Podcasts about aws step functions

An airhacks.fm conversation with Colt McNealy (@coltmcnealy) about: first computing experience with Sun workstations and network computing, background in hockey and other sports, using system76 Linux laptops for development, starting programming in high school with Java and later learning C, fortran, assembly, C++ and python, working at a real estate company with kubernetes and Kafka, the genesis of LittleHorse from experiencing challenges with distributed microservices and workflow management, LittleHorse as an open source workflow orchestration engine using Kafka as a commit log rather than a message queue, building a custom distributed database optimized for workflow orchestration, the recent move to fully open source licensing, comparison with AWS Step Functions but with more capabilities and open source benefits, using RocksDB and Kafka Streams for the underlying implementation, performance metrics of 12-40ms latency between tasks and hundreds of tasks per second, the multi-tenant architecture allowing for serverless offerings, integration with Kafka for event-driven architectures, the distinction between orchestration and choreography in distributed systems, using Java 21 with benefits from virtual threads and generational garbage collection, plans for Java 25 adoption, the naming story behind "Little Horse" and its competition with MuleSoft, the Sun Microsystems legacy and innovation culture, recent adoption of Quarkus for some components, the "Know Your Customer" flow as the Hello World example for Little Horse, the importance of observability and durability in workflow management, plans for serverless offerings and multi-tenant architecture, the balance between open source core and commercial offerings Colt McNealy on twitter: @coltmcnealy

In this episode, we provide an overview of AWS Step Functions and dive deep into the powerful new JSONata and variables features. We explain how JSONata allows complex JSON transformations without custom Lambda functions, enabling more serverless workflows. The variables feature also helps avoid the previous 256KB state size limit. We share examples from real projects showing how these features simplify workflows, reduce costs and enable new use cases.AWS Bites is brought to you in association with fourTheorem. If you need a friendly partner to support you and work with you to de-risk any AWS migration or development project, check them out at ⁠⁠fourtheorem.com⁠⁠In this episode, we mentioned the following resources:JSONata and variables official launch post: https://aws.amazon.com/blogs/compute/simplifying-developer-experience-with-variables-and-jsonata-in-aws-step-functions/JSONata exerciser: https://try.jsonata.org/Stedi JSONata playground: https://www.stedi.com/jsonata/playgroundEpisode 103: Building GenAI Features with Bedrock https://awsbites.com/103-building-genai-features-with-bedrock/Episode 63: How to automate transcripts with Amazon Transcribe and OpenAI Whisper https://awsbites.com/63-how-to-automate-transcripts-with-amazon-transcribe-and-openai-whisper/ Do you have any AWS questions you would like us to address?Leave a comment here or connect with us on X/Twitter, BlueSky or LinkedIn:- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/eoins⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠https://bsky.app/profile/eoin.sh⁠ | ⁠https://www.linkedin.com/in/eoins/⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/loige⁠⁠⁠⁠⁠ | ⁠https://bsky.app/profile/loige.co⁠ | ⁠https://www.linkedin.com/in/lucianomammino/

The free livestreams for AI Engineer Summit are now up! Please hit the bell to help us appease the algo gods. We're also announcing a special Online Track later today.Today's Deep Research episode is our last in our series of AIE Summit preview podcasts - thanks for following along with our OpenAI, Portkey, Pydantic, Bee, and Bret Taylor episodes, and we hope you enjoy the Summit! Catch you on livestream.Everybody's going deep now. Deep Work. Deep Learning. DeepMind. If 2025 is the Year of Agents, then the 2020s are the Decade of Deep.While “LLM-powered Search” is as old as Perplexity and SearchGPT, and open source projects like GPTResearcher and clones like OpenDeepResearch exist, the difference with “Deep Research” products is they are both “agentic” (loosely meaning that an LLM decides the next step in a workflow, usually involving tools) and bundling custom-tuned frontier models (custom tuned o3 and Gemini 1.5 Flash).The reception to OpenAI's Deep Research agent has been nothing short of breathless:"Deep Research is the best public-facing AI product Google has ever released. It's like having a college-educated researcher in your pocket." - Jason Calacanis“I have had [Deep Research] write a number of ten-page papers for me, each of them outstanding. I think of the quality as comparable to having a good PhD-level research assistant, and sending that person away with a task for a week or two, or maybe more. Except Deep Research does the work in five or six minutes.” - Tyler Cowen“Deep Research is one of the best bargains in technology.” - Ben Thompson“my very approximate vibe is that it can do a single-digit percentage of all economically valuable tasks in the world, which is a wild milestone.” - sama“Using Deep Research over the past few weeks has been my own personal AGI moment. It takes 10 mins to generate accurate and thorough competitive and market research (with sources) that previously used to take me at least 3 hours.” - OAI employee“It's like a bazooka for the curious mind” - Dan Shipper“Deep research can be seen as a new interface for the internet, in addition to being an incredible agent… This paradigm will be so powerful that in the future, navigating the internet manually via a browser will be "old-school", like performing arithmetic calculations by hand.” - Jason Wei“One notable characteristic of Deep Research is its extreme patience. I think this is rapidly approaching “superhuman patience”. One realization working on this project was that intelligence and patience go really well together.” - HyungWon“I asked it to write a reference Interaction Calculus evaluator in Haskell. A few exchanges later, it gave me a complete file, including a parser, an evaluator, O(1) interactions and everything. The file compiled, and worked on my test inputs. There are some minor issues, but it is mostly correct. So, in about 30 minutes, o3 performed a job that would take me a day or so.” - Victor Taelin“Can confirm OpenAI Deep Research is quite strong. In a few minutes it did what used to take a dozen hours. The implications to knowledge work is going to be quite profound when you just ask an AI Agent to perform full tasks for you and come back with a finished result.” - Aaron Levie“Deep Research is genuinely useful” - Gary MarcusWith the advent of “Deep Research” agents, we are now routinely asking models to go through 100+ websites and generate in-depth reports on any topic. The Deep Research revolution has hit the AI scene in the last 2 weeks: * Dec 11th: Gemini Deep Research (today's guest!) rolls out with Gemini Advanced* Feb 2nd: OpenAI releases Deep Research* Feb 3rd: a dozen “Open Deep Research” clones launch* Feb 5th: Gemini 2.0 Flash GA* Feb 15th: Perplexity launches Deep Research * Feb 17th: xAI launches Deep SearchIn today's episode, we welcome Aarush Selvan and Mukund Sridhar, the lead PM and tech lead for Gemini Deep Research, the originators of the entire category. We asked detailed questions from inspiration to implementation, why they had to finetune a special model for it instead of using the standard Gemini model, how to run evals for them, and how to think about the distribution of use cases. (We also have an upcoming Gemini 2 episode with our returning first guest Logan Kilpatrick so stay tuned

Topics covered in this episode: dbos-transact-py Typed Python in 2024: Well adopted, yet usability challenges persist RightTyper Lazy self-installing Python scripts with uv Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org / @mkennedy.codes (bsky) Brian: @brianokken@fosstodon.org / @brianokken.bsky.social Show: @pythonbytes@fosstodon.org / @pythonbytes.fm (bsky) Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Monday at 10am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Michael #1: dbos-transact-py DBOS Transact is a Python library providing ultra-lightweight durable execution. Durable execution means your program is resilient to any failure. If it is ever interrupted or crashes, all your workflows will automatically resume from the last completed step. Under the hood, DBOS Transact works by storing your program's execution state (which workflows are currently executing and which steps they've completed) in a Postgres database. Incredibly fast, for example 25x faster than AWS Step Functions. Brian #2: Typed Python in 2024: Well adopted, yet usability challenges persist Aaron Pollack on Engineering at Meta blog “Overall findings 88% of respondents “Always” or “Often” use Types in their Python code. IDE tooling, documentation, and catching bugs are drivers for the high adoption of types in survey responses, The usability of types and ability to express complex patterns still are challenges that leave some code unchecked. Latency in tooling and lack of types in popular libraries are limiting the effectiveness of type checkers. Inconsistency in type check implementations and poor discoverability of the documentation create friction in onboarding types into a project and seeking help when using the tools. “ Notes Seems to be a different survey than the 2023 (current) dev survey. Diff time frame and results. July 29 - Oct 8, 2024 Michael #3: RightTyper A fast and efficient type assistant for Python, including tensor shape inference Brian #4: Lazy self-installing Python scripts with uv Trey Hunner Creating your own ~/bin full of single-file command line scripts is common for *nix folks, still powerful but underutilized on Mac, and trickier but still useful on Windows. Python has been difficult in the past to use for standalone scripts if you need dependencies, but that's no longer the case with uv. Trey walks through user scripts (*nix and Mac) Using #! for scripts that don'thave dependencies Using #! with uv run --script and /// script for dependencies Discussion about how uv handles that. Extras Brian: Courses at pythontest.com If you live in a place (or are in a place in your life) where these prices are too much, let me know. I had a recent request and I really appreciate it. Michael: Python 3.14 update released Top episodes of 2024 at Talk Python Universal check for updates macOS: Settings > Keyboard > Keyboard shortcuts > App shortcuts > + Then add shortcut for single app, ^U and the menu title. Joke: Python with rizz

Integrations are becoming more critical in today's serverless environments. Host Jason Andersen is with Amazon Web Services' Justin Callison, Director, Application Integration, and Bill Boora, Principle Worldwide Specialist, Serverless, for a conversation on the role of integration in accelerating innovation, highlighted by the recent launch of Amazon EventBridge + AWS Step Functions Private API. Tune into this episode of the Six Five On The Road at AWS re:Invent as they get into all things “application modernization” and

In this pre-re:Invent 2024 episode, Luciano and Eoin discuss some of their favorite recent AWS announcements, including improvements to AWS Step Functions, Lambda runtime updates, DynamoDB price reductions, ALB header injection, Cognito enhancements, VPC public access blocking, and more. They share their thoughts on the implications of these new capabilities and look forward to seeing what else is announced at the conference. Overall, it's an exciting time for AWS developers with many new features to explore. Very important: no focus on GenAI in this episode :) AWS Bites is brought to you, as always, by fourTheorem! Sometimes, AWS is overwhelming and you might need someone to provide clear guidance in the fog of cloud offerings. That someone is fourTheorem. Check them out at ⁠fourtheorem.com⁠ In this episode, we mentioned the following resources: The repo containing the code of the AWS Bites website: https://github.com/awsbites/aws-bites-site Orama Search: https://orama.com/ JSONata in AWS Step Functions: https://aws.amazon.com/blogs/compute/simplifying-developer-experience-with-variables-and-jsonata-in-aws-step-functions/ EC2 Auto Scaling improvements: https://aws.amazon.com/about-aws/whats-new/2024/11/amazon-ec2-auto-scaling-highly-responsive-scaling-policies/ Node.js 22 is available for Lambda: https://aws.amazon.com/blogs/compute/node-js-22-runtime-now-available-in-aws-lambda/ Python 3.13 runtime: https://aws.amazon.com/blogs/compute/python-3-13-runtime-now-available-in-aws-lambda/ Aurora Serverless V2 now scales to 0: https://aws.amazon.com/about-aws/whats-new/2024/11/amazon-aurora-serverless-v2-scaling-zero-capacity/ Episode 95 covering Mountpoint for S3: https://awsbites.com/95-mounting-s3-as-a-filesystem/ One Zone caching for Mountpoint for S3: https://aws.amazon.com/about-aws/whats-new/2024/11/mountpoint-amazon-s3-high-performance-shared-cache/ Appending to S3 objects: https://docs.aws.amazon.com/AmazonS3/latest/userguide/directory-buckets-objects-append.html 1 million S3 Buckets per account: https://aws.amazon.com/about-aws/whats-new/2024/11/amazon-s3-up-1-million-buckets-per-aws-account/ DynamoDB cost reduction: https://aws.amazon.com/blogs/database/new-amazon-dynamodb-lowers-pricing-for-on-demand-throughput-and-global-tables/ ALB Headers: https://aws.amazon.com/about-aws/whats-new/2024/11/aws-application-load-balancer-header-modification-enhanced-traffic-control-security/ Cognito Managed Login: https://aws.amazon.com/blogs/aws/improve-your-app-authentication-workflow-with-new-amazon-cognito-features/ Cognito Passwordless Authentication: https://aws.amazon.com/blogs/aws/improve-your-app-authentication-workflow-with-new-amazon-cognito-features/ VPC Block Public Access: https://aws.amazon.com/blogs/networking-and-content-delivery/vpc-block-public-access/ Episode 88 where we talk about VPC Lattice: https://awsbites.com/88-what-is-vpc-lattice/ Direct integration between Lattice and ECS: https://aws.amazon.com/blogs/aws/streamline-container-application-networking-with-native-amazon-ecs-support-in-amazon-vpc-lattice/ Resource Control Policies: https://aws.amazon.com/blogs/aws/introducing-resource-control-policies-rcps-a-new-authorization-policy/ Episode 23 about EventBridge: https://awsbites.com/23-what-s-the-big-deal-with-eventbridge/ EventBridge latency improvements: https://aws.amazon.com/about-aws/whats-new/2024/11/amazon-eventbridge-improvement-latency-event-buses/ AppSync web sockets: https://aws.amazon.com/blogs/mobile/announcing-aws-appsync-events-serverless-websocket-apis/ Do you have any AWS questions you would like us to address? Leave a comment here or connect with us on X/Twitter: - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/eoins⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/loige⁠⁠⁠⁠

