Hello dear friend :) Today let's do some slow and gentle mirrored touch. It is one of my favorite ASMR techniques and I hope you enjoy it too! Originally I saw this trigger on River ASMR channel https://www.youtube.com/watch?v=JUDwDMCytbE&t=0s and I loved it! Here's a another mirrored touch video I did a few years back https://www.youtube.com/watch?v=ZnI7P-z_Aws&t=5s :) Thank you for being here ✨ #ASMR #GentleWhispering --- Send in a voice message: https://podcasters.spotify.com/pod/show/maria-gentlewhispering/message Support this podcast: https://podcasters.spotify.com/pod/show/maria-gentlewhispering/support
James Barlow is a highly accomplished tech and business leader and the Founder of Triumph Technology Solutions LLC, a leading AWS cloud-native services provider with over a decade of experience in the industry. As a skilled entrepreneur, James has a deep understanding of the development of IT Services and Software Businesses with domain expertise in AWS, Fintech, Healthcare, E-Commerce, and more. He has started numerous tech companies, including an eBay-based business, and was generating close to $1m in revenue from eBay sales monthly at the age of only 20 as a “power seller.” James is also a highly skilled DevOps Engineer with experience in various web development technologies. Prior to founding Triumph Technology Solutions, he worked at Jurisdesk Business Web Development as a Lead DevOps Engineer, helping companies develop their online presence and generate leads for their sales teams. With his commitment to staying current with emerging technologies, James has earned certification as an AWS Certified Cloud Practitioner and Solutions Architect. He is also a passionate volunteer and deeply committed to several causes, including civil rights and social action, economic empowerment, education, disaster and humanitarian relief, politics, and science and technology. --- Support this podcast: https://podcasters.spotify.com/pod/show/john-aidan-byrne0/support
The Dayhuff Group is a born-in-the-cloud service provider supporting their customers in accelerating the reinvention of their applications and data in the cloud. They excel in developing and deploying data lakes and analytics, ML/AI, automated attendants, and data modernization + development by leveraging AI technologies from IBM and AWS to drive measurable business results.
Giant Robots Smashing Into Other Giant Robots
Lauren Maffeo is the author of Designing Data Governance from the Ground Up. Victoria talks to Lauren about human-centered design work, data stewardship and governance, and writing a book anybody can use regardless of industry or team size. Designing Data Governance from the Ground Up (https://www.amazon.com/Designing-Data-Governance-Ground-Data-Driven/dp/1680509802) Follow Lauren Maffeo on LinkedIn (https://www.linkedin.com/in/laurenmaffeo/) or Twitter (https://twitter.com/LaurenMaffeo). Follow thoughtbot on Twitter (https://twitter.com/thoughtbot) or LinkedIn (https://www.linkedin.com/company/150727/). Become a Sponsor (https://thoughtbot.com/sponsorship) of Giant Robots! Transcript: VICTORIA: Hey there. It's your host Victoria. And I'm here today with Dawn Delatte and Jordyn Bonds from our Ignite team. We are thrilled to announce the summer 2023 session of our new incubator program. If you have a business idea that involves a web or mobile app, we encourage you to apply for our 8-week program. We'll help you validate the market opportunity, experiment with messaging and product ideas, and move forward with confidence towards an MVP. Learn more and apply at tbot.io/incubator. Dawn and Jordyn, thank you for joining and sharing the news with me today. JORDYN: Thanks for having us. DAWN: Yeah, glad to be here. VICTORIA: So, tell me a little bit more about the incubator program. This will be your second session, right? JORDYN: Indeed. We are just now wrapping up the first session. We had a really great 8 weeks, and we're excited to do it again. VICTORIA: Wonderful. And I think we're going to have the person from your program on a Giant Robots episode soon. JORDYN: Wonderful. VICTORIA: Maybe you can give us a little preview. What were some of your main takeaways from this first round? JORDYN: You know, as ever with early-stage work, it's about identifying your best early adopter market and user persona, and then learning as much as you possibly can about them to inform a roadmap to a product. VICTORIA: What made you decide to start this incubator program this year with thoughtbot? DAWN: We had been doing work with early-stage products and founders, as well as some innovation leads or research and development leads in existing organizations. We had been applying a lot of these processes, like the customer discovery process, Product Design Sprint process to validate new product ideas. And we've been doing that for a really long time. And we've also been noodling on this idea of exploring how we might offer value even sooner to clients that are maybe pre-software product idea. Like many of the initiatives at thoughtbot, it was a little bit experimental for us. We decided to sort of dig into better understanding that market, and seeing how the expertise that we had could be applied in the earlier stage. It's also been a great opportunity for our team to learn and grow. We had Jordyn join our team as Director of Product Strategy. Their experience with having worked at startups and being an early-stage startup founder has been so wonderful for our team to engage with and learn from. And we've been able to offer that value to clients as well. VICTORIA: I love that. So it's for people who have identified a problem, and they think they can come up with a software solution. But they're not quite at the point of being ready to actually build something yet. Is that right? DAWN: Yeah. We've always championed the idea of doing your due diligence around validating the right thing to build. And so that's been a part of the process at thoughtbot for a really long time. But it's always been sort of in the context of building your MVP. So this is going slightly earlier with that idea and saying, what's the next right step for this business? It's really about understanding if there is a market and product opportunity, and then moving into exploring what that opportunity looks like. And then validating that and doing that through user research, and talking to customers, and applying early product and business strategy thinking to the process. VICTORIA: Great. So that probably sets you up for really building the right thing, keeping your overall investment costs lower because you're not wasting time building the wrong thing. And setting you up for that due diligence when you go to investors to say, here's how well I vetted out my idea. Here's the rigor that I applied to building the MVP. JORDYN: Exactly. It's not just about convincing external stakeholders, so that's a key part. You know, maybe it's investors, maybe it's new team members you're looking to hire after the program. It could be anyone. But it's also about convincing yourself. Really, walking down the path of pursuing a startup is not a small undertaking. And we just want to make sure folks are starting with their best foot forward. You know, like Dawn said, let's build the right thing. Let's figure out what that thing is, and then we can think about how to build it right. That's a little quote from a book I really enjoy, by the way. I cannot take credit for that. [laughs] There's this really great book about early-stage validation called The Right It by Alberto Savoia. He was an engineer at Google, started a couple of startups himself, failed in some ways, failed to validate a market opportunity before marching off into building something. And the pain of that caused him to write this book about how to quickly and cheaply validate some market opportunity, market assumptions you might have when you're first starting out. The way he frames that is let's figure out if it's the right it before we build it right. And I just love that book, and I love that framing. You know, if you don't have a market for what you're building, or if they don't understand that they have the pain point you're solving for, it doesn't matter what you build. You got to do that first. And that's really what the focus of this incubator program is. It's that phase of work. Is there a there there? Is there something worth the hard, arduous path of building some software? Is there something there worth walking that path for before you start walking it? VICTORIA: Right. I love that. Well, thank you both so much for coming on and sharing a little bit more about the program. I'm super excited to see what comes out of the first round, and then who gets selected for the second round. So I'm happy to help promote. Any other final takeaways for our listeners today? DAWN: If this sounds intriguing to you, maybe you're at the stage where you're thinking about this process, I definitely encourage people to follow along. We're trying to share as much as we can about this process and this journey for us and our founders. So you can follow along on our blog, on LinkedIn. We're doing a LinkedIn live weekly with the founder in the program. We'll continue to do that with the next founders. And we're really trying to build a community and extend the community, you know, that thoughtbot has built with early-stage founders, so please join us. We'd love to have you. VICTORIA: Wonderful. That's amazing. Thank you both so much. INTRO MUSIC: VICTORIA: This is the Giant Robots Smashing Into Other Giant Robots Podcast, where we explore the design, development, and business of great products. I'm your host, Victoria Guido. And with me today is Lauren Maffeo, Author of Designing Data Governance from the Ground Up. Lauren, thank you for joining us. LAUREN: Thanks so much for having me, Victoria. I'm excited to be here. VICTORIA: Wonderful. I'm excited to dive right into this topic. But first, maybe just tell me what led you to start writing this book? LAUREN: I was first inspired to write this book by my clients, actually. I was working as a service designer at Steampunk, which is a human-centered design firm serving the federal government. I still do work for Steampunk. And a few years ago, I was working with a client who had a very large database containing millions of unique data points going back several centuries. And I realized throughout the course of my discovery process, which is a big part of human-centered design work, that most of their processes for managing the data in this database were purely manual. There was no DevSecOps integrated into their workflows. These workflows often included several people and took up to a week to complete. And this was an organization that had many data points, as mentioned, in its purview. They also had a large team to manage the data in various ways. But they still really struggled with an overall lack of processes. And really, more importantly, they lacked quality standards for data, which they could then automate throughout their production processes. I realized that even when organizations exist to have data in their purview and to share it with their users, that doesn't necessarily mean that they actually have governance principles that they abide by. And so that led me to really consider, more broadly, the bigger challenges that we see with technology like AI, machine learning, large language models. We know now that there is a big risk of bias within these technologies themselves due to the data. And when I dug deeper, first as a research analyst at Gartner and then as a service designer at Steampunk, I realized that the big challenge that makes this a reality is lack of governance. It's not having the quality standards for deciding how data is fit for use. It's not categorizing your data according to the top domains in your organization that produce data. It's lack of clear ownership regarding who owns which data sets and who is able to make decisions about data. It's not having things like a data destruction policy, which shows people how long you hold on to data for. So that knowledge and seeing firsthand how many organizations struggle with that lack of governance that's what inspired me to write the book itself. And I wanted to write it from the lens of a service designer. I have my own bias towards that, given that I am a practicing service designer. But I do believe that data governance when approached through a design thinking lens, can yield stronger results than if it is that top-down IT approach that many organizations use today unsuccessfully. VICTORIA: So let me play that back a little bit. So, in your experience, organizations that struggle to make the most out of their data have an issue with defining the authority and who has that authority to make decisions, and you refer to that as governance. So that when it comes down to it, if you're building things and you want to say, is this ethical? Is this right? Is this secure? Is it private enough? Someone needs to be responsible [laughs] for answering that. And I love that you're bringing this human-centered design approach into it. LAUREN: Yeah, that's exactly right. And I would say that ownership is a big part of data governance. It is one of the most crucial parts. I have a chapter in my book on data stewards, what they are, the roles they play, and how to select them and get them on board with your data governance vision. The main thing I want to emphasize about data stewardship is that it is not just the technical members of your team. Data scientists, data architects, and engineers can all be exceptional data stewards, especially because they work with the data day in and day out. The challenge I see is that these people typically are not very close to the data, and so they don't have that context for what different data points mean. They might not know offhand what the definitions per data piece are. They might not know the format that the data originates in. That's information that people in non-technical roles tend to possess. And so, data stewardship and governance is not about turning your sales director into a data engineer or having them build ETL pipelines. But it is about having the people who know that data best be in positions where they're able to make decisions about it, to define it, to decide which pieces of metadata are attached to each piece of data. And then those standards are what get automated throughout the DevSecOps process to make better life cycles that produce better-quality data faster, at speed with fewer resources. VICTORIA: So, when we talk about authority, what we really mean is, like, who has enough context to make smart decisions? LAUREN: Who has enough context and also enough expertise? I think a big mistake that we as an industry have made with data management is that we have given the responsibility for all data in an organization to one team, sometimes one person. So, typically, what we've done in the past is we've seen all data in an organization managed by IT. They, as a department, make top-down decisions about who has access to which data, what data definitions exist, where the data catalog lives, if it exists in an organization at all. And that creates a lot of blockers for people if you always have to go through one team or person to get permission to use data. And then, on top of that, the IT team doesn't have the context that your subject matter experts do about the data in their respective divisions. And so it really is about expanding the idea of who owns data and who is in a position of authority to make decisions about it by collaborating across silos. This is very challenging work to do. But I would actually say that for smaller organizations, they might lack the resources in, time, and money, and people to do data governance at scale. But what they can do is start embedding data governance as a core principle into the fabric of their organizations. And ultimately, I think that will power them for success in a way that larger organizations were not able to because there is a lot of technical debt out there when it comes to bad data. And one way to avoid that in the future or to at least mitigate it is to establish data governance standards early on. VICTORIA: Talk me through what your approach would be if you were working with an organization who wants to build-in this into the fabric of how they work. What would be your first steps in engaging with them and identifying where they have needs in part of that discovery process? LAUREN: In human-centered design, the discovery process occurs very early in a project. This is where you are working hand in hand with your client to figure out what their core needs are and how you can help them solve those core needs. And this is important to do because it's not always obvious what those needs are. You might get a contract to work on something very specific, whether it's designing the user