluxData, developer of InfluxDB. Rick unpacks his career journey and explains how InfluxData uses Kubernetes and other CNCF projects from an end-user perspective.

In episode 19 of The Kubelist Podcast, Marc Campbell speaks with Rick Spencer about InfluxData, developer of InfluxDB. Rick unpacks his career journey and explains how InfluxData uses Kubernetes and other CNCF projects from an end-user perspective.

Anadelia Fadeev, Director of Demand Generation and Growth at Teleport, discusses lead gen and brand awareness, how she measures effectiveness of campaigns, and "must have" online tools.Anadelia Fadeev's BioAnadelia is a Director of Demand Generation and Growth at Teleport, a Kleiner Perkins-backed software company that allows engineers and security professionals to unify access to Servers, web applications, and databases.Prior to Teleport, Anadelia was Demand generation at several tech startups, including LightStep, InfluxData, ToutApp (acq. by Marketo), and Inkling. She started her career at Visage Mobile where she oversaw all aspects of marketing.Time Stamps00:10 Anadelia and Teleport 3:13 Brand Awareness6:50 Lead Generation8:00 Measuring effectiveness of campaigns10:02 Anadelia's Tech Stack11:20 Case Study14:00 Bowtie Funnel16:00 Looking for leadsSIGN UP at https://www.saashimi.cloud to receive transcripts of the interviews and news about upcoming guests and events.

Todd Persen, Co-founder & CEO, Era Software (prev. Co-founder & CTO, InfluxData) In this episode, we'll dig into the InfluxData founding story as well as Todd's decision to make his new company, EraDB, closed source. We'll also discuss the metrics to determine if an open-source project is a success, what features users will pay for, and the benefits (and drawbacks) of having an open-source component at a startup.

Molly Norris Walker is Head of Design & User Research at InfluxData. Today we're talking about how to smash your growth targets through design experimentation. A big part of Molly's role is scaling design experimentation for a better UX to support growth, which is something Molly calls Growth Design. Molly not only practices this on a day-to-day basis within the world of B2B SaaS but she is also author of Design-Driven Growth: Strategy & Case Studies For Product Shapers. In this episode, Molly discusses: - Why growth design is super important in B2B - The relationship between growth design and product-led growth - A 5-step framework for implementing growth design - How you can design growth loops into your SaaS business model - A growth design AB-Test challenge Links InfluxData >> https://www.influxdata.com/ Design-Driven Growth: https://www.design-driven-growth.com/ Design-Driven Growth: Strategy & Case Studies For Product Shapers >> https://www.amazon.com/UX-Design-Growth-optimize-conversion-ebook/dp/B07BYX1GY8 Lex Roman on Medium >> https://medium.com/@calexity GrowthDesigners.Co >> https://growthdesigners.co/ --- Advance B2B >> www.advanceb2b.com Follow The Growth Hub on Twitter >> twitter.com/SaaSGrowthHub Follow Edward on Twitter >> twitter.com/NordicEdward

Key Insights InfluxData - 600+ customers serving from 1-person startup to Fortune-50 companies Support Organization - non-tiered, roughly 12 people in US and UK. Very remote-friendly. Just started building customer success team. Case volume ~400 per month. How-to / Break-Fix case split 25 / 75 Support Tech - Used to be Zendesk; migrating to Salesforce ServiceCloud. GitHub open source for docs. Discourse for Community Forums [InfluxData being an open source company promotes use of open source products] Case split across channels - earlier >75% on email. Now shifting towards web. Knowledge Base - Separate KB doesn't exist instead knowledge is added to product documentation. Though this will likely change in future Cool Idea - “Crowd sourcing for support answers” — worked very well at MobileIron (used a vendor called Directly) What's broken in Support Tech Stack-- Integration between CRM, Case Management and Bug database is broken. One has to throw tools, consulting dollars to fix it! Focus for next 12 months - Build Customer Success Team Online Certification/Education - No standard tool that exists; a few open source tools though Metrics - Success : Customer Health (primary indicator product usage), Support: CSAT What would you do differently if you were to do this all over again - Focus on Customer Success deeply from the beginning; that way you understand deeply about customer and product-market fit. Books: Survival to Thrival: Building the Enterprise Startup - Book 1 The Company Journey Survival to Thrival: Building the Enterprise Startup - Book 2: Change or Be Changed Startupland: How Three Guys Risked Everything to Turn an Idea into a Global Business