In this episode of the vBrownBag, Damian does a deeper dive into the Meatgrinder, showing how the different AWS services interact, how the process logs to CloudWatch, and more! 00:00 Intro 1:20 The AWS Services that power the Meatgrinder

In this episode of the vBrownBag, a host is a guest! Damian does a deep dive into the vBrownBag Meatgrinder, an event-driven automation solution built with AWS Serverless that powers the show behind the scenes. Meatgrinder uses AWS S3, Event Bridge, Step Functions, Lambda, and Cloud Watch and handles post-production automation of vBrownBag content. We'll talk about the design decisions made while architecting the solution, and lessons learned along the way. 00:00 Intro and so much banter! 10:14 We actually start talking about the topic

This interview was recorded for GOTO Unscripted.https://gotopia.techRead the full transcription of this interview hereBen Smith - Principal Developer Advocate for serverless at AWSEric Johnson - Principal Developer Advocate for Serverless at AWSRESOURCESBenhttps://twitter.com/benjamin_l_shttps://github.com/bls20AWShttps://linkedin.com/in/bensmithportfoliohttp://developeradvocate.co.ukhttps://thewebsmithsite.wordpress.comErichttps://twitter.com/edjgeekhttps://linkedin.com/in/singledigitLinkshttps://serverlessland.comhttps://serverlessland.com/workflowshttps://youtu.be/o8qAlbjX3iUhttps://youtu.be/9StQpMLC-5Qhttps://youtu.be/4YeZf3HupQAhttps://youtu.be/dzW3-Mol1yohttps://docs.aws.amazon.com/step-functions/latest/dg/workflow-studio-use.htmlhttps://robsutter.comhttps://gotoldn.com/2024-eda-aws-dayDESCRIPTIONIn this conversation, Eric Johnson and Ben Smith discuss the benefits and evolving capabilities of AWS Step Functions, emphasizing their utility in managing complex workflows involving multiple AWS services. They highlight the initial hesitation due to limitations in earlier versions but acknowledge significant improvements such as express workflows and synchronous invocation, which have made Step Functions more versatile and powerful. They delve into favorite patterns, including concurrent processing with dynamic map states and reusable workflows, underscoring the efficiency and scalability Step Functions bring to serverless architectures. [...]RECOMMENDED BOOKSAdam Bellemare • Building Event-Driven MicroservicesPeter Sbarski • Serverless Architectures on AWSMichael Stack • Event-Driven Architecture in GolangFord, Richards, Sadalage & Dehghani • Software Architecture: The Hard PartsGerardus Blokdyk • Event-Driven Architecture EDAJames Urquhart • Flow ArchitecturesTwitterInstagramLinkedInFacebookLooking for a unique learning experience?Attend the next GOTO conference near you! Get your ticket: gotopia.techSUBSCRIBE TO OUR YOUTUBE CHANNEL - new videos posted daily!

En este episodio del podcast Marcia nos comparte novedades personales y nos adentra en el mundo de la orquestación de aplicaciones con IA generativa. Desde patrones tradicionales hasta un futuro innovador, Marcia explora el papel de la IA en el diseño de modelos de orquestación, optimizando procesos y desafiando paradigmas establecidos. Veremos la integración de modelos de ML y exploraremos los desafíos y oportunidades en esta nueva era impulsada por la IA.Contenidos:01:00 Bombazo de Marcia!01:42 Las ventajas de vivir en Finlandia!07:00 Orquestación tradicional 10:32 Patrones de Orquestación15:09 Elegir tu modelo de IA16:55 Prompt Engineering 18:48 Por qué Serverless?20:08 El mundo de AWS Step Functions 28:05 Integrando Step Functions con Amazon BedRock30:15 Integrando Step Functions con Amazon S333:00 Usando Step Functions para el fine-tuning de nuestros modelos ML37:15 Validaciones Humanas en un mundo probabilístico40:26 Amazon Guardrails, poniéndole vallas al campo de la IA41:20 Amazon Agents,43:30 Amazon Knowledge Bases, nuestra fuentes de datos47:02 La seguridad en la IA48:15 Seguimos con las integraciones, nuestra app del tiempo54:40 Los desafíos de la orquestación con IA.Eventos AWSAWS Summit MadridCFP Community Day Madrid Otros AWS Summits en la agenda: Mexico City (7 Agosto), Sao Paulo (15 Agosto)Enlaces Introducción a AWS Step FunctionsAWS Step Functions Workshop Paso a PasoSeries Lambda FundamentalsMejorar la Atención al cliente con un Asistente Whatsapp✉️ Si quieren escribirnos pueden hacerlo a este correo: podcast-aws-espanol@amazon.comPodes encontrar el podcast en este link: https://aws-espanol.buzzsprout.com/O en tu plataforma de podcast favoritaMás información y tutoriales en el canal de youtube de Charlas Técnicas☆☆ NUESTRAS REDES SOCIALES ☆☆

Only a few can claim they have successfully created a Pure-Serverless architecture and only those really understand the challenges of observing real event driven architectures. Apostolis Apostolidis (also known as Toli) is one of those people and its why we invited him back to discuss all the lessons learned from his time as Head of Engineering Practices at cinch. Tune in and learn about the evoluation of Serverless observability and the challenges when observing API Gateways, Queues and Step Functions. Listen to Toli's advice on picking one observability vendor, doing your own custom instrumentation and making yourself familiar with the observability data from your managed service provider.Also go back to our previous episode to hear more from his Engineering Practices for Success and remember that the time to ask about coldstarts is over

AWS Morning Brief for the week of May 30, 2023 with Corey Quinn. Links: Bloomberg reported this week that I referred to AWS's hyped generative AI offerings that nobody I know has been able to access as vaporware Amazon Aurora PostgreSQL improves availability of read replicas  AWS Copilot announces Static Site pattern to host single-page web applications  Developing a serverless Slack app using AWS Step Functions and AWS Lambda How Broadridge used Amazon Managed Blockchain to build a private equity lifecycle management solution  Stronger together: Highlights from RSA Conference 2023 Welcome to AWS Documentation

While application modernization continues to be a top priority for organizations, building modern applications with serverless technologies can still seem like a significant lift for some developers who are unsure how to get started. In this episode, Simon is joined by Eric Johnson (Principal Developer Advocate) to talk about the upcoming AWS Serverless Innovation Day, a virtual “builders show builders how to build” event, which will cover serverless strategy, serverless demos on machine learning and generative AI and event-driven architecture, insights from AWS serverless leaders and customers, and best practices using AWS serverless technology choices, including AWS Lambda, Amazon ECS with AWS Fargate, Amazon EventBridge, AWS Step Functions and more.

On this episode of The Cloud Pod, the team discusses the AWS systems manager default enablement option for all EC2 instances in an account, different ideas from leveraging innovators plus subscription using $500 Google credits, the Azure Open Source Day, the new theme for the Oracle OCI Console, and lastly, different ways to migrate to a cloud provider. A big thanks to this week's sponsor, Foghorn Consulting, which provides full-stack cloud solutions with a focus on strategy, planning and execution for enterprises seeking to take advantage of the transformative capabilities of AWS, Google Cloud and Azure. This week's highlights

In this episode, Dave is joined by special co-host Brooke Jaimeson, and Justin Callison, General Manager AWS Step Functions. AWS Step Functions is a visual workflow service that helps developers use AWS services to build distributed applications, automate processes, orchestrate microservices, and create data and machine learning pipelines. Justin walks us through what is new in Step Functions, the Workflow Studio tool, how customers are using the service today, and the new distributed map support launched at re:Invent 2022. Justin on Twitter: https://twitter.com/justincallison Justin on LinkedIn: https://www.linkedin.com/in/justin-callison Brooke's Twitter: https://twitter.com/brooke_jamieson Brooke's TikTok: https://www.tiktok.com/@brookebytes Brooke's Instagram: https://www.instagram.com/brooke.bytes/ Brooke on LinkedIn: https://www.linkedin.com/in/brookejamieson/ [BLOG] Step Functions Distributed Map – A Serverless Solution for Large-Scale Parallel Data Processing - https://aws.amazon.com/blogs/aws/step-functions-distributed-map-a-serverless-solution-for-large-scale-parallel-data-processing [DOCS] Serverless Land - Serverless Workflows Collection - https://serverlessland.com/workflows [DOCS] Serverless Land - Distributed Map Reduce Weather Analysis Workflow - https://serverlessland.com/workflows/distributed-map-weather-anaysis [PORTAL] AWS Step Functions - https://aws.amazon.com/step-functions/ [WORKSHOP] The AWS Step Functions Workshop - https://catalog.workshops.aws/stepfunctions/en-US/ [YOUTUBE] AWS re:Invent 2022 - [NEW] Accelerate Workloads Using Parallelism with Step Functions and Lambda (API205) - https://www.youtube.com/watch?v=SG6_oy72hh4&ab_channel=AWSEvents Subscribe: Amazon Music: https://music.amazon.com/podcasts/f8bf7630-2521-4b40-be90-c46a9222c159/aws-developers-podcast Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-developers-podcast/id1574162669 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zb3VuZGNsb3VkLmNvbS91c2Vycy9zb3VuZGNsb3VkOnVzZXJzOjk5NDM2MzU0OS9zb3VuZHMucnNz Spotify: https://open.spotify.com/show/7rQjgnBvuyr18K03tnEHBI TuneIn: https://tunein.com/podcasts/Technology-Podcasts/AWS-Developers-Podcast-p1461814/ RSS Feed: https://feeds.soundcloud