interface of a database or it's migrating a website. Those are technical challenges to solve. And those are typically the reason why you get contracted to work with your client. But you still have to do quite a bit of work to figure out what the real ask is there and what is causing the need for them to have hired you in the first place. And so, the first thing I would do if I was walking a client through this is I would start by asking who the most technical senior lead in the organization is. And I would ask how they are managing data today. I think it's really important, to be honest about the state of data in your organization today. The work that we do designing data governance is very forward-thinking in a lot of ways, but you need a foundation to build upon. And I think people need to be honest about the state of that foundation in their organization. So the first thing I would do is find that most-senior data leader who is responsible for making decisions about data and owns the data strategy because that person is tasked with figuring out how to use data in a way that is going to benefit the business writ large. And so, data governance is a big part of what they are tasked to do. And so, in the first instance, what I would do is I would host a workshop with the client where I would ask them to do a few things. They would start by answering two questions: What is my company's mission statement, and how do we use data to fulfill that mission statement? These are very baseline questions. And the first one is so obvious and simple that it might be a little bit off-putting because you're tempted to think, as a senior leader, I already know what my company does. Why do I need to answer it like this? And you need to answer it like this because just like we often get contracts to work on particular technical problems, you'd be surprised by how many senior leaders cannot articulate their company's mission statements. They'll talk to you about their jobs, the tools they use to do their jobs, who they work with on a daily basis. But they still aren't ultimately answering the question of how their job, how the technology they use fulfills a bigger organizational need. And so, without understanding what that organizational need is, you won't be able to articulate how data fulfills that mission. And if you're not able to explain how data fulfills your company's mission, I doubt you can explain which servers your data lives on, which file format it needs to be converted to, who owns which data sets, where they originate, what your DevSecOps processes are. So answering those two questions about the company mission and how data is used to fulfill that mission is the first step. The second thing I would do is ask this senior leader, let's say the chief data officer, to define the data domains within their organization. And when we talk about data domains, we are talking about the areas of the business that are the key areas of interest. This can also be the problem spaces that your organization addresses. It also can have a hand in how your organization is designed as is; in other words, who reports to whom? Do you have sales and marketing within one part of the organization, or are they separate? Do you have customer success as its own wing of the organization separate from product? However your organization is architected, you can draw lines between those different teams, departments, and the domains that your organization works in. And then, most importantly, you want to be looking at who leads each domain and has oversight over the data in that domain. This is a really important aspect of the work because, as mentioned, stewards play a really key role in upholding and executing data governance. You need data stewards across non-technical and technical roles. So defining not just what the data domains are but who leads each domain in a senior role is really important to mapping out who your data stewards will be and to architect your first data governance council. And then, finally, the last thing I would have them do in the first instance is map out a business capability map showing not only what their data domains are but then the sub-domains underneath. So, for example, you have sales, and that can be a business capability. But then, within the sales data domain, you're going to have very different types of sales data. You're going to have quarterly sales, bi-annual sales, inbound leads versus outbound leads. You're going to have very different types of data within that sales data domain. And you want to build those out as much as you possibly can across all of your data domains. If you are a small organization, it's common to have about four to six data domains with subdomains underneath, each of those four to six. But it varies according to each startup and organization and how they are structured. Regardless of how your organization is structured, there's always value in doing those three things. So you start by identifying what your organization does and how data fulfills that goal. You define the core data domains in your organization, including who owns each domain. And then, you take that information about data domains, and you create a capability map showing not just your core data domains but the subdomains underneath because you're going to use all of that information to architect a future data governance program based on what you currently have today. VICTORIA: I think that's a great approach, and it makes a lot of sense. Is that kind of, like, the minimum that people should be doing for a data governance program? Like, what's the essentials to do, like, maybe even your due diligence, say, as a health tech startup company? LAUREN: This is the bare minimum of what I think every organization should do. The specifics of that are different depending on industry, depending on company size, organizational structure. But I wrote this book to be a compass that any organization can use. There's a lot of nuance, especially when we get into the production environment an organization has. There's a lot of nuance there depending on tools, all of that. And so I wanted to write a book that anybody could use regardless of industry size, team size, all of that information. I would say that those are the essential first steps. And I do think that is part of the discovery process is figuring out where you stand today, and no matter how ugly it might be. Because, like we've mentioned, there is more data produced on a daily basis than ever before. And you are not going into this data governance work with a clean slate. You already have work in your organization that you do to manage data. And you really need to know where there are gaps so that you can address those gaps. And so, when we go into the production environment and thinking about what you need to do to be managing data for quality on a regular basis, there are a couple of key things. The first is that you need a plan for how you're going to govern data throughout each lifecycle. So you are very likely not using a piece of data once and never again. You are likely using it through several projects. So you always want to have a plan for governance in production that includes policies on data usage, data archiving, and data destruction. Because you want to make sure that you are fulfilling those principles, whatever they are, throughout each lifecycle because you are managing data as a product. And that brings me to the next thing that I would encourage people working in data governance to consider, which is taking the data mesh principle of managing data as a product. And this is a fundamental mind shift from how big data has been managed in the past, where it was more of a service. There are many detriments to that, given the volume of data that exists today and given how much data environments have changed. So, when we think about data mesh, we're really thinking about four key principles. The first is that you want to manage your data according to specific domains. So you want to be creating a cloud environment that really accounts for the nuance of each data domain. That's why it's so important to define what those data domains are. You're going to not just document what those domains are. You're going to be managing and owning data in a domain-specific way. The second thing is managing data as a product. And so, rather than taking the data as a service approach, you have data stewards who manage their respective data as products within the cloud environment. And so then, for instance, rather than using data about customer interactions in a single business context, you can instead use that data in a range of ways across the organization, and other colleagues can use that data as well. You also want to have data available as a self-service infrastructure. This is really important in data mesh. Because it emphasizes keeping all data on a centralized platform that manages your storage, streaming, pipelines, and anything else, and this is crucial because it prevents data from leaving in disparate systems on various servers. And it also erases or eases the need to build integrations between those different systems and databases. And it also gives each data steward a way to manage their domain data from the same source. And then the last principle for data mesh is ecosystem governance. And really, what we're talking about here is reinforcing the data framework and mission statement that you are using to guide all of your work. It's very common in tech for tech startups to operate according to a bigger vision and according to principles that really establish the rationale for why that startup deserves to exist in the world. And likewise, you want to be doing all of your production work with data according to a bigger framework and mission that you've already shared. And you want to make sure that all of your data is formatted, standardized, and discoverable against equal standards that govern the quality of your data. VICTORIA: That sounds like data is your biggest value as a company and your greatest source of liability [laughs] and in many ways. And, I'm curious, you mentioned just data as a product, if you can talk more about how that fits into how company owners and founders should be thinking about data and the company they're building. LAUREN: So that's a very astute comment about data as a liability. That is absolutely true. And that is one of the reasons why governance is not just nice to have. It's really essential, especially in this day and age. The U.S. has been quite lax when it comes to data privacy and protection standards for U.S. citizens. But I do think that that will change over the next several years. I think U.S. citizens will get more data protections. And that means that organizations are going to have to be more astute about tracking their data and making sure that they are using it in appropriate ways. So, when we're talking to founders who want to consider how to govern data as a product, you're thinking about data stewards taking on the role of product managers and using data in ways that benefits not just them and their respective domains but also giving it context and making it available to the wider business in a way that it was not available before. So if you are architecting your data mesh environment in the cloud, what you might be able to do is create various domains that exist on their own little microservice environments. And so you have all of these different domains that exist in one environment, but then they all connect to this bigger data mesh catalog. And from the catalog, that is where your colleagues across the business can access the data in your domain. Now, you don't want to necessarily give free rein for anybody in your organization to get any data at any time. You might want to establish guardrails for who is able to access which data and what those parameters are. And the data as a product mindset allows you to do that because it gives you, as the data steward/pseudo pm, the autonomy to define how and when your data is used, rather than giving that responsibility to a third-party colleague who does not have that context about the data in your domain. VICTORIA: I like that about really giving the people who have the right context the ability to manage their product and their data within their product. That makes a lot of sense to me. Mid-Roll Ad: As life moves online, bricks-and-mortar businesses are having to adapt to survive. With over 18 years of experience building reliable web products and services, thoughtbot is the technology partner you can trust. We provide the technical expertise to enable your business to adapt and thrive in a changing environment. We start by understanding what's important to your customers to help you transition to intuitive digital services your customers will trust. We take the time to understand what makes your business great and work fast yet thoroughly to build, test, and validate ideas, helping you discover new customers. Take your business online with design-driven digital acceleration. Find out more at tbot.io/acceleration or click the link in the show notes for this episode. VICTORIA: What is it like to really bring in this culture of design-thinking into an organization that's built a product around data? LAUREN: It can be incredibly hard. I have found that folks really vary in their approach to this type of work. I think many people that I talk to have tried doing data governance to some degree in the past, and, for various reasons, it was not successful. So as a result, they're very hesitant to try again. I think also for many technical leaders, if they're in CIO, CDO, CTO roles, they are not used to design thinking or to doing human-centered design work. That's not the ethos that was part of the tech space for a very long time. It was all about the technology, building what you could, experimenting and tinkering, and then figuring out the user part later. And so this is a real fundamental mindset shift to insist on having a vision for how data benefits your business before you start investing money and people into building different data pipelines and resources. It's also a fundamental shift for everyone in an organization because we, in society writ large, are taught to believe that data is the responsibility of one person or one team. And we just can't afford to think like that anymore. There is too much data produced and ingested on a daily basis for it to fall to one person or one team. And even if you do have a technical team who is most adept at managing the cloud environment, the data architecture, building the new models for things like fraud detection, that's all the purview of maybe one team that is more technical. But that does not mean that the rest of the organization doesn't have a part to play in defining the standards for data that govern everything about the technical environment. And I think a big comparison we can make is to security. Many of us… most of us, even if we work in tech, are not cybersecurity experts. But we also know that employees are the number one cause of breaches at organizations. There's no malintent behind that, but people are most likely to expose company data and cause a breach from within the company itself. And so organizations know that they are responsible for creating not just secure technical environments but educating their employees and their workforce on how to be stewards of security. And so, even at my company, we run constant tests to see who is going to be vulnerable to phishing? Who is going to click on malicious links? They run quarterly tests to assess how healthy we are from a cybersecurity perspective. And if you click on a phishing attempt and you fall for it, you are directed to a self-service education video that you have to complete, going over the aspects of this phishing test, what made it malicious. And then you're taught to educate yourself on what to look for in the future. We really need to be doing something very similar with data. And it doesn't mean that you host a two-hour training and then never talk about data again. You really need to look at ways to weave data governance into the fabric of your organization so that it is not disruptive to anybody's day. It's a natural part of their day, and it is part of working at your organization. Part of your organizational goals include having people serve as data stewards. And you emphasize that stewardship is for everyone, not just the people in the technology side of the business. VICTORIA: I love that. And I think there's something to be said for having more people involved in the data process and how that will impact just the quality of your data and the inclusivity of what you're building to bring those perspectives together. LAUREN: I agree. And that's the real goal. And I think this is, again, something that's actually easier for startups to do because startups are naturally more nimble. They