We've been talking about AWS re:Invent over the last few episodes. But one thing that we haven't talked about is Serverless Espresso. Serverless Espresso is a pop up coffee shop that allows you to order coffee from your phone. In the Expo Hall at the AWS Summit, they have a Barista setup. And you walk up to a QR code with a screen in the background. So you scan the QR code and enter in your email address. And up pops a menu. If you select an americano, espresso or other type of coffee, it kicks off an event driven flow. It uses an event driven service under the hood and pops up in the screen as a number. And then the Barista takes the number makes your coffee and gives it to you. But what's happening in the background is a whole load of orchestration and choreography run events. And as they've been using it as a way to explain serverless event driven architecture. Event driven architecture can be hard for people to conceptually wrap their heads around. So making it real through ordering coffee. And showing how to tie a coffee process and an event driven coffee ordering system makes it real. It demystifies it a little bit and removes some of the thinking that event driven architecture sounds really hard. This makes it more approachable. It stitches together a lot of stuff that we've been advocating for, in a way that makes sense. By using AWS Step Functions, EventBridge, Lambda, API Gateway, S3, DynamoDB and Cognito. It brings to bare a lot of great technology that we are advocating for in a way that's practical and easily consumable. And the Serverless Espresso workshop is very good for walking you through the steps about why you're doing what you're doing. And how do you do that, set up rules and set up everything. It's a great way to get hands on with event driven architectures and serverless in a practical way. There are two myths in this space that AWS are trying to dispel. We first started talking about event driven architecture 13 years ago. We had the idea of doing something but back then it was really difficult, because we didn't have a lot of support. So we had hard problems to solve technically, because the foundations weren't there. That is the first myth of being a hard thing to do. The second myth is that people think of serverless as just writing code and functions. It's actually more like an event driven architecture. It's events firing off activity and not a call stack. So it's a lot easier to build full event of architecture than it would have been years ago. The technical challenge is not as bad as you think it is. What I like about Serverless Espresso is the simple interactions. You order, it goes to the barista who makes the coffee, and he gives it back to you. There's one interaction. Normally when ordering a coffee, you talk to a waiter, the waiter talks to the barista, and the barista talks to someone about milk etc. There can be six or seven people in that flow. It causes confusion. In a company, if a business process is owned by six or seven teams, even across two or three departments, it gets messy. If a single team builds for the customer directly and there's no one else, it's usually pretty clean. Because you can see everything needs to happen. It gets complicated if the business processes is split over several teams and departments. Serverless Espresso Lab is good, because the opinions are out there and you add on your bit, which is your business process flow. It goes back to our book The Value Flywheel Effect. And the first phase of the value flywheel which is clarity of purpose. Who is the customer and what is the business flow that we're trying to build? And let's have a good debate on how we are going to do that. When you get to the technical side, that opinion is already there. And you can focus on getting the orchestration correct. Because you know that a lot of that underlying stuff is pretty much solved apart from making it behave. Look at the Serverless Espresso Lab on workshop.serverlesscoffee.com. Or search for Serverless Espresso. And big kudos to the AWS Serverless Developer Advocate team. They're mostly on serverlessland.com. Thanks for listening. Serverless Craic from The Serverless Edge Check out our book The Value Flywheel Effect Follow us on Twitter @ServerlessEdge  

AWS Step Functions are all the rage right now! The visual editor is getting better and better and there are always new capabilities like the recently introduced intrinsic functions. In this episode we will try to answer the question “are Step Functions a Low-Code tool”? In the process, we will give our own definition of what Low-Code means, and we will describe the main characteristics of Step Functions and try to assess whether they match our definition or not. We will also discuss several practical use cases that can be addressed with Low-Code and Step Functions. In this episode, we mentioned the following resources: - Our previous episode dedicated to Step Functions and what can you do with them: https://awsbites.com/7-when-do-you-use-step-functions/ - FullStack Bulletin Newsletter - https://fullstackbulletin.com/ - Implementing the Saga pattern with Step Functions: https://theburningmonk.com/2017/07/applying-the-saga-pattern-with-aws-lambda-and-step-functions/ You can listen to AWS Bites wherever you get your podcasts: - Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-bites/id1585489017 - Spotify: https://open.spotify.com/show/3Lh7PzqBFV6yt5WsTAmO5q - Google: https://podcasts.google.com/feed/aHR0cHM6Ly9hbmNob3IuZm0vcy82YTMzMTJhMC9wb2RjYXN0L3Jzcw== - Breaker: https://www.breaker.audio/aws-bites - RSS: https://anchor.fm/s/6a3312a0/podcast/rss Do you have any AWS questions you would like us to address? Leave a comment here or connect with us on Twitter: - https://twitter.com/eoins - https://twitter.com/loige

En este episodio hablamos de qué es la observabilidad, por qué es importante en aplicaciones serverless. Cubrimos todos los conceptos más importantes y presentamos a los servicios más importantes en AWS para empezar a hacer observabilidad.Este es el episodio 6 de la tercera temporada del podcast de Charlas Técnicas de AWS.

In this episode, Dave and Emily chat with Matthew Bonig, Senior Cloud Architect at Defiance Digital. Matthew is an AWS DevTools Hero, one of the authors of the CDK Book, and a contributing member of the developer community. Matthew chats about his journey to the cloud, and shares his insights into building your own automated workflow orchestration using AWS Step Functions, Workflow Studio, and the CDK. Matthew on Twitter: https://twitter.com/mattbonig Emily on Twitter: https://twitter.com/editingemily Dave on Twitter: https://twitter.com/thedavedev Matthew on Github: https://github.com/mbonig Matthew's Website: https://matthewbonig.com/ CDK.dev Slack Channel: https://cdk.dev/ The Open Construct Foundation: https://www.openconstructfoundation.org/ The CDK Book: https://thecdkbook.com/ Developing Step Functions with the AWS CDK: https://matthewbonig.com/2022/02/19/step-functions-and-the-cdk/ AWS Step Functions Workflow Studio: https://go.aws/3vUXpOx Subscribe: Amazon Music: https://music.amazon.com/podcasts/f8bf7630-2521-4b40-be90-c46a9222c159/aws-developers-podcast Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-developers-podcast/id1574162669 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zb3VuZGNsb3VkLmNvbS91c2Vycy9zb3VuZGNsb3VkOnVzZXJzOjk5NDM2MzU0OS9zb3VuZHMucnNz Spotify: https://open.spotify.com/show/7rQjgnBvuyr18K03tnEHBI TuneIn: https://tunein.com/podcasts/Technology-Podcasts/AWS-Developers-Podcast-p1461814/ RSS Feed: https://feeds.soundcloud.com/users/soundcloud:users:994363549/sounds.rss

On The Cloud Pod this week, we're back to a full house (at least for one episode.) Plus, introducing AWS open-source Cloud Map, GCP announces new Bigtable autoscale feature, and Oracle gives us a retro tour of a data center. A big thanks to this week's sponsors: Foghorn Consulting, which provides full-stack cloud solutions with a focus on strategy, planning and execution for enterprises seeking to take advantage of the transformative capabilities of AWS, Google Cloud and Azure. JumpCloud, which offers a complete platform for identity, access, and device management — no matter where your users and devices are located.  This week's highlights

On The Cloud Pod this week, the team finds out whose re:Invent 2021 crystal ball was most accurate. Also Graviton3 is announced, and Adam Selipsky gives his first re:Invent keynote.  A big thanks to this week's sponsors: Foghorn Consulting, which provides full-stack cloud solutions with a focus on strategy, planning and execution for enterprises seeking to take advantage of the transformative capabilities of AWS, Google Cloud and Azure. JumpCloud, which offers a complete platform for identity, access, and device management — no matter where your users and devices are located.  This week's highlights