find out what works, what doesn't work. They're willing to try things. They have to be willing to try things. Because, to use a really clichéd phrase, if they're not innovating, then they're going to get stale and go out of business. But the other benefit that I think startups have when they're doing this work is the small size. Yes, you don't have the budget or team size of a company like JP Morgan, that is enormous, or a big bank. But you still have an opportunity to really design a culture, an organizational culture that puts data first, regardless of role. And then you can architect the structure of every role according to that vision. And I think that's a really exciting opportunity for companies, especially if they are selling data or already giving data as a product in some way. If they're selling, you know, data as a product services, this is a really great approach and a unique approach to solving data governance and making it everyone's opportunity to grow their own roles and work smarter. VICTORIA: Right. And when it's really the core of your business, it makes sense to pay more attention to that area [laughs]. It's what makes it worthwhile. It's what makes potential investors know that you're a real company who takes things seriously. [laughs] LAUREN: That's true. That's very true. VICTORIA: I'm thinking, what questions...do you have any questions for me? LAUREN: I'm curious to know, when you talk to thoughtbot clients, what are the main aspects of data that they struggle with? I hear a variety of reasons for data struggles when I talk to clients, when I talk to people on the tech side, either as engineers or architects. I'm curious to hear what the thoughtbot community struggles with the most when it comes to managing big data. VICTORIA: I think, in my experience, in the last less than a year that I've been with thoughtbot, one challenge which is sort of related to data...but I think for many small companies or startups they don't really have an IT department per se. So, like, what you mentioned early on in the discovery process as, like, who is the most senior technical person on your team? And that person may have little to no experience managing an IT operations group. I think it's really bringing consulting from the ground up for an organization on IT operations, data management, user and access management. Those types of policies might just be something they hadn't considered before because it's not in their background and experience. But maybe once they've gotten set up, I think the other interesting part that happens is sometimes there's just data that's just not being managed at all. And there are processes and bits and pieces of code in app that no one really knows what they are, who they're used for, [laughs] where the data goes. And then, you know, the connections between data. So everything that you're mentioning that could happen when you don't do data governance, where it can slow down deployment processes. It can mean that you're giving access to people who maybe shouldn't have access to production data. It can mean that you have vulnerabilities in your infrastructure. That means someone could have compromised your data already, and you just don't know about it. Just some of the issues that we see related to data across the spectrum of people in their lifecycle of their startups. LAUREN: That makes total sense, I think, especially when you are in a startup. If you're going by the typical startup model, you have that business-minded founder, and then you likely have a more technical co-founder. But we, I think, make the assumption that if you are, quote, unquote, "technical," you, therefore, know how to do anything and everything about every system, every framework, every type of cloud environment. And we all know that that's just not the case. And so it's easy to try to find the Chief Technology Officer or the Chief Information Officer if one exists and to think, oh, this is the right person for the job. And they might be the most qualified person given the context, but that still doesn't mean that they have experience doing this work. The reality is that very few people today have deep hands-on experience making decisions about data with the volume that we see today. And so it's a new frontier for many people. And then, on top of that, like you said as well, it's really difficult to know where your data lives and to track it. And the amount of work that goes into answering those very basic questions is enormous. And that's why documentation is so important. That's why data lineage in your architecture is so important. It really gives you a snapshot of which data lives where, how it's used. And that is invaluable in terms of reducing technical debt. VICTORIA: I agree. And I wonder if you have any tips for people facilitating conversations in their organization about data governance. What would you tell them to make it less scary and more fun, more appealing to work on? LAUREN: I both love and hate the term data governance. Because it's a word that you say, and whether you are technical or not, many people tune out as soon as they hear it because it is, in a way, a scary word. It makes people think purely of compliance, of being told what they can't do. And that can be a real challenge for folks. So I would say that if you are tasked with making a data governance program across your organization, you have to invest in making it real for people. You have to sell them on stewardship by articulating what folks will gain from serving as stewards. I think that's really critical because we are going to be asking folks to join a cause that they're not going to understand why it affects them or why it benefits them at first. And so it's really your job to articulate not only the benefits to them of helping to set up this data stewardship work but also articulating how data governance will help them get better at their jobs. I also think you have to create a culture where you are not only encouraging people to work across party lines, so to speak, to work across silos but to reward them for doing so. You are, especially in the early months, asking a lot of people who join your data stewardship initiatives and your data governance council you're asking them to build something from the ground up, and that's not easy work. So I think any opportunity you can come up with to reward stewards in the form of bonuses or in terms of giving them more leeway to do their jobs more of a title bump than they might have had otherwise. Giving them formal recognition for their contributions to data governance is really essential as well. Because then they see that they are rewarded for contributing to the thought leadership that helps the data governance move forward. VICTORIA: I'm curious, what is your favorite way to be rewarded at work, Lauren? LAUREN: So I am a words person. When we talk about love languages, one of them is words of affirmation. And I would say that is the best way to quote, unquote, "reward me." I save emails and screenshots of text messages and emails that have really meant a lot to me. If someone sends me a handwritten card that really strikes a chord, I will save that card for years. My refrigerator is filled with holiday cards and birthday cards, even from years past. And so any way to recognize people for the job they're doing and to let someone know that they're seen, and their work is seen and valued really resonates with me. I think this is especially important in remote environments because I love working from home, and I am at home alone all day. And so, especially if you are the only person of your kind, of your role on your team, it's very easy to feel insular and to wonder if you're hitting the mark, if you're doing a good job. I think recognition, whether verbally or on Slack, of a job well done it really resonates with me. And that's a great way to feel rewarded. VICTORIA: I love that. And being fully remote with thoughtbot, I can feel that as well. We have a big culture of recognizing people. At least weekly, we do 15Five as a tool to kind of give people high-fives across the company. LAUREN: Yep, Steampunk does...we use Lattice. And people can submit praise and recognition for their colleagues in Lattice. And it's hooked up to Slack. And so then, when someone submits positive feedback or a kudos to a colleague in Lattice, then everyone sees it in Slack. And I think that's a great way to boost morale and give people a little visibility that they might not have gotten otherwise, especially because we also do consulting work. So we are knee-deep in our projects on a daily basis, and we don't always see or know what our colleagues are working on. So little things like that go a long way towards making people feel recognized and valued as part of a bigger company. But I'm also curious, Victoria, what's your favorite way to get rewarded and recognized at work? VICTORIA: I think I also like the verbal. I feel like I like giving high-fives more than I like receiving them. But sometimes also, like, working at thoughtbot, there are just so many amazing people who help me all throughout the day. I start writing them, and then I'm like, well, I have to also thank this person, and then this person. And then I just get overwhelmed. [laughs] So I'm trying to do more often so I don't have a backlog of them throughout the week and then get overwhelmed on Friday. LAUREN: I think that's a great way to do it, and I think it's especially important when you're in a leadership role. Something that I'm realizing more and more as I progress in my career is that the more senior you are, the more your morale and attitude sets the tone for the rest of the team. And that's why I think if you are in a position to lead data governance, your approach to it is so crucial to success. Because you really have to get people on board with something that they might not understand at first, that they might resent it first. This is work that seems simple on the surface, but it's actually very difficult. The technology is easy. The people are what's hard. And you really have to come in, I think, emphasizing to your data stewards and your broader organization, not just what governance is, because, frankly, a lot of people don't care. But you really have to make it tangible for them. And you have to help them see that governance affects everyone, and everyone can have a hand in co-creating it through shared standards. I think there's a lot to be learned from the open-source community in this regard. The open-source community, more than any other I can think of, is the model of self-governance. It does not mean that it's perfect. But it does mean that people from all roles, backgrounds have a shared mission to build something from nothing and to make it an initiative that other people will benefit from. And I think that attitude is really well-positioned for success with data governance. VICTORIA: I love that. And great points all around on how data governance can really impact an organization. Are there any final takeaways for our listeners? LAUREN: The biggest takeaway I would say is to be thoughtful about how you roll out data governance in your organization. But don't be scared if your organization is small. Again, it's very common for people to think my business is too small to really implement governance. We don't have the budget for, you know, the AWS environment we might need. Or we don't have the right number of people to serve as stewards. We don't actually have many data domains yet because we're so new. And I would say start with what you have. If you are a business in today's day and age, I guarantee that you have enough data in your possession to start building out a data governance program that is thoughtful and mission-oriented. And I would really encourage everyone to do that, regardless of how big your organization is. And then the other takeaway I would say is, if you remember nothing else about data governance, I would say to remember that you automate your standards. Your standards for data quality, data destruction, data usage are not divorced from your technical team's production environments; it's the exact opposite. Your standards should govern your environment, and they should be a lighthouse when you are doing that work. And so you always want to try to integrate your standards into your production environment, into your ETL pipelines, into your DevSecOps. That is where the magic happens. Keeping them siloed won't work. And so I'd love for people, if you really enjoyed this episode and the conversation resonated with you, too, get a copy of the book. It is my first book. And I was really excited to work with the Pragmatic Programmers on it. So if readers go to pragprog.com, they can get a copy of the book directly through the publisher. But the book is also available at Target, Barnes & Noble, Amazon, and local bookstores. So I am very grateful as a first-time author for any and all support. And I would really also love to hear from thoughtbot clients and podcast listeners what you thought of the book because version two is not out of the question. VICTORIA: Well, looking forward to it. Thank you again so much, Lauren, for joining us today. You can subscribe to the show and find notes along with a complete transcript for this episode at giantrobots.fm. If you have questions or comments, email us at email@example.com. And you can find me on Twitter @victori_ousg. This podcast is brought to you by thoughtbot and produced and edited by Mandy Moore. ANNOUNCER: This podcast is brought to you by thoughtbot, your expert strategy, design, development, and product management partner. We bring digital products from idea to success and teach you how because we care. Learn more at thoughtbot.com. Special Guest: Lauren Maffeo.
This week, Alex spoke to two guests from the world of Microsoft for Startups - GM, Hans Yang, and Senior Director, Tom Davis. We're working to figure out how big tech corporations are playing in the startup sandbox, starting with the launch of Microsoft's Pegasus program.Here's what we got into:Why programs like Pegasus are particularly helpful for startups in a conservative VC marketThe mutually beneficial relationship between the large tech players and startupsThe close relationship between Microsoft and OpenAIAs always, Equity will be back on Friday with your weekly news round up, but until then, you can catch us on Twitter @EquityPodFor episode transcripts and more, head to Equity's Simplecast website. Equity drops at 7:00 a.m. PT every Monday, Wednesday and Friday, so subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. TechCrunch also has a great show on crypto, a show that interviews founders, one that details how our stories come together and more!
Sunny and Vinny are back to demo some new AI tools (14:08), discuss open-source vs. "ClosedAI" (38:45), and more! (0:00) Jason kicks off the show (1:31) Jason's trip to the UAE and Abu Dhabi's 30-year investment horizon (12:39) Miro - Sign up for a free account at https://miro.com/startups (14:08) Sunny demos ChatPDF and LLMs' future in the workforce (24:23) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist (25:41) Google's new universal translator (30:11) What is Hugging Face? (37:26) iConnections - Get 20% off iConnections Miami 2024 event at http://iconnections.io/twist (38:45) Open-source vs. "ClosedAI" and the race to build AI hardware (48:28) Comparing Google Bard to ChatGPT (1:01:13) Google's vision for Gmail and AWS's partnership with Hugging Face FOLLOW Vinny: https://twitter.com/VinnyLingham FOLLOW Sunny: https://twitter.com/sundeep FOLLOW Jason: https://linktr.ee/calacanis Links: https://www.semianalysis.com/p/google-we-have-no-moat-and-neither https://www.chatpdf.com https://huggingface.co/espnet/kan-bayashi_ljspeech_vits Subscribe to our YouTube to watch all full episodes: https://www.youtube.com/channel/UCkkhmBWfS7pILYIk0izkc3A?sub_confirmation=1 FOUNDERS! Subscribe to the Founder University podcast: https://podcasts.apple.com/au/podcast/founder-university/id1648407190
Welcome to the newest episode of The Cloud Pod podcast! Justin, Ryan, Jonathan, and Matthew are all here this week to discuss the latest news and announcements in the world of cloud and AI - including New Relic Grok, Athena Provisioned Capacity from AWS, and updates to the Azure Virtual Desktop. Titles we almost went with this week: None! This week's title was SO GOOD we didn't bother with any alternates. Sometimes it's just like that, you know? A big thanks to this week's sponsor: Foghorn Consulting, provides top-notch cloud and DevOps engineers to the world's most innovative companies. Initiatives stalled because you have trouble hiring? Foghorn can be burning down your DevOps and Cloud backlogs as soon as next week.
We get you up to speed on two serious flaws, Linux's recent gaming loss, Ubuntu doubling down on RISC-V, and news from the Open Source Summit North America.
AWS Morning Brief Extras edition for the week of May 10, 2023.Want to give your ears a break and read this as an article? You're looking for this link.https://www.lastweekinaws.com/blog/9-things-I-love-about-awsNever miss an episode Join the Last Week in AWS newsletter Subscribe wherever you get your podcasts Help the show Leave a review Share your feedback Subscribe wherever you get your podcasts Buy our merch https://store.lastweekinaws.comWhat's Corey up to? Follow Corey on Twitter (@quinnypig) See our recent work at the Duckbill Group Apply to work with Corey and the Duckbill Group to help lower your AWS bill
The Jason & Scot Show - E-Commerce And Retail News
EP305 - Amazon and Shopify Q1 2023 earnings Amazon and Shopify both reported their Q1 2023 earnings last week. Amazon had a strong first quarter, slightly over-shadowed by it's slowing AWS growth. Shopify also had strong Q1 2023 earnings although it did not achieve profitability. Shopify also announced a second reduction of headcount and announced that they were selling all of the recently acquired logistic assets. Don't forget to like our facebook page, and if you enjoyed this episode please write us a review on itunes. Episode 305 of the Jason & Scot show was recorded on Thursday, May 4th 2023. http://jasonandscot.com Join your hosts Jason "Retailgeek" Goldberg, Chief Commerce Strategy Officer at Publicis, and Scot Wingo, CEO of GetSpiffy and Co-Founder of ChannelAdvisor as they discuss the latest news and trends in the world of e-commerce and digital shopper marketing. Transcript Jason: [0:23] Welcome to the Jason and Scot show, this is episode 305 being recorded on Thursday May 4th May the 4th be with you I'm your host Jason retailgeek Goldberg and as usual I'm here with your co-host Scot Wingo. Scot: [0:39] Hey Jason and welcome back Jason Scott showed listeners Happy Star Wars Day May the 4th be with you hope everyone had a great Star Wars Day Jason people can't see you but you are wearing your Jar Jar Binks cosplay. Jason: [0:53] I kind of assumed people just assume I'm always wearing that. Scot: [0:57] You should do the whole episode and jar jar speak well said Jason what's a new at the Amazon what. Jason: [1:10] I feel like people don't get the jar jar one I did I did do an act during covid-19 doing all this pitch theater online I did a pitch on Halloween in a Darth Vader mask. And we won the pitch so I feel like I should be doing costumes more. Scot: [1:28] Awesome you guys intimidate them and it's called the Darth Vader intimidation closed when you wear the Vader the Vader suit. Jason: [1:34] Exactly exactly and it had the voice changing thing and so it is. Scot: [1:38] Honest I find your lack of faith yeah there's a lot of death lot of lot of puts you can use in a pitch. Jason: [1:48] Yes unfortunately not a large enough chunk of the total addressable Market are Geeks. If you like is wrong I know how I got in this like funky like creative advertising world with all these I kept custody clients like I totally don't fit in. Scot: [2:09] Yeah been a misfit toy my whole life so sir not going to stop anytime soon embrace it Jason. Jason: [2:15] Yeah it was announced today that we won a big new client lvmh and so I like went on LinkedIn and joke that like it was largely thanks to my my stature is a luxury influencer. Scot: [2:29] Nice congrats your tick-tocks on luxury have one the death. Jason: [2:32] I know I know for a long time people were like why are you wasting your time with that and now they know. Scot: [2:38] Who will we have it's been a while since we dropped a pod because we both had spring breaks and then you've been traveling a bit so it's great to be back. Jason: [2:49] Yeah it's super fun to catch up with you and with the audience. I feel like the last show we did was right after shoptalk so I did get to see a bunch of folks and now you know it's a treat your season is starting to heat up so I have a bunch of upcoming trips so. If listeners are going to any of these shows make sure you make a point to catch up with me and you could see the jar jar costume. In person so I'm actually doing this show from. The famous Mayflower Hotel in Washington d.c. because I'm in town for the. Home and Commercial products Association I'm doing the keynote for their annual conference tomorrow morning. And then I'm going to sap Sapphire which is their big customer show in Orlando in on May 15th if you like. There's a fair amount of our listeners that go to that show and then to fun ones that are you know core Commerce shows after that we have Commerce next by our friends Scott Silverman is in New York in June so June 20th. And I'll be doing some fun stuff stuff on stage there and then in RFC you know has their kind of future looking executive digital Summit. [4:07] On the beach it Tara no in Rancho Palos Verdes it's called the inner F Nexus on July 10 and all both be giving a keynote and I will also be interviewing Kara Swisher so I feel like. I'm going to spend an hour just making fun of Scott Galloway with her. Scot: [4:25] Nice yeah that's good the dog dog is off the porch whoo. Jason: [4:30] Exactly I was thinking about like maybe bring a mask I've already you know I have audio collection of a lot of my favorite Scott Galloway predictions meaning which didn't come true. Scot: [4:43] Macy's Woodberry Amazon and apparel. Jason: [4:47] But I feel like this is. Scot: [4:48] Amazon to be Roadkill. Jason: [4:50] Like Freaky Friday like so like Cara is this like super famous interviewer and I am interviewing her and we're doing it at Tara know where she started code conference so it's very topsy-turvy. Scot: [5:03] Yeah yeah just bring red tears without her trademark thing. Jason: [5:07] I assume she just travels with one of her own yeah that Herman Miller red chair yeah. Scot: [5:09] BYO RC okay. Jason: [5:15] I actually think she's not with Vox anymore so I don't know you know she may be in withdrawn not she may have said said goodbye to the red chairs will have to ask her. Scot: [5:24] Look that's that's question number one. Jason: [5:26] Yeah but besides all of that we are just getting started on q1 earnings season and you know of course for most of our listeners one of the most important earnings calls happened last week. Scot: [5:39] Yeah it wouldn't be a Jason and Scot show if we didn't have some Amazon news. So on April 27th which was last Thursday when we're recording this Amazon had their earnings it was what Wall Street would call a clear beat meaning both top and the bottom line where a beat this is welcome news because Amazon's earnings have been kind of like not not mrs. but not amazing. [6:07] So revenues came in two percent above consensus which is a slight beat but what got Wall Street very excited was operating income came in 57 percent above and longtime listeners will know I usually cover the retail portion of Amazon and Jason covers the cloud or a WS part, we're going to mix it up because I read all the reports and what was most interesting right now in kind of the world of Internet stocks the whole world has been turned upside down by chat GPT which is put out by open AI Sam Altman startup who is partially owned and supported by Microsoft there and investor and the hole, infrastructure runs on Azure their cloud computing, platform this has been a huge win for Microsoft because it's enabled them to add a chat gbt like component to Bing. [7:02] And you know the buzz is that, search is dead a lot of people are even speculating maybe even apps will be dead you know maybe maybe you don't really need apps on a phone if you could just talk to your phone and say hey book me restaurant reservation as 6:30 at the one of these three restaurants why do you need a nap if an AI can go to that room so there's there's a lot of people in the Wall Street and Tech world are, I would say there's like this wall of worry around this new innovation and this is real so chat GPT was the fastest product to 100 million users what was it Jason like four weeks or something. [7:42] Like an egg yeah if you see a chart it's like this a vertical wall whereas like Facebook and some of those kinds of things were previous record holders for this and it took, you know years and so-so. Jason: [7:54] Two months to a billion or 4 months to a billion users. Scot: [7:58] Yeah so it's just this crazy adoption curve unlike anything we've ever seen before so you know there's, this was top of mind when this came out so the so while streets pretty obsessed with what's going on with the cloud also Amazon's Cloud division has been slowing their growth it was the you know the darling of the Amazon portfolio and now it's been slowing because as we head into this recessionary period, also another concern is we cover this a little bit last time but Silicon Valley Bank failed we've had all this kind of startup craziness and a lot of those startups use cloud computing and Amazon so, so that was what all eyes were on and you know what we saw was the growth did slow to 11 and a half percent which was less bad than what people were thinking so is kind of viewed as positive which is always one of these counter, Wall Street all about expectations not like the real absolute numbers but 11.5 percent growth is this is this part we've been covering this for for. [9:04] Years of this point five years and it's always growing north of 50% but this time it really slowed down and they're even projecting for next quarter or slow 2011 Amazon did Jesse did talk a lot about AI there they've talked about how they're going to do a lot of people the other problem with Chad gbt is it looks the prior to the prior a I think we all spend a lot of time with which was Alexa now feels wildly inferior because you're having these really robust conversations with chat gvt and Alexis can do like, yeah it's not really like at that level of conversational AI you can get some weather maybe play a song and a couple other little things add something it'll talk to you about do you want to reorder your dog food and yeah that's about it right so very, Barry and then you know that used to be cool and now in a world where we're chatty be teeing it feels inferior so Amazon like Google is a little bit on their heels from this and they basically came out and said we're going to do a lot around Alexa here and it will we're dedicated that being by far the best voice assistant, and we'll be adding chats ubt like capabilities but then for AWS they basically said look there's all these language models out there and we're going to be neutral will have all kinds of different flavors kind of thing so whatever you want we'll have. [10:30] And the one of the concerns is these large language models use a ton of gpus and those are expensive. Azure is adding a ton of workloads from this and their conference call they went so far as to say. It's like accelerated growth dramatically at Azure they're getting all these loads that they would have never seen before thanks to their relationship and, they're scaling up this gpus and so it kind of feels early and Aang's like maybe Microsoft has got like this. Bit of an advantage over both Google and they WS so, so you know it was interesting because I'm saying all that because what happened is they announced their up a little bit that day and then they announced and they were down and they've been kind of sideways since then so and what was clear be quarter with AWS not as bad as you would think it would be you had the numbers would say oh the stock should go up 5 to 10% but they didn't because I don't think everyone really liked, body language around you know what's going on chat gbt and Amazon's response. [11:40] So that was a that was a long part but that was I thought it was kind of interesting. The whole world and like the last yeah six months has been turned upside down by this and it's always an option or that always gets my attention because this is where unique opportunities are created for disruption and all kinds of what happens is when my favorite books is the innovators dilemma when something new like this comes along, people that were previously the leaders have a really hard time adapting to it because they get baked into their business model so for example to pick on Google it's very hard for them to offer a chat interface on the core Google search because, every pixel of core Google search is like so highly optimized and them hitting their numbers relies on that that real estate. [12:28] Basically not changing that to change that real estate and experiment with something that is expensive and not monetized is. Almost impossible you know it's it will certainly make them lose mountains of Revenue and even worse on ibadah, so it's really kind of fascinating to Think Through the strategy here of what's everyone going to do and how do they adapt to this new world and to some extent Amazon not as bad as Google I would argue but that Amazon is a little bit of a in a pickle. Um it got even so bad also around the same time Jeff Bezos was at Coachella and he was just out there dancing and wearing this kind of fun butterfly shirt and everyone's kind of like you know it almost felt like fiddling while Rome burned so a lot of people are like and then you know so Disney's CEO has come back and a lot of people are projecting that maybe we'll see a day where like a Larry Page comes back to Google and a Bezos comes back to Amazon to it's going to be interesting to see what happens this next next three to six months are gonna be really fun to watch in the world of large trillion-dollar internet companies to see what's going down. Jason: [13:39] Oh for sure and I keep saying this but we're going to have to do another. Deep dive on AI and chechi because there are so many it's changing so, fast and there's this whole like shift from keywords to prompts and you know like all of you know Google's intrinsic strengths are suddenly becoming weaknesses there's this interesting battle, um between like these AI capabilities as destinations versus these AI capabilities as. Sort of infrastructure that that you add to any destination right and so you know the interesting thing about Chad gbt you can license the. The GPT for engine and build it in your own apps or your own website but 1.2 billion consumers a month, are going to chat. Open a i.com so that's now a destination on the web that's bigger than Bing. [14:40] Like move more people last month went to their website opening eyes website then went to Bing and that's a, Game Changer I get it's feels like a huge missed opportunity side note that there's not ads on that website yet I'm sure I'm sure that that that is coming in Italy but so there are all these like super interesting changes. I kind of feel like even if all that wasn't playing out like just the the fact that AWS is decelerating a little bit. [15:10] Would be the news from this earning thing and it's what everyone's talking about and it's almost a shame because it's kind of masking what otherwise like is a pretty remarkable quarter compared to like what most of their peers are likely to do. Scot: [15:25] Yeah yeah walk us through some of the highlights that you saw in the non aw site. Jason: [15:30] Well so the first thing if you look at North American gmv it grew 13% in q1 so that that is a deceleration from, their Q4 growth but like to put that in comparison. Us retail sales grew four percent in the first quarter so so you know this is kind of back to pre-pandemic levels where Amazon's growing. Despite being you know the largest or second largest retailer in the US depending on how you count growing quite a bit of water faster than the industry, you don't normally we would we compare Amazon's growth to all retailers growth but also to all of e-commerce has growth, so the US Department of Commerce comes out with their Q2 growth numbers in a couple weeks so May 18th I think if you want to mark your calendars will do a show and talk about that but. Just kind of interpreting the data and extrapolating. [16:31] U.s. e-commerce and q1's likely to grow about 10% which is kind of a recovery for e-commerce but still, that means Amazon the largest e-commerce player out there is growing faster than the industry as a whole which is. You know typical for Amazon but you know not very typical in the rest of the world so the retail story was, was really strong and it was driven almost exclusively by your favorite part of the retail Echo System the marketplace right it was almost all. [17:00] 3p sales which I want to say grew 16 percent. Or fifteen percent for the quarter so so 3p continues to be a super important part, and you know I always like to talk about the ad business ads were up 21% which is a, a deceleration of the ads business as well just like AWS but a couple interesting things, there's a ton of headwinds, for traditional dip digital ads right now as the economy is getting a little more challenging you know a lot of brands are cutting back on their spinned because the privacy issues they're cutting back on a lot of the traditional digital channels, um so you look at like metas ad business in q1 it grew three percent Google's ad business grew to percent. [17:55] Pinterest was the leader of those kind of traditional platforms their ad business grew five percent, and Amazon which is has a bigger ad business than Pinterest Amazon grew 21% so that that growth you know continues to be remarkable, um I did a quick back of the napkin estimate and I, I know AWS generated about 5 billion dollars in earn income for the quarter the ad unit probably generated 7.1 billion dollars in earning come for the quarter so quite a bit more, profit to the bottom line coming from that ad business then coming from from AWS, and then you know Amazon you know as they always do they kind of pepper and some favorable stats so they talked about how. They they had 26 million customers for same-day delivery in q1 which is fifty percent growth year over year so you know you. You kind of