Listen to the Changelog: https://changelog.com/podcast/467Essays: https://www.swyx.io/LIP https://www.swyx.io/api-economy https://www.swyx.io/cloudflare-go TranscriptJerod Santo: So swyx, we have been tracking your work for years; well, you've been Learning in Public for years, so I've been (I guess) watching you learn, but we've never had you on the show, so welcome to The Changelog.Shawn Wang: Thank you. Long-time listener, first-time guest, I guess... [laughs]Adam Stacoviak: Yeah.Jerod Santo: Happy to have you here.Adam Stacoviak: Very excited to have you here.Jerod Santo: So tell us a little bit of your story, because I think it informs the rest of our conversation. We're gonna go somewhat deep into some of your ideas, some of the dots you've been connecting as you participate and watch the tech industry... But I think for this conversation it's probably useful to get to know you, and how you got to be where you are. Not the long, detailed story, but maybe the elevator pitch of your recent history. Do you wanna hook us up?Shawn Wang: For sure. For those who want the long history, I did a 2,5-hour podcast with Quincy Larson from FreeCodeCamp, so you can go check that out if you want. The short version is I'm born and raised in Singapore, came to the States for college, and was totally focused on finance. I thought people who were in the finance industry rules the world, they were masters of the universe... And I graduated just in time for the financial crisis, so not a great place to be in. But I worked my way up and did about 6-7 years of investment banking and hedge funds, primarily trading derivatives and tech stocks. And the more I covered tech stocks, the more I realized "Oh, actually a) the technology is taking over the world, b) all the value is being created pre-IPO, so I was investing in public stocks, after they were basically done growing... And you're kind of just like picking over the public remains. That's not exactly true, but...Jerod Santo: Yeah, tell that to Shopify...Shawn Wang: I know, exactly, right?Adam Stacoviak: And GitLab.Shawn Wang: People do IPO and have significant growth after, but that's much more of a risk than at the early stage, where there's a playbook... And I realized that I'd much rather be value-creating than investing. So I changed careers at age 30, I did six months of FreeCodeCamp, and after six months of FreeCodeCamp - you know, I finished it, and that's record time for FreeCodeCamp... But I finished it and felt not ready, so I enrolled myself in a paid code camp, Full Stack Academy in New York, and came out of it working for Two Sigma as a frontend developer. I did that for a year, until Netlify came along and offered me a dev rel job. I took that, and that's kind of been my claim to fame; it's what most people know me for, which is essentially being a speaker and a writer from my Netlify days, from speaking about React quite a bit.[04:13] I joined AWS in early 2020, lasted a year... I actually was very keen on just learning the entire AWS ecosystem. You know, a frontend developer approaching AWS is a very intimidating task... But Temporal came along, and now I'm head of developer experience at Temporal.Adam Stacoviak: It's an interesting path. I love the -- we're obviously huge fans of FreeCodeCamp, and Quincy, and all the work he's done, and the rest of the team has done to make FreeCodeCamp literally free, globally... So I love to see -- it makes you super-happy inside just to know how that work impacts real people.Like, you see things happen out there, and you think "Oh, that's impacting", but then you really meet somebody, and 1) you said you're a long-time listener, and now you're on the show, so it just really -- like, having been in the trenches so long, and just see all this over-time pay off just makes me really believe in that whole "Slow and steady, keep showing up, do what needs done", and eventually things happen. I just love that.Shawn Wang: Yeah. There's an infinite game mentality to this. But I don't want to diminish the concept of free, so... It bothers me a little, because Quincy actually struggles a lot with the financial side of things. He supports millions of people on like a 300k budget. 300k. If every single one of us who graduated at FreeCodeCamp and went on to a successful tech career actually paid for our FreeCodeCamp education - which is what I did; we started the hashtag. It hasn't really taken off, but I started a hashtag called #payitbackwards. Like, just go back, once you're done -- once you can afford it, just go back and pay what you thought it was worth. For me, I've paid 20k, and I hope that everyone who graduates FreeCodeCamp does that, to keep it going.Adam Stacoviak: Well, I mean, why not...?Shawn Wang: I'd also say one thing... The important part of being free is that I can do it on nights and weekends and take my time to decide if I want to change careers. So it's not just a free replacement to bootcamps, it actually is an async, self-guided, dip-your-toe-in-the-water, try-before-you-buy type of thing for people who might potentially change their lives... And that's exactly what happened for me. I kept my day job until the point I was like "Okay, I like enough of this... I'm still not good, but I like enough of this that I think I could do this full-time."Adam Stacoviak: I like the #payitbackwards hashtag. I wish it had more steam, I suppose.Jerod Santo: We should throw some weight behind that, Adam, and see if we can...Adam Stacoviak: Yeah. Well, you know, you think about Lambda School, for example - and I don't wanna throw any shade by any means, because I think what Austin has done with Lambda... He's been on Founders Talk before, and we talked deeply about this idea of making a CS degree cost nothing, and there's been a lot of movement on that front there... But you essentially go through a TL;DR of Lambda as you go through it, and you pay it after you get a job if you hit certain criteria, and you pay it based upon your earnings. So why not, right? Why not have a program like that for FreeCodeCamp, now that you actually have to commit to it... But it's a way. I love that you paid that back and you made that an avenue, an idea of how you could pay back FreeCodeCamp, despite the commitment not being there.Jerod Santo: Right.Shawn Wang: Yeah. And Quincy is very dedicated to it being voluntary. He thinks that people have different financial situations. I don't have kids, so I can afford a bit more. People should have that sort of moral obligation rather than legal obligation.I should mention that Lambda School is currently being accused of some fairly substantial fraud against its students...Jerod Santo: Oh, really?Shawn Wang: Yeah, it actually just came out like two days ago.Adam Stacoviak: I saw that news too, on Monday.Shawn Wang: Yeah. It's not evidenced in the court of law, it's one guy digging up dirt; let's kind of put this in perspective. But still, it's very serious allegations, and it should be investigated. That said, the business of changing careers and the business of teaching people to code, and this innovation of Income Share Agreements (ISA), where it actually makes financial sense for people to grow bootcamps and fund bootcamps - this is something I strongly support... Whether or not it should be a venture-funded thing, where you try to go for 10x growth every year - probably not... [laughs]Adam Stacoviak: Yeah...Jerod Santo: So after FreeCodeCamp you didn't feel quite ready, so you did do a bootcamp... Did you feel ready after that?Shawn Wang: [08:03] Yeah. [laughs] I did a reflection, by the way, of my first year of learning to code, so people can look it up... It's called "No zero days. My path to learning to code", and I think I posted it on Hacker News. And doing everything twice actually helped me a lot. Because before I came into my paid bootcamp, I had already spun up some React apps. I had already started to mess with WebPack, and I knew enough that I wasn't understanding it very much, I was just following the instructions. But the second time you do things, you have to space, to really try to experiment, to actually read the docs, which most people don't do, and actually try to understand what the hell it is you're doing. And I felt that I had an edge over the other people in my bootcamp because I did six months of FreeCodeCamp prior.Jerod Santo: So this other thing that you do, which not everybody does, is this Learning in Public idea... And you have this post, Learn in Public. You call it "The fastest way to learn", or the fastest way to build your expertise - networking, and second brain. I'm not sure what the second brain is, so help us out with that one... But also, why is learning in public faster than learning in private.Shawn Wang: Yeah. This is a reflection that came from me understanding the difference, qualitatively, between why I'm doing so well in my tech career versus my finance career. In finance, everything is private, meaning the investment memos that I wrote, the trade ideas that I had - they're just from a company; they're intellectual property of my company. In fact, I no longer own them. Some of my best work has been in that phase, and it's locked up in an email inbox somewhere, and I'll never see it again. And that's because tech is a fundamentally open and positive-sum industry, where if you share things, you don't lose anything; you actually gain from sharing things... Whereas in finance it's a zero-sum battle against who's got the secret first and who can act on it first.And I think when you're in tech, you should exploit that. I think that we have been trained our entire lives to be zero-sum, from just like the earliest days of our school, where we learn, we keep it to ourselves to try to pass the test, try to get the best scores, try to get the best jobs, the best colleges, and all that, because everything's positional. For you to win, others have to lose. But I don't see tech in that way, primarily because tech is still growing so fast. There's multiple ways for people to succeed, and that's just the fundamental baseline. You layer on top of that a bunch of other psychological phenomenon.I've been really fascinated by this, by what it is so effective. First of all, you have your skin in the game, meaning that a lot of times when your name is on the blog posts out there, or your name is on the talk that you gave, your face is there, and people can criticize you, you're just incentivized to learn better, instead of just "Oh, I'll read this and then I'll try to remember it." No, it doesn't really stick as much. So having skin in the game really helps.When you get something wrong in public, there are two effects that happen. First is people will climb over broken glass to correct you, because that's how the internet does. There's a famous XKCD comic where like "I can't go to bed yet." "Why?" "Someone's wrong on the internet. I have to correct them."Jerod Santo: Right.Shawn Wang: So people are incentivized to fix your flaws for you - and that's fantastic - if you have a small ego.Jerod Santo: I was gonna say, that requires thick skin.Shawn Wang: Yeah, exactly. So honestly -- and that's a barrier for a lot of people. They cannot get over this embarrassment. What I always say is you can learn so much on the internet, for the low, low price of your ego. If we can get over that, we can learn so much, just because you don't care. And the way to get over it is to just realize that the version that you put out today is the version you should be embarrassed about a year from now, because that shows that you've grown. So you divorce your identity from your work, and just let people criticize your work; it's fine, because it was done by you, before you knew what you know today. And that's totally fine.And then the second part, which is that once you've gotten something wrong in public, it's just so embarrassing that you just remember it in a much clearer fashion. [laughter] This built a feedback loop, because once you started doing this, and you show people that you respond to feedback, then it builds a feedback and an expectation that you'll do the next thing, and people respond to the next thing... It becomes a conversation, rather than a solitary endeavor of you just learning the source material.So I really like that viral feedback loop. It helps you grow your reputation... Because this is not just useful for people who are behind you; a lot of people, when they blog, when they write, when they speak, they're talking down. They're like "I have five years experience in this. Here's the intro to whatever. Here's the approach to beginners." They don't actually get much out of that.[12:17] That's really good, by the way, for beginners; that's really important, that experts in the field share their knowledge. They don't see this blogging or this speaking as a way to level up in terms of speaking to their experts in their fields. But I think it's actually very helpful. You can be helpful to people behind you, you can be helpful to people around you, but you can actually be helpful to people ahead of you, because you're helping to basically broadcast or personalize their message. They can check their messaging and see - if you're getting this wrong, then they're getting something wrong on their end, docs-wise, or messaging-wise. That becomes a really good conversation. I've interacted with mentors that way. That's much more how I prefer to interact with my mentors than DM-ing and saying "Hey, can you be my mentor?", which is an unspecified, unpaid, indefinitely long job, which nobody really enjoys. I like project-based mentorship, I like occasional mentorship... I really think that that develops when you learn in public.Adam Stacoviak: I've heard it say that "Today is the tomorrow you hope for."Shawn Wang: Wow.Adam Stacoviak: Because today is always tomorrow at some point, right? Like, today is the day, and today you were hoping for tomorrow to be better...Jerod Santo: I think by definition today is not tomorrow...Adam Stacoviak: No, today is the tomorrow that you hoped for... Meaning like "Seize your moment. It's here."Jerod Santo: Carpe diem. Gotcha.Adam Stacoviak: Yeah, kind of a thing like that.Shawn Wang: I feel a little shady -- obviously, I agree, but also, I feel a little shady whenever I venture into this territory, because then it becomes very motivational speaking-wise, and I'm not about that. [laughs]Adam Stacoviak: Kind of... But I think you're in the right place; keep showing up where you need to be - that kind of thing. But I think your perspective though comes from the fact that you had this finance career, and a different perspective on the way work and the way a career progressed. And so you have a dichotomy essentially between two different worlds; one where it's private, and one where it's open. That to me is pretty interesting, how you were able to tie those two together and see things differently. Because I think too often sometimes in tech, especially staying around late at night, correcting someone on the internet, you're just so deeply in one industry, and you have almost a bubble around you. You have one lens for which you see the world. And you've been able to have multi-faceted perspectives of this world, as well as others, because of a more informed career path.Jerod Santo: Yeah. When you talk about finance as a zero-sum game, I feel like there's actually been moves now to actually open up about finance as well; I'm not sure if either of you have tracked the celebrity rise of Cathie Wood and Ark Invest, and a lot of the moves that she's doing in public. They're an investment fund, and they will actually publish their moves at the end of every day. Like, "We sold these stocks. We bought these stocks." And people laughed at that for a while, but because she's been successful with early on Bitcoin, early with Tesla, she's very much into growth stocks - because of that, people started to follow her very closely and just emulate. And when she makes moves now, it makes news on a lot of the C-SPANs and the... Is C-SPAN the Congress one? What's the one that's the finance one...?Shawn Wang: CNBC?Jerod Santo: CNBC, not C-SPAN. And so she's very much learning in public. She's making her moves public, she's learning as she goes, and to a certain degree it's paid off, it's paid dividends in her career. Now, I'm not sure if everyone's doing that... When you look at crypto investors, like - okay, pseudonymous, but a lot of that stuff, public ledgers. So there's moves that are being made in public there as well. So I wonder if eventually some of that mentality will change. What do you think about that?Shawn Wang: [15:45] It's definitely changed for -- there's always been celebrity investors, and people have been copying the Buffett portfolio for 30 years. So none of that is new. What is new is that Cathie Wood is running an ETF, and just by way of regulation and by way of innovation, she does have to report those changes. [laughs] So mutual funds, hedge fund holdings - these have all been public, and people do follow them. And you're always incentivized to talk your book after you've established your position in your book...Jerod Santo: Right, but you establish it first.Shawn Wang: ...so none of that has changed. But yeah, Cathie has been leading an open approach...Jerod Santo: Is it the rate of disclosure perhaps that's new? Because it seems like it's more real-time than it has historically...Shawn Wang: Yeah. I mean, she's running an ETF, which is new, actually... Because most people just run mutual funds or hedge funds, and those are much more private. The other two I'll probably shout out is Patrick O'Shaughnessy who's been running I guess a fund of funds, and he's been fairly open. He actually adopted the "learn in public" slogan in the finance field, independently of me. And then finally, the other one is probably Ted Seides, who is on the institutional investor side of things. So he invests for universities, and teachers pensions, and stuff like that. So all these people - yeah, they've been leading that... I'm not sure if it's spreading, or they've just been extraordinarily successful in celebrity because of it.Adam Stacoviak: This idea of "in public" is happening. You see people too, like -- CopyAI is building in public... This idea of learning in public, or building in public, or exiting in public... Whatever the public might be, it's happening more and more... And I think it's definitely similar to the way that open source moves around. It's open, so it's visible to everyone. There's no barrier to see what's happening, whether it's positive or negative, with whatever it is in public. They're leveraging this to their advantage, because it's basically free marketing. And that's how the world has evolved to use social media. Social media has inherently been public, because it's social...Jerod Santo: Sure.Adam Stacoviak: Aside from Facebook being gated, with friends and stuff like that... Twitter is probably the most primary example of that, maybe even TikTok, where if I'm a creator on TikTok, I almost can't control who sees my contact. I assume it's for the world, and theoretically, controlled by the algorithm... Because if I live in Europe, I may not see content in the U.S, and the algorithm says no, or whatever. But it's almost like everybody is just in public in those spaces, and they're leveraging it to their advantage... Which is an interesting place to be at in the world. There was never an opportunity before; you couldn't do it at that level, at that scale, ten years ago, twenty years ago. It's a now moment.Jerod Santo: Yeah. Swyx, can you give us an example of something learned in public? Do you basically mean like blog when you've learned something, or ask questions? What does learning in public actually mean when it comes to -- say, take a technology. Maybe you don't understand Redux. I could raise my hand on that one... [laughter] How could I learn that in public?Shawn Wang: There are a bunch of things that you can try. You can record a livestream of you going through the docs, and that's useful to maintainers, understanding "Hey, is this useful or not?" And that's immediately useful. It's so tangible.I actually have a list -- I have a talk about this on the blog post as well... Just a suggestion of things you can do. It's not just blogging. You can speak, you can draw comics, cheatsheets are really helpful... I think Amy Hoy did a Ruby on Rails cheatsheet that basically everyone has printed out and stapled to their wall, or something... And if you can do a nice cheatsheet, I think that's also a way for you to internalize those things that you're trying to learn anyway, and it just so happens to benefit others.So I really like this idea that whatever content you're doing, it's learning exhaust, it's a side effect of you learning, and you just happen to put it out there; you understand what formats work for you, because you have abnormal talents. Especially if you can draw, do that. People love developers who can draw. And then you just put it out there, and you win anyway just by doing it. You don't need an audience. You get one if you do this long enough, but you don't need an audience right away. And you win whether or not people participate with you. It's a single-player game that can become a multiplayer game.Specifically for Redux - you know, go through source code, or go through the docs, build a sample app, do like a simple little YouTube video on it... Depending on the maturity, you may want to try to speak at a meetup, or whatever... You don't have to make everything a big deal. I'm trying to remove the perception from people that everything has to be this big step, like it has to be top of Hacker News, or something. No. It could just be helpful for one person. I often write blog posts with one persona in mind. I mean, I don't name that person, but if you focus on that target persona, actually often it does better than when you try to make some giant thesis that shakes the world...Adam Stacoviak: [20:22] Yeah. Too often we don't move because we feel like the weight of the move is just too much. It's like "How many people have to read this for me to make this a success for me?" You mentioned it's a learning exhaust... And this exhaust that you've put out before - has it been helpful really to you? Is that exhaust process very helpful to you? Is that ingrained in the learnings that you've just gone through, just sort of like synthesize "Okay, I learned. Here's actually what I learned"?Shawn Wang: Yeah. This is actually an opportunity to tie into that second brain concept which maybe you wanted to talk a little bit about. Everything that you write down becomes your second brain. At this point I can search Google for anything I've ever written on something, and actually come up on my own notes, on whatever I had. So I'm not relying on my memory for that. Your human brain, your first brain is not very good at storage, and it's not very good at search; so why not outsource that to computers? And the only way to do that is you have to serialize your knowledge down into some machine-readable format that's part of research. I do it in a number of places; right now I do it across GitHub, and my blog, and a little bit of my Discord. Any place where you find you can store knowledge, I think that's a really good second brain.And for Jerod, I'll give you an example I actually was gonna bring up, which is when I was trying to learn React and TypeScript - like, this goes all the way back to my first developer job. I was asked to do TypeScript, even though I'd never done it before. And honestly, my team lead was just like "You know TypeScript, right? You're a professional React dev, you have to know TypeScript." And I actually said no, and I started learning on day one.And what I did was I created the React to TypeScript cheatsheet, which literally was just copy-pasteable code of everything that I found useful and I wish I knew when I was starting out. And I've just built that over time. That thing's been live for three years now, it's got like 20,000 stars. I've taught thousands of developers from Uber, from Microsoft, React and TypeScript. And they've taught me - every time they send in a question or a PR... I think it's a very fundamental way of interacting, which is learning in public, but specifically this one - it's open source knowledge; bringing up our open source not just to code, but to everything else. I think that's a fundamental feedback loop that I've really enjoyed as well.Break: [22:31]Jerod Santo: One of the things I appreciate about you, swyx, is how you are always thinking, always writing down your thoughts... You've been watching and participating in this industry now for a while, and you've had some pretty (I think) insightful writings lately. The first one I wanna talk about is this API Economy post. The Light and Dark Side of the API Economy. You say "Developers severely underestimate the importance of this to their own career." So I figure if that's the case, we should hear more about it, right?Shawn Wang: [laughs] Happy to talk about it. So what is the API economy? The API economy is developers reshaping the world in their image. Very bold statement, but kind of true, in the sense that there is now an API for everything - API for cards, API for bank accounts, API for text, API for authentication, API for shipping physical goods... There's all sorts of APIs. And what that enables you to do as a developer is you can call an API - as long as you know REST or GraphQL these days, you know how to invoke these things and make these things function according to the rest of your program. You can just fit those things right in. They're a very powerful thing to have, because now the cost of developing one of these services just goes down dramatically, because there's another company doing that as a service for you.I wrote about it mainly because at Netlify we were pitching serverless, we were pitching static hosting, and we were pitching APIs. That's the A in JAMstack. But when I google "API economy", all the search results were terrible. Just horrible SEO, bland, meaningless stuff that did not speak to developers; it was just speaking to people who like tech buzzwords. So I wrote my own version. The people who coined it at Andreessen Horowitz, by the way, still to this day do not have a blog post on the API economy. They just have one podcast recording which nobody's gonna listen. So I just wrote my version.Jerod Santo: You're saying people don't listen to podcasts, or what?Shawn Wang: [laughs] When people are looking up a term, they are like "What is this thing?", and you give them a podcast, they're not gonna sit down and listen for 46 minutes on a topic. They just want like "Give me it, in one paragraph. Give me a visual, and I'm gonna move on with my day." So yeah, whenever I see an opportunity like that, I try to write it up. And that's the light side; a lot of people talk about the light side. But because it's a personal blog, I'm empowered to also talk about the dark side, which is that as much as it enables developers, it actually is a little bit diminishing the status of human expertise and labor and talent. So we can talk a little bit about that, but I'm just gonna give you time to respond.Jerod Santo: [28:05] Hm. I'm over here thinking now that you're not at Netlify, I'm curious - this is tangential, but what's your take on JAMstack now? I know you were a professional salesman there for a while, but... It seems like JAMstack - we've covered it for years, it's a marketing term, it's something we've already been doing, but maybe taking it to the next level... There's lots of players now - Netlify, Vercel etc. And yet, I don't see much out there in the real world beyond the people doing demos, "Here's how to build a blog, here's how to do this, here's my personal website", and I'm just curious... I'm not like down on JAMstack, but I just don't see it manifesting in the ways that people have been claiming it's going to... And maybe we're just waiting for the technology to catch up. I'd just love to hear what you think about it now.Shawn Wang: Yeah. I think that you're maybe not involved in that world, so you don't see this, but real companies are moving on to JAMstack. The phrasing that I like is that -- JAMstack has gone mainstream, and it's not even worth talking about these days, because it's just granted that that's an option for you... So PayPal.me is on the JAMstack, there's large e-commerce sites... Basically, anything that decouples your backend from your frontend, and your frontend is statically-hosted - that is JAMstack.I actually am blanking on the name, but if you go check out the recent JAMstack Conf, they have a bunch of examples of people who've not only moved to JAMstack, but obviously moved to Netlify, where they're trying to promote themselves.Jerod Santo: Sure, yeah.Shawn Wang: So yes, it's true that I'm no longer a professional spokesperson, but it's not true that JAMstack is no longer being applied in the enterprise, because it is getting adoption; it's moved on that boring phase where people don't talk about it.One thing I'll say - a thesis that I've been pursuing is that JAMstack is in its endgame. And what do I mean by that? There's a spectrum between the previous paradigm that JAMstack was pushing back on, which is the all-WordPress/server-render-everything paradigm, and then JAMstack is prerender-everything. And now people are filling in--Jerod Santo: In the middle.Shawn Wang: ...I'm gonna put my hands in the Zoom screen right now. People are filling that gap between fully dynamic and fully static. So that's what you see with Next.js and Gatsby moving into serverless rendering, partial rendering or incremental rendering... And there's a full spectrum of ways in which you can optimize your rendering for the trade-offs of updating your content, versus getting your data/content delivered as quickly as possible. There's always some amount of precompilation that you need to do, and there's always some amount of dynamicism that you have to do, that cannot be precompiled. So now there is a full spectrum between those.Why I say it's the end game is because that's it, there's nothing else to explore. It's full-dynamic, full-static, choose some mix in the middle, that's it. It's boring.Jerod Santo: Hasn't that always been the case though? Hasn't there always been sites that server-side render some stuff, and pre-render other things? You know, we cache, we pre-render, some people crawl their own websites once, and... I don't know it seems like maybe just a lot of excitement around a lot of things that we've been doing for many years.Shawn Wang: [laughs] So first of all, those are being remade in the React ecosystem of things, which a lot of us lost when a lot of the web development industry moved to React... So that's an important thing to get back.I mean, I agree, that's something that we've always had, pre-rendering, and services like that, caching at the CDN layer - we've always had that. There's some differences... So if you understand Netlify and why they're trying to push distributed persistent rendering (DVR), it's because caching is a hard problem, and people always end up turning off the cache. Because the first time you run into a bug, you're gonna turn off the cache. And the cache is gonna stay off.So the way that Netlify is trying to fix it is that we put the cache in Git, essentially. Git is the source of truth, instead of some other source of truth distributed somewhere between your CDN and your database and somewhere else. No, everything's in Git. I'm not sure if I've represented that well, to be honest... [laughter]Adam Stacoviak: Well, good thing you don't work for Netlify anymore. We're not holding you to the Netlify standard.Shawn Wang: [31:58] Exactly. All I can say is that to me now it's a good thing in the sense that it's boring. It's the good kind of boring, in the sense of like "Okay, there's a spectrum. There's all these techniques. Yes, there were previous techniques, but now these are the new hotness. Pick your choice." I can get into a technical discussion of why this technique, the first one, the others... But also, is it that interesting unless you're evaluating for your site? Probably not...Jerod Santo: Well, it does play into this API economy though, right? Because when you're full JAMstack, then the A is your most important thing, and when the A is owned by a bunch of companies that aren't yours - like, there's a little bit of dark side there, right? All of a sudden, now I'm not necessarily the proprietor of my own website, to a certain degree, because I have these contracts. I may or may not get cut off... There's a lot of concerns when everybody else is a dependency to your website.Shawn Wang: Yeah. So I don't consider that a dark side at all.Jerod Santo: No, I'm saying to me that seems like a dark side.Shawn Wang: Yeah, sure. This is the risk of lock-in; you're handing over your faith and your uptime to other people. So you have to trade that off, versus "Can you build this yourself? And are you capable of doing something like this, and are you capable of maintaining it?" And that is a very high upfront cost, versus the variable cost of just hiring one of these people to do it for you as a service.So what I would say is that the API economy is a net addition, because you as a startup - the startup cost is very little, and if you get big enough where it makes sense for you to build in-house - go ahead. But this is a net new addition for you to turn fixed costs into variable costs, and start with a small amount of investment. But I can hire -- like, Algolia was started by three Ph.D's in search, and I can hire them for cents to do search on my crummy little website. I will absolutely do that every single day, until I get to a big enough point where I cannot depend on them anymore, and I have to build my own search. Fine, I'll do that. But until then, I can just rely on them. That's a new addition there.Jerod Santo: One hundred percent. So what then do you think is the darker side? You mentioned it, but put a finer point on it.Shawn Wang: Yeah. The dark side is that there are people -- like, when I call an Uber ride, Uber is an API for teleportation, essentially. I'm here, I wanna go there. I press a button, the car shows up. I get in the car, get off, I'm there. What this papers over is that the API is calling real actual humans, who are being commoditized. I don't care who drives the car, I really don't. I mean, they may have some ratings, but I kind of don't care.Jerod Santo: That was the case with taxis though, wasn't it?Shawn Wang: That was the case with taxis, for sure. But there's a lot of people living below the API, who are economically constrained, and people who live above the API, developers, who have all the upside, essentially... Because the developers are unique, the labor is commoditized. My DoorDash pickers, my Instacart deliverers - all these are subsumed under the API economy. They're commodities forever, they know it, and there's no way out for them, unless they become developers themselves. There's a class system developing below and above the API. And the moment we can replace these people under the API with robots, you better believe we'll do that, because robots are way cheaper, and they complain less, they can work 24 hours, all this stuff.Jerod Santo: Yeah.Shawn Wang: So that's the dark side, which is, yeah, as a developer now - fantastic. I can control most parts of the economy with just a single API call. As a startup founder, I can develop an API for literally anything, and people will buy it. The downside is human talent is being commoditized, and I don't know how to feel about that. I think people are not talking enough about it, and I just wanna flag it to people.Jerod Santo: Yeah.Adam Stacoviak: So dark side could mean a couple things. One, it could mean literally bad; dark as synonymous with bad. Or dark as in shady. And we're not sure, it's obscured in terms of what's happening. And so let's use an Instacarter or a Dasher - to use their terminology. I happen to be a DoorDash user, so I know they're called Dashers; that's the only reason I know that. It's not a downplay, it's just simply what the terminology is...[35:59] You could say it's below the API, but I wonder, if you've spoken with these people, or people that live in what you call below the API, because I would imagine they're not doing that because they're being forced. Like, it's an opportunity for them.Shawn Wang: Oh, yeah.Adam Stacoviak: And I remember when I was younger and I had less opportunity because I had less "above the API" (so to speak) talent... And I do agree there's a class here, but I wonder if it's truly bad; that dark is truly bad, or if it's just simply obscure in terms of how it's gonna play out.Shawn Wang: This is about upside. They will never get to that six figures income with this thing.Adam Stacoviak: Not that job.Jerod Santo: No.Shawn Wang: It's really about the class system, which is the dark side. You don't want to have society splinter into like a serving class and whatever the non-serving class is. It's also about the upside - like, I don't see a way for these people to break out unless, they really just take a hard stop and just go to a completely different career track.Jerod Santo: Right.Adam Stacoviak: Here's where I have a hard time with that... I'm not pushing back on that you're wrong, I'm just wondering more deeply...Shawn Wang: Sure.Adam Stacoviak: I imagine at one point in my life I was a DoorDasher.Shawn Wang: Yeah.Adam Stacoviak: I washed dishes, I did definitely unique jobs at a young age before I had skill. And so the path is skill, and as long as we have a path to skill, which you've show-cased through FreeCodeCamp in your path, then I think that dark side is just simply shady, and not bad.Shawn Wang: Okay.Adam Stacoviak: And I'm just trying to understand it, because I was truly a DoorDasher before DoorDash was available. I washed dishes, delivered papers, I had servant-level things; I was literally a server at a restaurant before... And I loved doing that kind of work, but my talents have allowed me to go above that specific job, and maybe even the pay that came with that job. I've served in the military before, got paid terrible dollars, but I loved the United States military; it's great. And I love everybody who's served in our military. But the point is, I think the path is skill, and as long as we have a pathway to skill, and jobs that can house that skill and leverage that skill to create new value for the world, I just wonder if it's just necessary for society to have, I suppose, above and below API things.Jerod Santo: Until we have all the robots. Then there is nobody underneath. At that point it's all robots under the API.Shawn Wang: Yes, and that is true in a lot of senses, actually. Like, farming is mostly robots these days. You do have individual farmers, but they're much less than they used to be. I don't know what to say about that, shady or dark... I think it's just -- there's no career track. You have to go break out of that system yourself. Thank God there's a way to do it. But back in the day, you used to be able to go from the mailroom to the boardroom.Adam Stacoviak: I see.Shawn Wang: I see these stories of people who used to be janitors at schools become the principal. Companies used to invest in all their people and bring them up. But now we're just hiring your time, and then if you wanna break out of that system - good luck, you're on your own. I think that that lack of upward mobility is a problem, and you're not gonna see it today. It's a slow-moving train wreck. But it's gonna happen where you have society split in two, and bad things happen because of it.Adam Stacoviak: I mean, I could agree with that part there, that there definitely is no lateral movement from Dasher to CEO of DoorDash.Shawn Wang: It's just not gonna happen.Adam Stacoviak: Or VP of engineering at DoorDash. I think because there is no path, the path would be step outside of that system, because that system doesn't have a path. I could agree with that, for sure.Jerod Santo: Yeah. I mean, the good news is that we are creating -- there are paths. This is not like a path from X to Y through that system, but there are other alternate paths that we are creating and investing in, and as well as the API gets pushed further and further down in terms of reachability - we now have more and more access to those things. It's easier now, today, than it ever has been, because of what we were talking about, to be the startup founder, right? To be the person who starts at CEO because the company has one person in it, and they're the CEO. And to succeed in that case, and become the next DoorDash.Adam Stacoviak: True.Jerod Santo: So there are opportunities to get out, it's just not a clear line... And yeah, it takes perhaps some mentorship, perhaps ingenuity... A lot of the things that it takes to succeed anyway, so...Shawn Wang: [40:05] I'll give a closing note for developers who are listening, because you're already a developer... So the analogy is if you're above the API, you tell machines what to do; if you're below the API, machines tell you what to do. So here's the developer analogy, which is there's another division in society, which is the kanban board. If you're below the kanban board, the kanban board tells you what to do. If you're above it, you tell developers what to do. [laughs]Jerod Santo: There you go.Shawn Wang: So how do you break out of that class division? I'll leave it out to you, but just keep in mind, there's always layers.Jerod Santo: I love that.Adam Stacoviak: I love the discussion around it, but I'm also thankful you approached the subject by a way of a blog post, because I do believe that this is interesting to talk about, and people should talk about it, for sure. Because it provides introspection into, I guess, potentially something you don't really think about, like "Do I live below or above the APi?" I've never thought about that in that way until this very moment, talking to you, so... I love that.Break: [40:58]Jerod Santo: So another awesome post you have written lately is about Cloudflare and AWS. Go - not the language, the game Go... I know very little about the language, and I know even less about the game... And Chess... How Cloudflare is approaching things, versus how AWS and Google and others are... Given us the TL;DR of that post, and then we'll discuss.Shawn Wang: Okay. The TL;DR of that post is that Cloudflare is trying to become the fourth major cloud after AWS, Azure and GCP. The way they're doing it is fundamentally different than the other three, and the more I've studied them - I basically observed Cloudflare for the entire time since I joined Netlify. Netlify kind of is a competitor to Cloudflare, and it's always this uncomfortable debate between "Should you put Cloudflare in front of Netlify? Netlify itself is a CDN. Why would you put a CDN in front of another CDN?" Oh, because Netlify charges for bandwidth, and Cloudflare does not. [laughter]Jerod Santo: It's as simple as that.Shawn Wang: And then there's DDOS protection, all that stuff; very complicated. Go look up the Netlify blog post on why you should not put Cloudflare in front of Netlify, and decide for yourself. But Netlify now taking on AWS S3 - S3 is like a crown jewel of AWS. This is the eighth wonder of the world. It provides eleven nines of durability. Nothing less than the sun exploding will take this thing down... [laughs]Jerod Santo: Right? You know what's funny - I don't even consider us at Changelog AWS customers; I don't even think of us that way. But of course, we use S3, because that's what you do. So yeah, we're very much AWS customers, even though I barely even think about it, because S3 is just like this thing that of course you're gonna use.Shawn Wang: There's been a recent history of people putting out S3-compatible APIs, just because it's so dominant that it becomes the de-facto standard. Backblaze did it recently. But Cloudflare putting out R2 and explicitly saying "You can slurp up the S3 data, and by the way, here's all the cost-benefit of AWS egress charges that's what Matthew Prince wrote about in his blog post is all totally true, attacks a part of AWS that it cannot compromise on and just comes at the top three clouds from a different way, that they cannot respond to.