you've seen a lot of other retailers that as the economy has gotten kind of tough they've kind of. [18:58] Ratcheted back their service level a little bit like you're seeing a lot of people starting to charge more for returns you're starting to see delivery promises get stretched out a little bit and you know Amazon is kind of. Adjusting their returns policy as well but like they're they're all in on that fast same day delivery. And it seems like consumers are continuing to embrace that. Um there's this kind of big strategic shift that they talked about Scott that I know you've been falling which is kind of the shift from a national fulfillment model to a regional fulfillment model. And this is all about getting more efficiency so the idea is you know in the old model you placed an order and you know they ship from whatever Warehouse fulfillment center had the goods in stock so often that. Are shipping things from pretty far away, and mold you know in a you know your your multicart order could have Goods coming from a lot of different fulfillment centers and you know this quarter the focus is really on redesigning the whole fulfillment center to optimize. [20:06] How many trips they have to make to your house and how many, how much of the goods can all come from the same fulfillment center so there's a laser focus on kind of getting the inventory in each fulfillment center right for the market that it's serving, um and the you know in their investor call the CFO was talking about how like they're starting to they're already starting to unlock. Um significant improvements in their operating margins as a result of cutting down on the amount of trips in order to serve the same amount of gmv and they think there's a lot of Headroom to continue improving math if you've been following that kind of, Regional shift it almost feels like the Reinventing the you know kind of against innovators dilemma they're Reinventing their whole fulfillment model despite the fact that they have the. The world's largest fulfillment model. Scot: [21:00] Yeah yeah I think this is really interesting and in some ways maybe the go Puffs the world kind of showed him how to do this ironically enough and you know and this surge of same-day delivery I think they're having. I think you know in the early days the same day delivery I remember Sebastian going ham he was SVP saying yes he was at our conference and he said something like we just put out there to see and we were surprised by how many people use it and then you know they had data that indicated this is like five years ago that it was addictive because you. [21:37] We have forget which of us going this is your zero friction addiction so once you have one of these low-friction experiences you're like yeah yeah you know of course I would like it yeah, I'm running this morning all like it the same day but that's making them for deploying a lot more of the product to be able to satisfy that demand but they have the data to do it the key is it's a you know there's, there's this you know something like 300 million skus out there in the cloud that you can buy a small portion of those percentage-wise large sales wise is in the network of FCS and then the system learned what to, put at the edge near you and that same day thing there's a set of skus and it's probably down to 10,000 at that point, that they know those are the most frequently Asked seemed a things it's going to be things like toilet replenishable toiletries, dog food for me all those types personal items Healthcare Beauty and you know it's not the it's not the Xbox or something that can kind of weight well I guess some of that could be but you know there's plenty of stuff people are happy to wait for so, that that edge Network allows them to Ford deploy 5 to 10,000 excuse and get them to you really fast. Jason: [22:56] Yeah and I think what's interesting is that it turns out that the. The those skews that are needed for same-day delivery in Raleigh are not the same as the skills that are needed in Chicago and AI is really helping them sort of optimize. Those fulfillment centers and the numbers are actually a little bigger than your you're saying there are now like 300,000 same day skus in the system and in some markets there they have over 100,000 skus available for same-day so it y you know there. [23:26] They're kind of expanding from the head in skews to you know at least the chunky middle scuze. On that same day delivery and it and it seems like that's continuing to work for them. I just think it's you know again a lot of people that had you know the huge infrastructure lead the Amazon had him fulfillment centers you know would. But I find it hard to disrupt that model and pivot to a new model and it seems like you know Tim zones credit they're they're not afraid to disrupt themselves and it feels like that's kind of what they're doing here. And it seems like it least pull narrowly it's working you know they're also. Over the covid time there have been some capacity constraints and they rolled out a lot of technology to help help third-party sellers better manage their own. Capacity and you know I'm hearing from third-party sellers that that is going better that they have you know are better able. [24:29] Predict the cost and the capacity that will be available for them and they're not getting as many unpleasant surprises as they as they kind of had had in the past of that that stuff is all interesting, I also think Amazon's big enough that they're they're you know kind of a. A good surrogate for for the actual consumer economies at this point and so is interesting you know they talked about the Americans can consumer and you know the North America was where a lot of Amazon's growth was. Um They they had a statement that they're continuing to see the US consumer is being conscious that she's definitely moderated her spending on discretionary categories, she's trading down to more value oriented eizan's. [25:16] You know there continues to be healthy demand for Staples and you know I think we heard similar things from other big retailers like Wal-Mart and Target so that kind of felt in line but what was interesting was Europe. The growth is much slower but it was a significantly higher beat versus expectations than North America was and they had kind of an interesting editorial on Europe they said that, European demand while cautious came in better than expected, we see customer confidence increasing with inflation tickling down in the EU and that's kind of at odds with a bunch of other retailers that that are competing in Europe that are still you know kind of talking about, the consumer Demand Being really repressed in Europe and the European consumer really struggling due to even higher inflation then then what consumers are experiencing here in North America so, um it either sounds like Amazon's having a better go of it than a lot of other retailers in Europe, or Amazon is being the first one to sort of see the economy turning a little more favorable in Europe so. I kind of found that interesting. [26:42] Yeah well again you know the. Historically like Europe is smaller than North America for Amazon but it you know because it's smaller it was growing faster but you know there have been more. Challenges supply chain disruptions there's more uncertainty in a lot of the European economies and so you know it's like for global companies I'm particularly brands that do business everywhere. Um that European softness has been a challenge the one outlier of all that is luxury so it does feel. Like kind of a bifurcated economy that like luxury can you know is actually kind of bounce back in Europe and is continuing to do pretty pretty well worldwide while. High inflation is hurting a lot more of the kind of staple Industries a lot more. Scot: [27:35] Having Survived the Great Recession of 08 and 09 at Chow buzzer the weird thing about the data was the luxury segment accelerated you have to have the the wealthy folks do find during economic downturns turns out. Jason: [27:50] Yeah this was a weird one in that like that's for that was for sure true where the demand was shifted in unusual ways because often you have a lot of. Really wealthy consumers are also tend to be really mobile consumer so you have, historical you'd have a lot of really wealthy people from China that would go to France and buy a lot of luxury goods and in covid of course nobody was going anywhere so there was this huge, spike in luxury goods in China so like the overall worldwide demand for luxury was very high but there were these weird mismatches where the demand was not coming from the markets that it typically came from and now it feels like it's. Reverting more it's starting to revert to more traditional. [28:37] So there was a another interesting earnings call this morning. Scot: [28:41] Yeah so Shopify came out with their earnings and they've had just kind of set the stage. In the during covid they were Off to the Races and they've had a really hard time in the last year kind of in that post covid era as they invested so much and then covid the e-commerce growth reverted to the mean as you've been, so good at pointing out and they thought it would just continue up into the right and so they did about a ten percent reduction in force I think is a year ago maybe a little longer, and so then this morning they came out and they beat Lowered Expectations to put this in perspective of their growth has slowed to 25% and they were consistently growing well north of 50% so they're they're definitely, this was good for a while there were kind of Contracting but now at least they're back to growth they are losing money but they should get back to profitability here in a quarter or two but the big surprise was you know if you recall they were going to take on Amazon and they started really building out some fulfillment and they bought a couple companies to do that and started building out this whole infrastructure called Shopify fulfillment Network or sfm. [30:00] So they announced on the call today that they're just basically abandoning that whole strategy and the assets they previously bought an aggregate for over two billion dollars they sold to a company called Flex port for a billion so that had to hurt so basically a billion dollar loss on the strategy and they basically said you know the future is AI and that's where we're going to put our effort, and then when they sell this unit there also some people go with that but they're also announced they're doing at 23% that would include some of those people it's not it's not entirely clear. [30:36] How many will be core Shopify versus the people leaving with the sfn I think it's. Relatively small you know I don't think that's happened was like this huge. People operation like you have an Amazon anyway so they're going to reduce headcount by 11,000 people 29k so from 11,000 29k, so about 23% reduction these things are always kind of. [31:06] Little tricky emotionally because you feel for those people that are losing their jobs and found out this morning that's going to be no fun, but then Wall Street loves a good reduction for us because that means more profits oh, the stock this is a huge win for the stock because Wall Street has hated hated hated this idea if you take this super high margin software business and you layer in a super low margin fulfillment business, so you know Wall Street this is part of the innovators dilemma, once you've baked your margins in at 85% or whatever you can't then go to Wall Street and say we're going to bring that down 15% 270 because we're going to be fulfillment and that's a, yeah 30% margin business your blend that in with our 85 you get us to 70 or whatever it is, so so Wall Street was very happy to see them abandoned us, it does raise the question one of the reasons they got in this is you and I talked a lot about Shopify versus Amazon and you know the same time. Amazon is raising the bar on e-commerce we just talked about this two same day, Shopify was going to arm the rebels so that they could at least keep up with two day now they're abandoning that you know there's gonna continue to be, yeah this could be a big moment in history where Shopify messes up and you know. [32:29] What's a I going to solve if you have this great product recommendation or something that doesn't show up for five days in Amazon eats the Shopify Merchants lunch because they just are better at Logistics so this is this is a big decision throwing in the towel and it's going to be interesting to see, if this is wise or not I obviously lean towards I don't think this is going to be a great in decision for him. Jason: [32:57] Yeah it is tricky. The you know I would also mention there's this so I you know scary service from Amazon looming on the Shopify Horizon that it's not clear Shopify his really declared what they want they're going to do with yet which is the. The by with prime service which is you know in in effect to use that really solid Amazon Fulfillment Network even when you sell stuff on Shopify. And so you know maybe they're they're dumping on the Shopify fulfillment Network stuff in there just gonna see the Fulfillment Amazon we'll have to see. Um I do I've decided to correct one thing you said like Shopify is huge on talking about e-commerce regress to the mean. That's actually not true right get when they talk about that they're talking about the ratio of e-commerce sales to retail sales and it's partly true for that. That you know we kind of went from 14 or 15 percent of all sales being online to 17 or 18 percent and we bounced back down to 15%. Um you know that that shape varied while we you know depending on the category so image digitally immature categories like Grocery and Automotive had kind of a permanent Spike whereas, like apparel you know had kind of a temporary bump. [34:23] In absolute dollars e-commerce is way bigger than before the pandemic e-commerce is 90% up from from 2019 and so when when they kind of use that. As an excuse for the layoffs I would say like don't buy it right like that. [34:41] There's a lot more demand for digital Goods than there were in 2019 and Shopify isn't laying people off because that demand has receded like throwing people off because they haven't perfectly figured out what the right business model is and from my standpoint. They're still a little dyslexic on who they're even trying to serve they still have all this language around you know serving the small Independent Business the mom-and-pop and arming the rebels and all that but like you know when you listen all the success stories in their earnings calls. It's it's Staples it's why it's it's you know it's it's bigger or midsize specialty retailers that are moving to the platform, it's not the rebels I, Kendall Jackson and Kendall Jenner and Staples are not the rebels and so I don't know like I think they like that that narrative but like I'm not sure they've come a perfectly aligned their product offering to the. The companies that are like driving the bulk of their gmv growth and when they you know do focus on the long tail Mom and Pops. It really makes that gmv number kind of office gated because there's so much churn over there right and they go or gmv went up 25%. Was that because like all your customers are thriving and they're all growing or is it because you just added way more companies that will have a nine-month mortality rate than you then you did the quarter before. [36:09] So I think it's like I definitely like there's a lot of strong, sort of advantages and and experiences still in the Shopify ecosystem and. Feel like shot pay is getting some traction the shop app has got a lot more traction than I originally predicted and now there are some legitimate. Marketplace features in there there's a lots of things going for them I certainly would not write them off but I do think. Like in the next couple of quarters we need to see some more clarity about like what they want to be and where their growth is really going to come. Scot: [36:46] Yeah yeah it's going to be we'll be tracking it closely on the show as we have them so it's going to be interesting to see I don't think either of us had this in our predictions though sadly. Jason: [36:57] Yeah no I mean I was definitely caught by I never thought this Acquisitions made sense but I certainly thought that you know they would hold on to him longer so I don't know I guess if you're an investor like. Like once you realize it was the wrong decision like there's probably something good about like cutting bait quickly instead of trying to. Drag it around drag it out longer just because you you don't want to own up to the mistake. So anyway that feels like a pretty good recap of the two big earnings there's a you know a bunch of the traditional retailers will be record reporting over the next four weeks and of course we'll have US Department of Commerce data, including q1 e-commerce. Later this month so lots of reasons to have another new show and I still do think we got to get that. That large language Model A I show on the on the books. Scot: [37:52] Yeah yeah we will we're through our vacation period and we should have some time to lay that down and Jason you've got a keynote tomorrow and you got some slides to work on buddy so we're going to make this a short one in the pantheon of Jason and Scot show lengthy episodes. Jason: [38:09] Yeah yeah we'll give it a few minutes back to our listeners and I will go write a keynote for tomorrow. Scot: [38:15] Awesome it's always good when you're up against deadlines so you're going to crush it. Jason: [38:20] I feel like the one thing I have going for me is the present the content will be very Timely. Scot: [38:26] Good yep fresh like. Jason: [38:30] Awesome Scott thinks every very much everyone for listening as always enjoyed the show we sure would love it if you jump on iTunes and give us that five star review and until next time happy commercing!