[44:17] So I always like these analogies of how people play destruction games. I'm a student of destruction, and I study Ben Thompson and Clay Christensen, and that entire world, very quickly... So I thought this was a different model of destruction, where you're essentially embracing rather than trying to compete head-on. And wrapping around it is essentially what Go does versus chess, and I like -- you know, there's all these comparisons, like "You're playing 2D chess, I'm playing 3D chess. You're playing chess, I'm playing Go." So Cloudflare is playing Go by surrounding the S3 service and saying "Here is a strict superset. You're already a consumer of S3. Put us on, and magically your costs get lower. Nothing else about it changes, including your data still lives in AWS if you ever decide to leave us." Or if you want to move to Cloudflare, you've just gotta do the final step of cutting off S3.That is a genius, brilliant move that I think people don't really appreciate, and it's something that I study a lot, because I work at companies that try to become the next big cloud. I worked at Netlify, and a lot of people are asking, "Can you build a large public company on top of another cloud? Our second-layer cloud is viable." I think Vercel and Netlify are proving that partially it is. They're both highly valued. I almost leaked some info there... When does this go out? [laughs]Jerod Santo: Next week, probably...Shawn Wang: Okay, alright... So they're both highly valued, and - like, can they be hundred-billion-dollar companies? I don't know. We don't know the end state of cloud, but I think people are trying to compete there, and every startup -- I nearly joined Render.com as well. Every startup that's trying to pitch a second-layer cloud thesis is always working under the shadows of AWS. And this is the first real thesis that I've seen, that like "Oh, okay, you not only can credibly wrap around and benefit, you can actually come into your own as a fourth major cloud." So I'm gonna stop there... There's so many thoughts I have about Cloudflare.Jerod Santo: Yeah. So do you see that R2 then -- I think it's a brilliant move, as you described it... As I read your post, I started to appreciate, I think, the move, more than I did when I first read about it and I was like "Oh, they're just undercutting." But it seems they are doing more than just that. But do you think that this R2 then is a bit of a loss leader in order to just take a whole bunch of AWS customers, or do you think there's actually an economic -- is it economically viable as a standalone service, or do you think Cloudflare is using it to gain customers? What are your thoughts in their strategy of Why?Shawn Wang: This is the top question on Twitter and on Hacker News when they launch. They are going to make money on this thing, and the reason is because of all the peering agreements that they've established over the past five years. As part of the normal business strategy of Cloudflare, they have peering agreements with all of the ISPs; bandwidth is free for them. So... For them in a lot of cases. Again, I have to caveat all this constantly, because I should note to people that I am not a cloud or networking expert. I'm just learning in public, just like the rest of you, and here's what I have so far. So please, correct me if I'm wrong, and I'll learn from it.But yeah, I mean - straight on, it's not a loss leader. They plan to make money on it. And the reason they can is because they have worked so hard to make their cost structure completely different in AWS, and they've been a friend to all the other ISPs, rather than AWS consuming everything in its own world. Now you're starting to see the benefits of that strategy play out. And by the way, this is just storage, but also they have data store, also they have service compute, all following the same model.Jerod Santo: So what do you think is a more likely path over the next two years? Cloudflare --Adam Stacoviak: Prediction time!Jerod Santo: ...Cloudflare steals just massive swathes of AWS customers, or AWS slashes prices to compete?Shawn Wang: So I try not to do the prediction business, because I got out of that from the finance days... All I'm doing is nowcasting. I observe what I'm seeing now and I try to put out the clearest vision of it, so the others can follow.I think that it makes sense for them to be replicating the primitives of every other cloud service. So in 2017 they did service compute with Cloudflare Workers. In 2018 they did eventually consistent data store. In 2019 - website hosting; that's the Netlify competitor. In 2020 they did strongly-consistent data store, with Durable Objects. In 2021 object storage. What's next on that list? Go on to your AWS console and go shopping. And instead of seven different ways to do async messaging in AWS, probably they're gonna do one way in Cloudflare. [laughs]Adam Stacoviak: [48:34] A unified API, or something like that...Jerod Santo: Yeah, they'll just look at AWS' offerings, the ones they like the best, and do it that way, right?Shawn Wang: Yeah, just pick it up.Adam Stacoviak: Maybe the way to get a prediction out of you, swyx, might be rather than directly predict, maybe describe how you win Go.Shawn Wang: How you win Go...Adam Stacoviak: Yeah, what's the point of Go? How do you win Go? Because that might predict the hidden prediction, so to speak.Shawn Wang: Okay. For listeners who don't know Go, let me draw out the analogy as well. So most people are familiar with chess; individual chess pieces have different values and different points, and they must all support each other. Whenever you play chess, you need the Knight to support the pawns, something like that... Whereas in Go, you place your pieces everywhere, and they're all indistinguishable from each other. And it's more about claiming territory; at the end of the day, that's how you win Go, you claim the most territory compared to the others... And it's never a winner-take-all situation. Most likely, it's like a 60/40. You won 60% of the territory and your competitor has 40% of the territory. That's more likely a mapping of how cloud is gonna play out than chess, where winner-takes-all when you take the King. There's no King in the cloud, but--Jerod Santo: Are you sure...?Shawn Wang: ...there's a lot likely of territory claiming, and Cloudflare is really positioned very well for that. It's just part of the final realization that I had at the end of the blog post. And partially, how you take individual pieces of territory is that you surround all the pieces of the enemy and you place the final piece and you fill up all the gaps, such that the enemy is completely cut off from everything else and is surrounded. And that's what R2 does to S3 - it surrounds S3, and it's up to you to place that final piece. They call it, Atari, by the way, which is the name of the old gaming company, Atari. They have placed AWS S3 in Atari, and it's up to the customers to say "I'm gonna place that final piece. I'm gonna pay the cost of transferring all my data out of S3 and cut S3 off", and they cut off all the remaining liberties. So how do you win in Go? You claim the most amount of territory, and you surround the pieces of the enemy.Adam Stacoviak: Which, if you thought maybe that was oxygen, the territory, you might suck the oxygen away from them, so they can't live anymore, so to speak... And maybe you don't take it by killing it. Maybe you sort of suffocate it almost, if their space becomes small enough; if you take enough territory and it begins to shrink enough, it's kind of like checkmate, but not.Shawn Wang: Yeah. There's also a concept of sente in Go, which is that you make a move that the opponent has to respond to, which is kind of like a check, or checkmate -- actually, not; just the check, in chess. And right now, AWS doesn't feel the need to respond. Cloudflare is not big enough. Like, these are names to us, but let's just put things in numbers. Cloudflare's market cap is 36 billion, AWS' market cap is 1.6 trillion; this is Amazon's total market cap. Obviously, AWS is a subset of that.Jerod Santo: Sure.Shawn Wang: So your competitor is 40 times larger than you. Obviously, Cloudflare is incentivized to make a lot of noise and make themselves seem bigger than it is. But until AWS has to respond, this is not real.Adam Stacoviak: Nice.Jerod Santo: So as a developer, as a customer of potentially one or both of these... Let's say you have a whole bunch of stuff on S3 - I'm asking you personally now, swyx - and R2 becomes available... Is that a no-brainer for you, or is there any reason not to use that?Shawn Wang: You're just adding another vendor in your dependency tree. I think for anyone running silicon bandwidth, it is a no-brainer.Jerod Santo: Yeah. So over the course of n months, where n equals when they launch plus a certain number - I mean, I think this is gonna end up eventually on Amazon's radar, to where it's gonna start affecting some bottom lines that important people are gonna notice. So I just wonder - I mean, how much territory can Cloudflare grab before there's a counter-move? It's gonna be interesting to watch.Shawn Wang: [52:12] So Ben from Vantage actually did a cost analysis... Vantage is a startup that is made up former AWS Console people; they're trying to build a better developer experience on top of AWS. They actually did a cost analysis on the R2 move, and they said that there's probably a hundred billion dollars' worth of revenue at stake for Amazon. So if they start to have a significant dent in that, let's say like 40%, AWS will probably have to respond. But until then, there's nothing to worry about. That's literally how it is in Amazon; you have to see the numbers hit before you respond.Jerod Santo: Yeah. It hasn't even been a blip on the radar at this point, the key metrics to the people who are important enough to care are watching. You said you started watching all of these CDNs. Of course, you worked at Netlify... You take an interest in backends. There's something you mentioned in the break about frontenders versus backend, and where you've kind of been directing your career, why you're watching Cloudflare so closely, what you're up to now with your work... Do you wanna go there?Shawn Wang: Let's go there. So if you track my career, I started out as a frontend developer. I was developing design systems, I was working with Storybook, and React, and all that... Then at Netlify I was doing more serverless and CLI stuff. At AWS more storage and database and AppSync and GraphQL stuff... And now at Temporal I'm working on a workflow engine, pure backend. I just went to KubeCon two weeks ago...Jerod Santo: Nice!Shawn Wang: What is a frontend developer doing at KubeCon...?Adam Stacoviak: New territory.Shawn Wang: It's a frontend developer who realizes that there's a career ceiling for frontend developers. And it's not a polite conversation, and obviously there are exceptions to frontend developers who are VPs of engineering, frontend developers who are startup founders... And actually, by the way, there's a lot of VC funding coming from frontend developers, which is fantastic for all my friends. They're all getting funded, left, right and center. I feel left out. But there is a Career ceiling, in a sense that survey a hundred VPs of engineering, how many of them have backend backgrounds, and how many of them have frontend backgrounds? And given that choice, what's more likely for you and your long-term career progression? Do you want to specialize in frontend or do you want to specialize in backend? Different people have different interests, and I think that you can be successful in whatever discipline you pick. But for me, I've been moving towards the backend for that reason.Adam Stacoviak: Describe ceiling. What exactly do you mean when you say "ceiling"?Shawn Wang: Career ceiling. What's your terminal title.Jerod Santo: Like your highest role, or whatever. Highest salary, highest role, highest title...Adam Stacoviak: Gotcha.Shawn Wang: Like, straight up, how many VPs of engineering and CTOs have backend backgrounds versus frontend.Jerod Santo: Yeah. I mean, just anecdotally, I would agree with you that it's probably 8 or 9 out of 10 CTOs have -- is that what you said, 8 or 9?Shawn Wang: Yeah, yeah. So there's obviously an economic reasoning for this; it's because there's a bias in the industry that frontend is not real development, and backend is. And that has to be combated. But also, there's an economic reasoning, and I always go back to the economics part, because of my finance background... Which is that your value to the company, your value to the industry really depends on how many machines run through you. You as an individual unit of labor, how much money do you control, and how much machine process, or compute, or storage, or whatever runs through you. And just straight-up frontend doesn't take as much. [laughs] Yes, frontend is hard, yes, design is hard, yes, UX is crucially important, especially for consumer-facing products... But at the end of the day, your compute is being run on other people's machines, and people don't value that as much as the compute that I pay for, that I need to scale, and therefore I need an experienced leader to run that, and therefore that is the leader of my entire eng.Jerod Santo: I wonder if that changes at all for very product-focused orgs, where I think a lot of frontenders, the moves are into product design and architecture, and away from - not software architecture, but product design. And it seems like maybe if you compare - not VP of engineering, but VP of product, you'd see a lot of former frontenders.Shawn Wang: [56:03] Yeah.Jerod Santo: Maybe that's their path. Do you think that's --Shawn Wang: Totally. But you're no longer a frontend dev. You suddenly have to do mocks...Jerod Santo: Yeah, but when you're VP of engineering you're not a backend dev either.Shawn Wang: Yeah.Jerod Santo: So you're kind of both ascending to that degreeShawn Wang: Backends devs will never report to you, let's put it that way.Jerod Santo: Okay. Fair.Shawn Wang: [laughter] But somehow, frontend devs have to report to backend devs, for some reason; just because they're superior, or something. I don't know, it's just like an unspoken thing... It's a very impolite conversation, but hey, it's a reality, man.Jerod Santo: So do you see this personally, or do you see this by looking around?Shawn Wang: Yeah.Jerod Santo: Yeah. You felt like you had reached a ceiling.Shawn Wang: Well, again, this is very impolite; there's a ton of ways to succeed, and there are definitely exceptions. Emily Nakashima at Honeycomb - former frontend person, now VP of engineering. I don't know, I could have done that. I have interest in backend and I'm pursuing that. So I will say that - this is a soft ceiling, it's a permeable ceiling. It's not a hard ceiling.Jerod Santo: Sure.Shawn Wang: But there's a ceiling though, because you can see the numbers.Adam Stacoviak: What is it in particular the VP of engineering does that would make a frontender less likely to have that role? What specifically? I mean, engineering is one of the things, right? Commanding the software... Which is not necessarily frontend.Jerod Santo: Well, frontend is also an engineering discipline.Adam Stacoviak: I guess it kind of depends on the company, too. Honeycomb is probably a different example.Shawn Wang: I haven't been a VP of engineering, so I only have some theories. I suggest you just ask the next VP of engineering that you talk to, or CTO.Adam Stacoviak: Yeah.Jerod Santo: Yeah. That'd be a good one to start asking people.Adam Stacoviak: What do you do here? What is it you do here?Shawn Wang: What is it you do here?Jerod Santo: Exactly.Shawn Wang: [laughs]Adam Stacoviak: Well, I just wondered if there was a specific skillset that happens at that VP of engineering level that leads more towards a backender being more likely than a frontender to get hired into the role.Shawn Wang: I think there's some traditional baggage. Power structures persist for very long times... And for a long time UX and frontend was just not valued. And we're like maybe five years into the shift into that. It's just gonna take a long time.Jerod Santo: I agree with that. So tell us what you're up to now. You said you're doing workflows... I saw a quick lightning talk; you were talking about "React for the backend." So you're very much taking your frontend stuff into the backend here, with React for the backend. Tell us about that.Shawn Wang: Let's go for it. So at Netlify and at AWS I was essentially a developer advocate for serverless. So this is very cool - it does pay-as-you-go compute, and you can do a lot of cool stuff with it. But something that was always at the back of my mind bothering me, that serverless does not do well, is long-running jobs. It just does not do well. You have to chain together a bunch of stuff, and it's very brittle; you cannot test it... It's way more expensive than you would do in a normal environment.Jerod Santo: Yeah.Shawn Wang: And it made me realize that in this move to take apart everything and make everything as a service, we have gained scalability, but we've lost basically everything else. And what I was trying to do was "How do we reconstruct the experience of the monolith? What are the jobs to be done?" When you break it down, what does a computer do for you, and what is not adequately addressed by the ecosystem?I went through the exercise... I wrote a blog post called "Reconstructing the monolith, and I actually listed it out." So what are the jobs of cloud for a computer? You want static file serving, you want functions, you want gateway, you want socket management, job runners, queue, scheduler, cold storage, hot storage. There's meta jobs like error logging, usage logging, dashboarding, and then edge computing is like a unique to cloud thing. But everything else, you can kind of break it up and you can locate it on one machine, or you can locate it on multiple machines, some of them owned by you, some of them not owned by you.The thing that serverless -- that had a whole in the ecosystem was job running. Not good. Basically, as an AWS developer right now, the answer is you set a CloudWatch schedule function, and you pull an endpoint, and that should read some states from a database, and check through where you are, and compute until the 15-minute timeout for Lambda, and then save it back in, and then wait for the next pull, and start back up again. Super-brittle, and just a terrible experience; you would never want to go this way.[01:00:08.13] The AWS current response to that is AWS Step Functions, which is a JSON graph of what happens after the other, and this central orchestrator controls all of that. I think we could do better, and that's eventually what got me to temporal. So essentially, this blog post that I wrote - people found me through that, and hired both our head of product and myself from this single blog post. So it's probably the highest ROI blog post I've ever written.Jerod Santo: Wow. That's spectacular.Shawn Wang: It's just the VC that invested in Temporal. So what Temporal does is it helps you write long-running workflows in a doable fashion; every single state transition is persisted to a database, in idiomatic code. So idiomatic Java, idiomatic Go, idiomatic JavaScript, and PHP. This is different from other systems, because other systems force you to learn their language. For Amazon, you have to learn Amazon States Language. For Google Workflows - Google Workflows has a very long, very verbose JSON and YAML language as well.And these are all weird perversions of -- like, you wanna start simple; JSON is very simple, for doing boxes and arrows, and stuff like that... But you start ending up having to handwrite the AST of a general-purpose programming language, because you want variables, you want loops, you want branching, you want all that god stuff. And the best way to model asynchronous and dynamic business logic is with a general-purpose programming language, and that's our strong opinion there.So Temporal was created at Uber; it runs over 300 use cases at Uber, including driver onboarding, and marketing, and some of the trips stuff as well. It was open source, and adopted at Airbnb, and Stripe, and Netflix, and we have all those case studies on -- DoorDash as well, by the way, runs on the Uber version of Temporal.Jerod Santo: There you go, Adam.Shawn Wang: And yeah, they spun out to a company two years ago, and we're now trying to make it as an independent cloud company. And again, the