Amazon CodeCatalyst is a unified software development service that makes it easier for you to build and deliver applications on AWS. Now generally available, CodeCatalyst provides everything you need to start planning, coding, building, testing, and deploying applications on AWS with a streamlined, integrated experience. Hear from DevOps Services GM Harry Mower about what led to the creation of CodeCatalyst, how it helps developers, and what's coming next in 2023. Amazon CodeCatalyst - https://bit.ly/418Azig Read the announcement - https://go.aws/41dm8JM Read about CodeCatalyst - https://go.aws/41aWmWK Read the documentation - https://go.aws/3HITtWm Smart Business Day: https://go.aws/3Ly6y5Q
AWS Morning Brief for the week of May 8, 2023 with Corey Quinn. Links: Announcing Provisioned Capacity for Amazon Athena Amazon EFS Replication is now available in all AWS Regions Amazon Redshift launches ra3.xlplus instances in additional Middle East, Europe and Asia Pacific Regions AWS Compute Optimizer now supports filtering by tags AWS Console Mobile Application launches push notifications Announcing AWS User Notifications general availability Process price transparency data using AWS Glue Patterns for building an API to upload files to Amazon S3 Improve query performance and reduce cost using scheduled queries in Amazon Timestream Working with JSON data in Amazon DynamoDB The history and future roadmap of the AWS CloudFormation Registry Partnerships extend Just Walk Out technology to more colleges and universities Quickly build high-accuracy Generative AI applications on enterprise data using Amazon Kendra, LangChain, and large language models Introducing AWS Verified Access – General Availability
Eswar Bala, Director of Amazon EKS at AWS, joins Corey on Screaming in the Cloud to discuss how and why AWS built a Kubernetes solution, and what customers are looking for out of Amazon EKS. Eswar reveals the concerns he sees from customers about the cost of Kubernetes, as well as the reasons customers adopt EKS over ECS. Eswar gives his reasoning on why he feels Kubernetes is here to stay and not just hype, as well as how AWS is working to reduce the complexity of Kubernetes. Corey and Eswar also explore the competitive landscape of Amazon EKS, and the new product offering from Amazon called Karpenter.About EswarEswar Bala is a Director of Engineering at Amazon and is responsible for Engineering, Operations, and Product strategy for Amazon Elastic Kubernetes Service (EKS). Eswar leads the Amazon EKS and EKS Anywhere teams that build, operate, and contribute to the services customers and partners use to deploy and operate Kubernetes and Kubernetes applications securely and at scale. With a 20+ year career in software , spanning multimedia, networking and container domains, he has built greenfield teams and launched new products multiple times.Links Referenced: Amazon EKS: https://aws.amazon.com/eks/ kubernetesthemuchharderway.com: https://kubernetesthemuchharderway.com kubernetestheeasyway.com: https://kubernetestheeasyway.com EKS documentation: https://docs.aws.amazon.com/eks/ EKS newsletter: https://eks.news/ EKS GitHub: https://github.com/aws/eks-distro 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: It's easy to **BEEP** up on AWS. Especially when you're managing your cloud environment on your own!Mission Cloud un **BEEP**s your apps and servers. Whatever you need in AWS, we can do it. Head to missioncloud.com for the AWS expertise you need. Corey: Welcome to Screaming in the Cloud, I'm Corey Quinn. Today's promoted guest episode is brought to us by our friends at Amazon. Now, Amazon is many things: they sell underpants, they sell books, they sell books about underpants, and underpants featuring pictures of books, but they also have a minor cloud computing problem. In fact, some people would call them a cloud computing company with a gift shop that's attached. Now, the problem with wanting to work at a cloud company is that their interviews are super challenging to pass.If you want to work there, but can't pass the technical interview for a long time, the way to solve that has been, “Ah, we're going to run Kubernetes so we get to LARP as if we worked at a cloud company but don't.” Eswar Bala is the Director of Engineering for Amazon EKS and is going to basically suffer my slings and arrows about one of the most complicated, and I would say overwrought, best practices that we're seeing industry-wide. Eswar, thank you for agreeing to subject yourself to this nonsense.Eswar: Hey, Corey, thanks for having me here.Corey: [laugh]. So, I'm a little bit unfair to Kubernetes because I wanted to make fun of it and ignore it. But then I started seeing it in every company that I deal with in one form or another. So yes, I can still sit here and shake my fist at the tide, but it's turned into, “Old Man Yells at Cloud,” which I'm thrilled to embrace, but everyone's using it. So, EKS has recently crossed, I believe, the five-year mark since it was initially launched. What is EKS other than Amazon's own flavor of Kubernetes?Eswar: You know, the best way I can define EKS is, EKS is just Kubernetes. Not Amazon's version of Kubernetes. It's just Kubernetes that we get from the community and offer it to customers to make it easier for them to consume. So, EKS. I've been with EKS from the very beginning when we thought about offering a managed Kubernetes service in 2017.And at that point, the goal was to bring Kubernetes to enterprise customers. So, we have many customers telling us that they want us to make their life easier by offering a managed version of Kubernetes that they've actually beginning to [erupt 00:02:42] at that time period, right? So, my goal was to figure it out, what does that service look like and which customer base should be targeting service towards.Corey: Kelsey Hightower has a fantastic learning tool out there in a GitHub repo called, “Kubernetes the Hard Way,” where he talks you through building the entire thing, start to finish. I wound up forking it and doing that on top of AWS, and you can find that at kubernetesthemuchharderway.com. And that was fun.And I went through the process and my response at the end was, “Why on earth would anyone ever do this more than once?” And we got that sorted out, but now it's—customers aren't really running these things from scratch. It's like the Linux from Scratch project. Great learning tool; probably don't run this in production in the same way that you might otherwise because there are better ways to solve for the problems that you will have to solve yourself when you're building these things from scratch. So, as I look across the ecosystem, it feels like EKS stands in the place of the heavy, undifferentiated lifting of running the Kubernetes control plane so customers functionally don't have to. Is that an effective summation of this?Eswar: That is precisely right. And I'm glad you mentioned, “Kubernetes the Hard Way,” I'm a big fan of that when it came out. And if anyone who did that tutorial, and also your tutorial, “Kubernetes the Harder Way,” would walk away thinking, “Why would I pick this technology when it's super complicated to setup?” But then you see that customers love Kubernetes and you see that reflected in the adoption, even in 2016, 2017 timeframes.And the reason is, it made life easier for application developers in terms of offering web services that they wanted to offer to their customer base. And because of all the features that Kubernetes brought on, application lifecycle management, service discoveries, and then it evolved to support various application architectures, right, in terms of stateless services, stateful applications, and even daemon sets, right, like for running your logging and metrics agents. And these are powerful features, at the end of the day, and that's what drove Kubernetes. And because it's super hard to get going to begin with and then to operate, the day-two operator experience is super complicated.Corey: And the day one experience is super hard and the day two experience of, “Okay, now I'm running it and something isn't working the way it used to. Where do I start,” has been just tremendously overwrought. And frankly, more than a little intimidating.Eswar: Exactly. Right? And that exactly was our opportunity when we started in 2017. And when we started, there was question on, okay, should we really build a service when you have an existing service like ECS in place? And by the way, like, I did work in ECS before I started working in EKS from the beginning.So, the answer then was, it was about giving what customers want. And their space for many container orchestration systems, right, ECS was the AWS service at that point in time. And our thinking was, how do we give customers what they wanted? They wanted a Kubernetes solution. Let's go build that. But we built it in a way that we remove the undifferentiated heavy lifting of managing Kubernetes.Corey: One of the weird things that I find is that everyone's using Kubernetes, but I don't see it in the way that I contextualize the AWS universe, which of course, is on the bill. That's right. If you don't charge for something in AWS Lambda, and preferably a fair bit, I don't tend to know it exists. Like, “What's an IAM and what might that possibly do?” Always have reassuring thing to hear from someone who's often called an expert in this space. But you know, if it doesn't cost money, why do I pay attention to it?The control plane is what EKS charges for, unless you're running a bunch of Fargate-managed pods and containers to wind up handling those things. So, it mostly just shows up as an addenda to the actual big, meaty portions of the belt. It just looks like a bunch of EC2 instances with some really weird behavior patterns, particularly with regard to auto-scaling and crosstalk between all of those various nodes. So, it's a little bit of a murder mystery, figuring out, “So, what's going on in this environment? Do you folks use containers at all?” And the entire Kubernetes shop is looking at me like, “Are you simple?”No, it's just I tend to disregard the lies that customers say, mostly to themselves because everyone has this idea of what's going on in their environment, but the bill speaks. It's always been a little bit of an investigation to get to the bottom of anything that involves Kubernetes at significant points of scale.Eswar: Yeah, you're right. Like if you look at EKS, right, like, we started with managing the control plane to begin with. And managing the control plane is a drop in the bucket when you actually look at the costs in terms of operating a Kubernetes cluster or running a Kubernetes cluster. When you look at how our customers use and where they spend most of their cost, it's about where their applications run; it's actually the Kubernetes data plane and the amount of compute and memory that the applications end of using end up driving 90% of the cost. And beyond that is the storage, beyond that as a networking costs, right, and then after that is the actual control plane costs. So, the problem right now is figuring out, how do we optimize our costs for the application to run on?Corey: On some level, it requires a little bit of understanding of what's going on under the hood. There have been a number of cost optimization efforts that have been made in the Kubernetes space, but they tend to focus around stuff that I find relatively, well, I call it banal because it basically is. You're looking at the idea of, okay, what size instances should you be running, and how well can you fill them and make sure that all the resources per node wind up being taken advantage of? But that's also something that, I guess from my perspective, isn't really the interesting architectural point of view. Whether or not you're running a bunch of small instances or a few big ones or some combination of the two, that doesn't really move the needle on any architectural shift, whereas ingesting a petabyte a month of data and passing 50 petabytes back and forth between availability zones, that's where it starts to get really interesting as far as tracking that stuff down.But what I don't see is a whole lot of energy or effort being put into that. And I mean, industry-wide, to be clear. I'm not attempting to call out Amazon specifically on this. That's [laugh] not the direction I'm taking this in. For once. I know, I'm still me. But it seems to be just an industry-wide issue, where zone affinity for Kubernetes has been a very low priority item, even on project roadmaps on the Kubernetes project.Eswar: Yeah, the Kubernetes does provide ability for customers to restrict their workloads within as particular [unintelligible 00:09:20], right? Like, there is constraints that you can place on your pod specs that end up driving applications towards a particular AZ if they want, right? You're right, it's still left to the customers to configure. Just because there's a configuration available doesn't mean the customers use it. If it's not defaulted, most of the time, it's not picked up.That's where it's important for service providers—like EKS—to offer ability to not only provide the visibility by means of reporting that it's available using tools like [Cue Cards 00:09:50] and Amazon Billing Explorer but also provide insights and recommendations on what customers can do. I agree that there's a gap today. For example in EKS, in terms of that. Like, we're slowly closing that gap and it's something that we're actively exploring. How do we provide insights across all the resources customers end up using from within a cluster? That includes not just compute and memory, but also storage and networking, right? And that's where we are actually moving towards at this point.Corey: That's part of the weird problem I've found is that, on some level, you get to play almost data center archaeologists when you start exploring what's going on in these environments. I found one of the only reliable ways to get answers to some of this stuff has been oral tradition of, “Okay, this Kubernetes cluster just starts hurling massive data quantities at 3 a.m. every day. What's causing that?” And it leads to, “Oh, no no, have you talked to the data science team,” like, “Oh, you have a data science team. A common AWS billing mistake.” And exploring down that particular path sometimes pays dividends. But there's no holistic way to solve that globally. Today. I'm optimistic about tomorrow, though.Eswar: Correct. And that's where we are spending our efforts right now. For example, we recently launched our partnership with Cue Cards, and Cue Cards is now available as an add-on from the Marketplace that you can easily install and provision on Kubernetes EKS clusters, for example. And that is a start. And Cue Cards is amazing in terms of features, in terms of insight it offers, right, it looking into computer, the memory, and the optimizations and insights it provides you.And we are also working with the AWS Cost and Usage Reporting team to provide a native AWS solution for the cost reporting and the insights aspect as well in EKS. And it's something that we are going to be working really closely to solve the networking gaps in the near future.Corey: What are you seeing as far as customer concerns go, with regard to cost and Kubernetes? I see some things, but let's be very clear here, I have a certain subset of the market that I spend an inordinate amount of time speaking to and I always worry that what I'm seeing is not holistically what's going on in the broader market. What are you seeing customers concerned about?Eswar: Well, let's start from the fundamentals here, right? Customers really want to get to market faster, whatever services and applications that they want to offer. And they want to have it cheaper to operate. And if they're adopting EKS, they want it cheaper to operate in Kubernetes in the cloud. They also want a high performance, they also want scalability, and they want security and isolation.There's so many parameters that they have to deal with before they put their service on the market and continue to operate. And there's a fundamental tension here, right? Like they want cost efficiency, but they also want to be available in the market quicker and they want performance and availability. Developers have uptime, SLOs, and SLAs is to consider and they want the maximum possible resources that they want. And on the other side, you've got financial leaders and the business leaders who want to look at the spending and worry about, like, okay, are we allocating our capital wisely? And are we allocating where it makes sense? And are we doing it in a manner that there's very little wastage and aligned with our customer use, for example? And this is where the actual problems arise from [unintelligible 00:13:00].Corey: I want to be very clear that for a long time, one of the most expensive parts about running Kubernetes has not been the infrastructure itself. It's been the people to run this responsibly, where it's the day two, day three experience where for an awful lot of companies like, oh, we're moving to Kubernetes because I don't know we read it in an in-flight magazine or something and all the cool kids are doing it, which honestly during the pandemic is why suddenly everyone started making better IT choices because they're execs were not being exposed to airport ads. I digress. The point, though, is that as customers are figuring this stuff out and playing around with it, it's not sustainable that every company that wants to run Kubernetes can afford a crack SRE team that is individually incredibly expensive and collectively staggeringly so. That it seems to be the real cost is the complexity tied to it.And EKS has been great in that it abstracts an awful lot of the control plane complexity away. But I still can't shake the feeling that running Kubernetes is mind-bogglingly complicated. Please argue with me and tell me I'm wrong.Eswar: No, you're right. It's still complicated. And it's a journey towards reducing the complexity. When we launched EKS, we launched only with managing the control plane to begin with. And that's where we started, but customers had the complexity of managing the worker nodes.And then we evolved to manage the Kubernetes worker nodes in terms two products: we've got Managed Node Groups and Fargate. And then customers moved on to installing more agents in their clusters before they actually installed their business applications, things like Cluster Autoscaler, things like Metric Server, critical components that they have come to rely on, but doesn't drive their business logic directly. They are supporting aspects of driving core business logic.And that's how we evolved into managing the add-ons to make life easier for our customers. And it's a journey where we continue to reduce the complexity of making