I libri, gli articoli, i post sono tutti ottimi strumenti per imparare. Ma non c'è nulla come mettere mani sul codice. Se poi il codice mima qualcosa di molto simile ad un dominio reale meglio ancora. Tutorial, direte voi. Vero, ma i tutorial hanno un grosso limite, ci guidano passo passo, e fondamentalmente ci inducono a spegnere il cervello.Con Mariano Calandra discutiamo di qualcosa che va oltre il classico tutorial, LiveProject un progetto editoriale di Manning. Ci addentriamo inoltre nei meandri di AWS Lambda e Step Function.Link citati durante la puntata:- Develop Microservices on AWS with Lambda and StepFunctions https://www.manning.com/liveprojectseries/develop-microservices-ser- Introduzione ai LiveProject https://liveproject.manning.com/- AWS Lambda https://aws.amazon.com/lambda/- AWS Step Functions https://aws.amazon.com/step-functions/- AWS X-Ray https://aws.amazon.com/xray/- lumigo https://lumigo.io/

This week we discuss AWS Step Functions, VMware Tanzu Community Edition and Zoom's M&A Strategy. Plus, some thoughts on car batteries… Rundown AWS Step Functions Supports 200 AWS Services To Enable Easier Workflow Automation (https://aws.amazon.com/blogs/aws/now-aws-step-functions-supports-200-aws-services-to-enable-easier-workflow-automation/) Introducing VMware Tanzu Community Edition (https://tanzu.vmware.com/content/blog/vmware-tanzu-community-edition-announcement) Tanzu Community Edition (https://tanzucommunityedition.io/) Zoom M&A And that's that, as the Zoom deal to buy Five9 is called off – TechCrunch (https://techcrunch.com/2021/09/30/and-thats-that-as-the-zoom-deal-to-buy-five9-is-called-off/) Zoom loses Five9 - leaves the cloud contact center business open to innovative alternatives (https://diginomica.com/zoom-loses-five9-leaves-cloud-contact-center-business-open-innovative-alternatives) Telegram added 70M new users amid six-hour WhatsApp outage (https://9to5mac.com/2021/10/05/telegram-added-70m-new-users-amid-six-hour-whatsapp-outage/e) Relevant to your interests Announcing Trusted Cloud Principles (https://trustedcloudprinciples.com/) Australian Bureau of Statistics runs 2021 Census on the AWS Cloud (https://aws.amazon.com/blogs/publicsector/australian-bureau-of-statistics-runs-2021-census-on-the-aws-cloud/) "A New Strategy, R2" (https://redmonk.com/rstephens/2021/09/30/a-new-strategy-r2/) Cloudflare's Disruption (https://stratechery.com/2021/cloudflares-disruption/) PSPDFkit raises $116M, its first outside money; now nearly 1B people use apps powered by its collaboration, signing and markup tools (https://techcrunch.com/2021/10/01/pspdfkit-raises-116m-its-first-outside-money-now-nearly-1b-people-use-apps-powered-by-its-collaboration-signing-and-markup-tools/) Microsoft announces Office 2021 features and pricing (https://www.theverge.com/22704168/microsoft-office-2021-features-pricing-release-date) Paperlike, the Screen Protector for iPad: write and draw like on paper (https://paperlike.com/) Microsoft sets Oct. 5 as Windows 11 launch date (https://www.axios.com/microsoft-oct-windows-11-launch-date-7202798e-fa64-421a-835a-4c625c97e728.html?utm_source=newsletter&utm_medium=email&utm_campaign=newsletter_axioslogin&stream=top) COVID Breathalyzers Could Transform Rapid Testing (https://spectrum.ieee.org/covid-breathalyzers-could-transform-rapid-testing) AWS Mistakes (https://news.ycombinator.com/item?id=28493193) The Verica Open Incident Database (https://www.thevoid.community/) Developer-focused infrastructure security platform Mondoo raises $15M (https://venturebeat.com/2021/10/05/developer-focused-infrastructure-security-platform-mondoo-raises-15m/) 1 big thing: Enterprise software's reawakening (https://www.axios.com/newsletters/axios-pro-rata-846feca0-b1b3-40c1-92b0-88c5cd3c0d46.html?chunk=0&utm_term=emshare#story0) FB Outage Understanding How Facebook Disappeared from the Internet (https://blog.cloudflare.com/october-2021-facebook-outage/) Tools to explore BGP (https://jvns.ca/blog/2021/10/05/tools-to-look-at-bgp-routes/) Facebook is down, along with Instagram, WhatsApp, Messenger, and Oculus VR (https://www.theverge.com/2021/10/4/22708989/instagram-facebook-outage-messenger-whatsapp-error) Security The entirety of Twitch has reportedly been leaked | VGC (https://www.videogameschronicle.com/news/the-entirety-of-twitch-has-reportedly-been-leaked/) DeFi bug accidentally gives $90 million to users, founder begs them to return it (https://www.cnbc.com/2021/10/01/defi-protocol-compound-mistakenly-gives-away-millions-to-users.html) Hackers rob thousands of Coinbase customers using MFA flaw (https://www.bleepingcomputer.com/news/security/hackers-rob-thousands-of-coinbase-customers-using-mfa-flaw/) Company That Routes Billions of Text Messages Quietly Says It Was Hacked (https://www.vice.com/en/article/z3xpm8/company-that-routes-billions-of-text-messages-quietly-says-it-was-hacked) Nonsense There are six internet links on my office on wheels. Seven when Starlink arrives. (https://ghuntley.com/internet/) Australia accelerates its plans to allow international travel. (https://www.nytimes.com/2021/10/01/world/australia/australia-international-travel-covid.html) As of today, Australia has 5 time zones once again. (https://pbs.twimg.com/media/FAv7UPuVEAA87S9.jpg) April Fools' copy-paste button for lazy programmers now actually for sale (https://www.cnet.com/news/april-fools-copy-paste-button-for-lazy-programmers-now-actually-for-sale/?PostType=link&ServiceType=twitter&UniqueID=5A6C2A44-2481-11EC-97B3-AFC2BDCD475E&ftag=COS-05-10aaa0b&TheTime=2021-10-03T19:37:32&utm_source=newsletter&utm_medium=email&utm_campaign=newsletter_axioslogin&stream=top) Sponsors strongDM — Manage and audit remote access to infrastructure. Start your free 14-day trial today at strongdm.com/SDT (http://strongdm.com/SDT) CBT Nuggets — Training available for IT Pros anytime, anywhere. Start your 7-day Free Trial today at cbtnuggets.com/sdt (https://cbtnuggets.com/sdt) Conferences KubeCon October 11-15 Virtual and In Person (https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/) GitOpsDays Community Special: GitOps One-Stop Shop Event October 20 (https://www.gitopsdays.com/) MongoDB.local London 2021 (https://events.mongodb.com/dotlocallondon) - November 9, 2021 THAT Conference comes to Texas January 17-20, 2022 (https://that.us/activities/call-for-counselors/tx/2022) Listener Feedback James wants you to wort at GoCardless in London as a IT Engineering Manager (https://boards.greenhouse.io/gocardless/jobs/3190118.), IT Support Manager (https://boards.greenhouse.io/gocardless/jobs/3501701) or Business Systems Engineer - HR Systems (https://boards.greenhouse.io/gocardless/jobs/3334891) SDT news & hype Join us in Slack (http://www.softwaredefinedtalk.com/slack). Send your postal address to stickers@softwaredefinedtalk.com (mailto:stickers@softwaredefinedtalk.com) and we will send you free laptop stickers! Follow us on Twitch (https://www.twitch.tv/sdtpodcast), Twitter (https://twitter.com/softwaredeftalk), Instagram (https://www.instagram.com/softwaredefinedtalk/), LinkedIn (https://www.linkedin.com/company/software-defined-talk/) and YouTube (https://www.youtube.com/channel/UCi3OJPV6h9tp-hbsGBLGsDQ/featured). Brandon built the Quick Concall iPhone App (https://itunes.apple.com/us/app/quick-concall/id1399948033?mt=823) and he wants you to buy it for $0.99. Use the code SDT to get $20 off Coté's book, (https://leanpub.com/digitalwtf/c/sdt) Digital WTF (https://leanpub.com/digitalwtf/c/sdt), so $5 total. Become a sponsor of Software Defined Talk (https://www.softwaredefinedtalk.com/ads)! TriggerMesh is hiring! (https://twitter.com/sebgoa/status/1437722696536797185) Recommendations Brandon: Bayco LBC-400 Recessed Light Bulb Changer (https://www.amazon.com/gp/product/B000GAUSCO/ref=ppx_yo_dt_b_asin_title_o02_s00?ie=UTF8&psc=1) Drones changing bulbs (https://twitter.com/AgBioWorld/status/1435753919817429000) Matt: Lee “Scratch” Perry A Live Injection: Anthology 1968-1979 (https://open.spotify.com/album/1W3cKgwqmprjq24abdSThm?si=ZOBFrj2FQpqxdjylhaUFEQ&dl_branch=1) Cloud Native AF: Farmers Don't Care About Kubernetes with Mike Dvorkin (https://www.cloudnativeaf.com/4) (https://www.cloudnativeaf.com/4) Photo Credit (https://unsplash.com/photos/ovGrEUgrkyE) Photo Credit (https://unsplash.com/photos/--kQ4tBklJI)