it easier for customers to adopt Kubernetes. And once you cross that chasm—and we are still trying to cross it—once you cross it, you have the problem of, okay so, adopting Kubernetes is easy. Now, we have to operate it, right, which means that we need to provide better reporting tools, not just for costs, but also for operations. Like, how easy it is for customers to get to the application level metrics and how easy it is for customers to troubleshoot issues, how easy for customers to actually upgrade to newer versions of Kubernetes. All of these challenges come out beyond day one, right? And those are initiatives that we have in flight to make it easier for customers [unintelligible 00:15:39].Corey: So, one of the things I see when I start going deep into the Kubernetes ecosystem is, well, Kubernetes will go ahead and run the containers for me, but now I need to know what's going on in various areas around it. One of the big booms in the observability space, in many cases, has come from the fact that you now need to diagnose something in a container you can't log into and incidentally stopped existing 20 minutes for you got the alert about the issue, so you'd better hope your telemetry is up to snuff. Now, yes, that does act as a bit of a complexity burden, but on the other side of it, we don't have to worry about things like failed hard drives taking systems down anymore. That has successfully been abstracted away by Kubernetes, or you know, your cloud provider, but that's neither here nor there these days. What are you seeing as far as, effectively, the sidecar pattern, for example of, “Oh, you have too many containers and need to manage them? Have you considered running more containers?” Sounds like something a container salesman might say.Eswar: So, running containers demands that you have really solid observability tooling, things that you're able to troubleshoot—successfully—debug without the need to log into the containers itself. In fact, that's an anti-pattern, right? You really don't want a container to have the ability to SSH into a particular container, for example. And to be successful at it demands that you publish your metrics and you publish your logs. All of these are things that a developer needs to worry about today in order to adopt containers, for example.And it's on the service providers to actually make it easier for the developers not to worry about these. And all of these are available automatically when you adopt a Kubernetes service. For example, in EKS, we are working with our managed Prometheus service teams inside Amazon, right—and also CloudWatch teams—to easily enable metrics and logging for customers without having to do a lot of heavy lifting.Corey: Let's talk a little bit about the competitive landscape here. One of my biggest competitors in optimizing AWS bills is Microsoft Excel, specifically, people are going to go ahead and run it themselves because, “Eh, hiring someone who's really good at this, that sounds expensive. We can screw it up for half the cost.” Which is great. It seems to me that one of your biggest competitors is people running their own control plane, on some level.I don't tend to accept the narrative that, “Oh, EKS is expensive that winds up being what 35 bucks or 70 bucks or whatever it is per control plane per cluster on a monthly basis.” Okay, yes, that's expensive if you're trying to stay completely within a free tier perhaps, but if you're running anything that's even slightly revenue-generating or a for-profit company, you will spend far more than that just on people's time. I have no problems—for once—with the EKS pricing model, start to finish. Good work on that. You've successfully nailed it. But are you seeing significant pushback from the industry of, “Nope, we're going to run our own Kubernetes management system instead because we enjoy pain, corporately speaking.”Eswar: Actually, we are in a good spot there, right? Like, at this point, customers who choose to run Kubernetes on AWS by themselves and not adopt EKS just fall into one main category, so—or two main categories: number one, they have existing technical stack built on running Kubernetes on themselves and they'd rather maintain that and not moving to EKS. Or they demand certain custom configurations of the Kubernetes control plane that EKS doesn't support. And those are the only two reasons why we see customers not moving into EKS and prefer to run their own Kubernetes on AWS clusters.[midroll 00:19:46]Corey: It really does seem, on some level, like there's going to be a… I don't want to say reckoning because that makes it sound vaguely ominous and that's not the direction that I intend for things to go in, but there has to be some form of collapsing of the complexity that is inherent to all of this because the entire industry has always done that. An analogy that I fall back on because I've seen this enough times to have the scars to show for it is that in the '90s, running a web server took about a week of spare time and an in-depth knowledge of GCC compiler flags. And then it evolved to ah, I could just unzip a tarball of precompiled stuff, and then RPM or Deb became a thing. And then Yum, or something else, or I guess apt over in the Debian land to wind up wrapping around that. And then you had things like Puppet where it was it was ensure installed. And now it's Docker Run.And today, it's a checkbox in the S3 console that proceeds to yell at you because you're making a website public. But that's neither here nor there. Things don't get harder with time. But I've been surprised by how I haven't yet seen that sort of geometric complexity collapsing of around Kubernetes to make it easier to work with. Is that coming or are we going to have to wait for the next cycle of things?Eswar: Let me think. I actually don't have a good answer to that, Corey.Corey: That's good, at least because if you did, I'd worried that I was just missing something obvious. That's kind of the entire reason I ask. Like, “Oh, good. I get to talk to smart people and see what they're picking up on that I'm absolutely missing.” I was hoping you had an answer, but I guess it's cold comfort that you don't have one off the top of your head. But man, is it confusing.Eswar: Yeah. So, there are some discussions in the community out there, right? Like, it's Kubernetes the right layer to do interact? And there are some tooling that's built on top of Kubernetes, for example, Knative that tries to provide a serverless layer on top of Kubernetes, for example. There are also attempts at abstracting Kubernetes completely and providing tooling that just completely removes any sort of Kubernetes API out of the picture and maybe a specific CI/CD-based solution that takes it from the source and deploys the service without even showing you that there's Kubernetes underneath, right?All of these are evolutions that are being tested out there in the community. Time will tell whether these end up sticking. But what's clear here is the gravity around Kubernetes. All sorts of tooling that gets built on top of Kubernetes, all the operators, all sorts of open-source initiatives that are built to run on Kubernetes. For example, Spark, for example, Cassandra, so many of these big, large-scale, open-source solutions are now built to run really well on Kubernetes. And that is the gravity that's pushing Kubernetes at this point.Corey: I'm curious to get your take on one other, I would consider interestingly competitive spaces. Now, because I have a domain problem, if you go to kubernetestheeasyway.com, you'll wind up on the ECS marketing page. That's right, the worst competition in the world: the people who work down the hall from you.If someone's considering using ECS, Elastic Container Service versus EKS, Elastic Kubernetes Service, what is the deciding factor when a customer's making that determination? And to be clear, I'm not convinced there's a right or wrong answer. But I am curious to get your take, given that you have a vested interest, but also presumably don't want to talk complete smack about your colleagues. But feel free to surprise me.Eswar: Hey, I love ECS, by the way. Like I said, I started my life in the AWS in ECS. So look, ECS is a hugely successful container orchestration service. I know we talk a lot about Kubernetes, I know there's a lot of discussions around Kubernetes, but I wouldn't make it a point that, like, ECS is a hugely successful service. Now, what determines how customers go to?If customers are… if the customers tech stack is entirely on AWS, right, they use a lot of AWS services and they want an easy way to get started in the container world that has really tight integration with other AWS services without them having to configure a lot, ECS is the way, right? And customers have actually seen terrific success adopting ECS for that particular use case. Whereas EKS customers, they start with, “Okay, I want an open-source solution. I really love Kubernetes. I lo—or, I have a tooling that I really like in the open-source land that really works well with Kubernetes. I'm going to go that way.” And those kind of customers end up picking EKS.Corey: I feel like, on some level, Kubernetes has become the most the default API across a wide variety of environments. AWS obviously, but on-prem other providers. It seems like even the traditional VPS companies out there that offer just rent-a-server in the cloud somewhere are all also offering, “Oh, and we have a Kubernetes service as well.” I wound up backing a Kickstarter project that runs a Kubernetes cluster with a shared backplane across a variety of Raspberries Pi, for example. And it seems to be almost everywhere you look.Do you think that there's some validity to that approach of effectively whatever it is that we're going to wind up running in the future, it's going to be done on top of Kubernetes or do you think that that's mostly hype-driven these days?Eswar: It's definitely not hype. Like we see the proof in the kind of adoption we see. It's becoming the de facto container orchestration API. And with all the tooling, open-source tooling that's continuing to build on top of Kubernetes, CNCF tooling ecosystem that's actually spawned to actually support Kubernetes at option, all of this is solid proof that Kubernetes is here to stay and is a really strong, powerful API for customers to adopt.Corey: So, four years ago, I had a prediction on Twitter, and I said, “In five years, nobody will care about Kubernetes.” And it was in February, I believe, and every year, I wind up updating an incrementing a link to it, like, “Four years to go,” “Three years to go,” and I believe it expires next year. And I have to say, I didn't really expect when I made that prediction for it to outlive Twitter, but yet, here we are, which is neither here nor there. But I'm curious to get your take on this. But before I wind up just letting you savage the naive interpretation of that, my impression has been that it will not be that Kubernetes has gone away. That is ridiculous. It is clearly in enough places that even if they decided to rip it out now, it would take them ten years, but rather than it's going to slip below the surface level of awareness.Once upon a time, there was a whole bunch of energy and drama and debate around the Linux virtual memory management subsystem. And today, there's, like, a dozen people on the planet who really have to care about that, but for the rest of us, it doesn't matter anymore. We are so far past having to care about that having any meaningful impact in our day-to-day work that it's just, it's the part of the iceberg that's below the waterline. I think that's where Kubernetes is heading. Do you agree or disagree? And what do you think about the timeline?Eswar: I agree with you; that's a perfect analogy. It's going to go the way of Linux, right? It's here to stay; it just going to get abstracted out if any of the abstraction efforts are going to stick around. And that's where we're testing the waters there. There are many, many open-source initiatives there trying to abstract Kubernetes. All of these are yet to gain ground, but there's some reasonable efforts being made.And if they are successful, they just end up being a layer on top of Kubernetes. Many of the customers, many of the developers, don't have to worry about Kubernetes at that point, but a certain subset of us in the tech world will need to do a deal with Kubernetes, and most likely teams like mine that end up managing and operating their Kubernetes clusters.Corey: So, one last question I have for you is that if there's one thing that AWS loves, it's misspelling things. And you have an open-source offering called Karpenter spelled with a K that is an extending of that tradition. What does Karpenter do and why would someone use it?Eswar: Thank you for that. Karpenter is one of my favorite launches in the last one year.Corey: Presumably because you're terrible at the spelling bee back when you were a kid. But please tell me more.Eswar: [laugh]. So Karpenter, is an open-source flexible and high performance cluster auto-scaling solution. So basically, when your cluster needs more capacity to support your workloads, Karpenter automatically scales the capacity as needed. For people that know the Kubernetes space well, there's an existing component called Cluster Autoscaler that fills this space today. And it's our take on okay, so what if we could reimagine the capacity management solution available in Kubernetes? And can we do something better? Especially for cases where we expect terrific performance at scale to enable cost efficiency and optimization use cases for our customers, and most importantly, provide a way for customers not to pre-plan a lot of capacity to begin with.Corey: This is something we see a lot, in the sense of very bursty workloads where, okay, you're going to steady state load. Cool. Buy a bunch of savings plans, get things set up the way you want them, and call it a day. But when it's bursty, there are challenges with it. Folks love using Spot, but in the event of a sudden capacity shortfall, the question is, is can we spin up capacity to backfill it within those two minutes that we have a warning on that on? And if the answer is no, then it becomes a bit of a non-starter.Customers have had to build an awful lot of those things around EC2 instances that handle a lot of that logic for them in ways that are tuned specifically for their use cases. I'm encouraged to see there's a Kubernetes story around this that starts to remove some of that challenge from the customer side.Eswar: Yeah. So, the burstiness is where complexity comes [here 00:29:42], right? Like many customers for steady state, they know what their capacity requirements are, they set up the capacity, they can also reason out what is the effective capacity needed for good utilization for economical reasons and they can actually pre plan that and set it up. But once burstiness comes in, which inevitably does it at [unintelligible 00:30:05] applications, customers worry about, “Okay, am I going to get the capacity that I need in time that I need to be able to service my customers? And am I confident at it?”If I'm not confident, I'm going to actually allocate capacity beforehand, assuming that I'm going to actually get the burst that I needed. Which means, you're paying for resources that you're not using at the moment. And the burstiness might happen and then you're on the hook to actually reduce the capacity for it once the peak subsides at the end of the [day 00:30:36]. And this is a challenging situation. And this is one of the use cases that we targeted Karpenter towards.Corey: I find that the idea that you're open-sourcing this is fascinating because of two reasons. One, it does show a willingness to engage with the community that… again, it's difficult. When you're a big company, people love to wind up taking issue with almost anything that you do. But for another, it also puts it out in the open, on some level, where, especially when you're talking about cost optimization and decisions that affect cost, it's all out in public. So, people can look at this and think, “Wait a minute, it's not—what is this line of code that means if it's toward the end of the month, crank it up because we might need to hit our numbers.” Like, there's nothing like that in there. At least I'm assuming. I'm trusting that other people have read this code because honestly, that seems like a job for people who are better at that than I am. But that does tend to breed a certain element of trust.Eswar: Right. It's one of the first things that we thought about when we said okay, so we have some ideas here to actually improve the capacity management solution for Kubernetes. Okay, should we do it out in the open? And the answer was a resounding yes, right? I think there's a good story here that actually enables not just AWS to offer these ideas out there, right, and we want to bring it to all sorts of Kubernetes customers.And one of the first things we did is to architecturally figure out all the core business logic of Karpenter, which is, okay, how to schedule better, how quickly to scale, what is the best instance types to pick for this workload. All of that business logic was abstracted out from the actual cloud provider implementation. And the cloud provider implementation is super simple. It's just creating instances, deleting instances, and describing instances. And it's something that we bake from the get-go so it's easier for other cloud providers to come in and to add their support to it. And we as a community actually can take these ideas forward in a much faster way than just AWS doing it.Corey: I really want to thank you for taking the time to speak with me today about all these things. If people want to learn more, where's the best place for them to find you?Eswar: The best place to learn about EKS, right, as EKS evolves, is using our documentation, we have an EKS newsletter that you can go subscribe, and you can also find us on GitHub where we share our product roadmap. So, it's a great places to learn about how EKS is evolving and also sharing your feedback.Corey: Which is always great to hear, as opposed to, you know, in the AWS Console, where we live, waiting for you to stumble upon us, which, yeah. No it's good does have a lot of different places for people to engage with you. And we'll put links to that, of course, in the [show notes 00:33:17]. Thank you so much for being so generous with your time. I appreciate it.Eswar: Corey, really appreciate you having me.Corey: Eswar Bala, Director of Engineering for Amazon EKS. 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 telling me why, when it comes to tracking Kubernetes costs, Microsoft Excel is in fact the superior experience.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.
Bret and Matt are joined by Chad Crowell of KubeSkills to walk through how you can contribute to Kubernetes open source. Chad started the kubeskills.com community and podcast to focus on learning Kubernetes by doing and in this episode, he's taking us through a detailed guide on how to get involved in the Kubernetes community.Although Kubernetes and other CNCF projects may seem big and complex with tons of activity, Chad helps us understand how the maturity of the projects and the community make it a much more pleasant onboarding experience for first-time contributors. We go through a wide range of resources and steps to help your first issue or pull request go smoothly.Live recording of this show from March 9, 2023 is on YouTube (Ep. #206).★Topics★Learning K8s by Open Source PDF slidesFirst Timers Only websiteK8s Contributor Community HomepageList of K8s SIGsK8s SlackOpen Sauced websiteK8s Contributors onboarding courseKube Cuddle podcast with Joe BedaLearning K8s Skills Support this show and get exclusive benefits on Patreon, YouTube, or bretfisher.com!★Join my Community★New live course on CI automation and gitops deploymentsBest coupons for my Docker and Kubernetes coursesChat with us and fellow students on our Discord Server DevOps FansGrab some merch at Bret's Loot BoxHomepage bretfisher.comCreators & Guests Bret Fisher - Host Cristi Cotovan - Editor Beth Fisher - Producer Matt Williams - Host Chad M. Crowell - Guest (00:00) - Intro (02:45) - Chad's Book (05:11) - Learning platforms (05:37) - Another way to learn (06:44) - SIGs (07:47) - Community or Contributor Experience SIG (10:06) - Volunteers (11:27) - For those who want to start contributing (13:50) - The different tags (14:48) - Good first issues (16:01) - Bret's first Docker fix (16:50) - Who determines the first issues? (18:37) - OpenSauced (19:16) - Finding the next steps after learning (19:59) - Dashboard to track contributions (20:42) - A very friendly community (22:30) - Who's paying for OpenSauced? (23:06) - How to build your rep on the internet (24:57) - Github Flow, Breaking it down (27:24) - Eddie Hub (28:10) - Assign yourself to the issue (28:50) - Compile Kubernetes (30:14) - Tracking the pull request lifecycle (31:44) - Changing the k8s reference issue (35:17) - Kubernetes Slack Channels (35:59) - SIG mailing lists (36:44) - Getting feedback before you do the work (38:18) - How do you give up and issue? (39:53) - Correlating issues with Slack (40:28) - Start with an issue first (41:24) - Random PRs don't go well (43:00) - Onboarding course (44:11) - Cheat sheet (44:26) - What Chad has learned from contributing (46:09) - Online resources (48:48) - Certifications and exams (50:46) - Matt's comment about a podcast (52:48) - Wrap up
Welcome to the newest episode of The Cloud Pod podcast! Justin, Ryan and Matthew are your hosts this week as we discuss all the latest news and announcements in the world of the cloud and AI - including what's new with Google Deepmind, as well as goings on over at the Finops X Conference. Join us! Titles we almost went with this week:
Prime Venture Partners Podcast
Rahul Garg Founder Moglix in conversation with with Shripati Acharya, Managing Partner Prime Venture Partners.Listen to the podcast to learn about:01:00 - B2B Commerce Needs to Transform like B2C commerce05:30 - Opportunity to Become a Disruptor Globally14:00 - Find What Customers Don't Want To Do18:00 - How B2B Marketplaces differ from B2C Marketplaces25:00 - The China Plus One Strategy & Opportunity for India31:00 - How to Evaluate a B2B Opportunity as an EntrepreneurEnjoyed the podcast? Please consider leaving a review on Apple Podcasts and subscribe wherever you are listening to this.For SaaS Startups!Prime Venture Partners and AWS have launched the 4th edition of SaaS Central, a programme designed to help accelerate the growth of early-stage SaaS startups. During the 3-day programme startups will get to interact with Unicorn founders, Investors and functional experts. So if you are a SaaS startup and want to learn from the best, apply here: bit.ly/SaaSCentral4Follow Prime Venture Partners:Twitter: https://twitter.com/Primevp_inLinkedIn: https://www.linkedin.com/company/primevp/This podcast is for you. Do let us know what you like about the podcast, what you don't like, the guests you'd like to have on the podcast and the topics you'd like us to cover in future episodes. Please share your feedback here: https://primevp.in/podcastfeedback
Last week in security news: Tailscale now offers network flow logs, Google had a GhostToken flaw, AWS reported an issue with IAM supporting multiple MFA devices, and more!Links: Tailscale now offers network flow logs Google had a GhostToken flaw that let attackers backdoor Google accounts. The folks at SADA found a major bug in Google Cloud; apparently it had the potential to expose the private keys for Google Cloud Service Accounts Issue With IAM Supporting Multiple MFA Devices This week in Tools: It's been a while since I linked to CloudMapper
This episode features an interview with Maxim Fateev, Co-founder and CEO of Temporal, an open source, distributed, and scalable workflow orchestration engine capable of running millions of workflows. He has 20 years of experience architecting mission-critical systems at Uber, Google, Amazon, and Microsoft. In this episode, Sam sits down with Maxim to discuss workflow services, the power behind Temporal, and bringing determinism to highly complex environments.-------------------“[Temporal] has this notion of workflows, which can run for a very long time and handle external events, you can treat them as a durable actor. And they're very good at implementing a lifecycle. For example, you can have an object per model and let this object handle all the events. Like, new data came in, notify this object, this object will go and retrain it. Or, it'll run an activity to superiorly check the status. So you can have end-to-end lifecycle implemented fully in Temporal.” – Maxim Fateev-------------------Episode Timestamps:(01:03): What's top of mind for Maxim in workflow services(04:09): What open source data means to Maxim(11:07): Maxim explains his time at AWS and building Cadence at Uber(23:09): Use cases and the community of Temporal(28:26): How Temporal is being used for ML workloads(32:28): One question Maxim wishes to be asked(36:38): Maxim's advice for those working with complex distributed systems(39:11): Backstage takeaways with executive producer, Audra Montenegro-------------------Links:LinkedIn - Connect with MaximTemporal.ioWatch Maxim's talk “Designing a Workflow Engine from First Principles”Replay Conference 2023
Dan and Deirdre Bosa discuss Uber earnings (1:00), Chegg crashing after its ChatGPT warning (14:00), and Amazon's AWS guide spooking investors (20:00). Later, Dan interviews Dan Niles, Founder & Portfolio Manager of the Satori Fund, and talks about his background as an internet analyst during the dot com crash (26:00), the psychology of investing (28:30), Meta (37:45), big tech valuations/Nvidia (45:30), Intel (52:30), Apple (58:00), and the broader market (1:06:00). View our show notes here Email us at firstname.lastname@example.org with any feedback, suggestions, or questions for us to answer on the pod and follow us @OkayComputerPod. We're on social: Follow Dan Nathan @RiskReversal on Twitter Follow @GuyAdami on Twitter Follow us on Instagram @RiskReversalMedia Subscribe to our YouTube page
Dan and Deirdre Bosa discuss Uber earnings (1:00), Chegg crashing after its ChatGPT warning (14:00), and Amazon's AWS guide spooking investors (20:00). Later, Dan interviews Dan Niles, Founder & Portfolio Manager of the Satori Fund, and talks about his background as an internet analyst during the dot com crash (26:00), the psychology of investing (28:30), Meta (37:45), big tech valuations/Nvidia (45:30), Intel (52:30), Apple (58:00), and the broader market (1:06:00). View our show notes here Email us at email@example.com with any feedback, suggestions, or questions for us to answer on the pod and follow us @OkayComputerPod. We're on social: Follow Dan Nathan @RiskReversal on Twitter Follow @GuyAdami on Twitter Follow us on Instagram @RiskReversalMedia Subscribe to our YouTube page
In this episode of Work in Progress, Moroni Benally of Aspire Ability and Amber Garrison Duncan of C-BEN join me to discuss the just-announced workforce initiative, the Navajo Nation Talent Marketplace, which will be the first-ever repository of all jobs available on the Navajo reservation and the skills needed to fill them. The Navajo Nation covers a lot of territory – nearly 27,000 square miles in Arizona, New Mexico, and Utah. There are 253,124 enrolled tribal members with 168,000 individuals (66%) living there on the land. Nearly 36% of Navajo households live below the federal poverty line, and "unemployment and poverty fuel an ongoing pattern of migration and brain drain that undermines the viability of the Navajo Nation," according to the news release announcing the new online Talent Marketplace. The two-year initiative is designed to address longstanding structural barriers to employment and economic growth on the reservation. "Having an online, publicly available resource linking jobs and education programs will match people to the full range of opportunities across the reservation," says Moroni Benally, a member of the Navajo Nation and head of public policy and partnerships at Aspire Ability. "It's a critical step in our nation's long-term efforts to offer all Navajo – from our 3,500 yearly high school graduates to those who moved away – access to credentials that tie to well paid jobs within the nation." Benally says, "A necessary first step for the whole Talent Marketplace is understanding what jobs are out there in the Navajo Nation already. We hear a lot of entrenched tropes about Indian country because no one has put forth the effort to actually identify the jobs." "So, up to about a year ago, we were operating under the assumption that the Navajo Nation was only creating about a 100 to 200 jobs a year. But we found 2,100 available vacant jobs in the private sector in the Navajo Nation. There's another 2,000 that are in the public sector, government jobs," Benally explains. Duncan adds, "The focus of the project is to make sure people know that there are jobs at home, to know that there is quality education available on the reservation. A lot of times what we are hearing is that people thought they had to leave the reservation to find education and work." This is an important starting point, she says. Knowing what jobs are available on the reservation clarifies for nearby competency-based learning institutions how they might realign their curriculum to serve the community. "The first thing we're doing is working with the colleges to bring the job board to them, to bring those discreet knowledge, skills, abilities, things that people will have to know and be able to do to perform those jobs." Benally says right now there are jobs in health care, construction, and education, but the type of jobs will grow exponentially as broadband is further implemented throughout the Navajo Nation. Duncan agrees, saying that people will be able to learn the skills needed for remote jobs in cybersecurity and IT. "There are also opportunities to think about Salesforce and Google and AWS, all of those components of 'now I can live at home and perform those jobs.' It also opens the door for online learning." "We want to be able to provide a space to bring our people back home to really build a Nation and to fulfill that mandate that our elders gave us...of coming home and bringing the goodness that you have," Benally explains. You learn more about how Aspire Ability and C-BEN plan to roll out the plan in the podcast. Listen here, or download and listen wherever you get your podcasts. Episode 270: Moroni Benally, Aspire Ability, and Amber Garrison Duncan, C-BENHost & Executive Producer: Ramona Schindelheim, Editor-in-Chief, WorkingNationProducer: Larry BuhlExecutive Producers: Joan Lynch and Melissa PanzerTheme Music: Composed by Lee Rosevere and licensed under CC by 4.
In this month's edition of Weld Wednesday with AWS, I am chatting with Paisley Cameron, Shanen Aranmor and Dr. Rick Polanin. Join us as we discuss the importance of being a life long learner and how you can stay up to date in the welding industry as technology continues to evolve. Resources in this episode: AWS Conferences: https://aws.org/events/conferences Weld-ED: https://www.weld-ed.org/ Nickel Institute: https://nickelinstitute.org/ Project MFG: https://www.projectmfg.com/