This is the audio version of the essay I published on Monday.I'm excited to finally share why I've joined Temporal.io as Head of Developer Experience. It's taken me months to precisely pin down why I have been obsessed with Workflows in general and Temporal in particular.It boils down to 3 core opinions: Orchestration, Event Sourcing, and Workflows-as-Code.Target audience: product-focused developers who have some understanding of system design, but limited distributed systems experience and no familiarity with workflow engines30 Second PitchThe most valuable, mission-critical workloads in any software company are long-running and tie together multiple services. Because this work relies on unreliable networks and systems: You want to standardize timeouts and retries. You want offer "reliability on rails" to every team. Because this work is so important: You must never drop any work. You must log all progress. Because this work is complex: You want to easily model dynamic asynchronous logic... ...and reuse, test, version and migrate it. Finally, you want all this to scale. The same programming model going from small usecases to millions of users without re-platforming. Temporal is the best way to do all this — by writing idiomatic code known as "workflows".Requirement 1: OrchestrationSuppose you are executing some business logic that calls System A, then System B, and then System C. Easy enough right?But: System B has rate limiting, so sometimes it fails right away and you're just expected to try again some time later. System C goes down a lot — and when it does, it doesn't actively report a failure. Your program is perfectly happy to wait an infinite amount of time and never retry C. You could deal with B by just looping until you get a successful response, but that ties up compute resources. Probably the better way is to persist the incomplete task in a database and set a cron job to periodically retry the call.Dealing with C is similar, but with a twist. You still need B's code to retry the API call, but you also need another (shorter lived, independent) scheduler to place a reasonable timeout on C's execution time since it doesn't report failures when it goes down.Do this often enough and you soon realize that writing timeouts and retries are really standard production-grade requirements when crossing any system boundary, whether you are calling an external API or just a different service owned by your own team.Instead of writing custom code for timeout and retries for every single service every time, is there a better way? Sure, we could centralize it!We have just rediscovered the need for orchestration over choreography. There are various names for the combined A-B-C system orchestration we are doing — depending who you ask, this is either called a Job Runner, Pipeline, or Workflow.Honestly, what interests me (more than the deduplication of code) is the deduplication of infrastructure. The maintainer of each system no longer has to provision the additional infrastructure needed for this stateful, potentially long-running work. This drastically simplifies maintenance — you can shrink your systems down to as small as a single serverless function — and makes it easier to spin up new ones, with the retry and timeout standards you now expect from every production-grade service. Workflow orchestrators are "reliability on rails".But there's a risk of course — you've just added a centralized dependency to every part of your distributed system. What if it ALSO goes down?Requirement 2: Event SourcingThe work that your code does is mission critical. What does that really mean? We cannot drop anything. All requests to start work must either result in error or success - no "it was supposed to be running but got lost somewhere" mismatch in expectations. During execution, we must be able to resume from any downtime. If any part of the system goes down, we must be able to pick up where we left off. We need the entire history of what happened when, for legal compliance, in case something went wrong, or if we want to analyze metadata across runs. There are two ways to track all this state. The usual way starts with a simple task queue, and then adds logging:(async function workLoop() { const nextTask = taskQueue.pop() await logEvent('starting task:', nextTask.ID) try { await doWork(nextTask) // this could fail! catch (err) { await logEvent('reverting task:', nextTask.ID, err) taskQueue.push(nextTask) } await logEvent('completed task:', nextTask.ID) setTimeout(workLoop, 0) })() But logs-as-afterthought has a bunch of problems. The logging is not tightly paired with the queue updates. If it is possible for one to succeed but the other to fail, you either have unreliable logs or dropped work — unacceptable for mission critical work. This could also happen if the central work loop itself goes down while tasks are executing. At the local level, you can fix this with batch transactions. Between systems, you can create two-phase commits. But this is a messy business and further bloats your business code with a ton of boilerplate — IF (a big if) you have the discipline to instrument every single state change in your code. The alternative to logs-as-afterthought is logs-as-truth: If it wasn't logged, it didn't happen. This is also known as Event Sourcing. We can always reconstruct current state from an ever-growing list of eventHistory:(function workLoop() { const nextTask = reconcile(eventHistory, workStateMachine) doWorkAndLogHistory(nextTask, eventHistory) // transactional setTimeout(workLoop, 0) })() The next task is strictly determined by comparing the event history to a state machine (provided by the application developer). Work is either done and committed to history, or not at all.I've handwaved away a lot of heavy lifting done by reconcile and doWorkAndLogHistory. But this solves a lot of problems: Our logs are always reliable, since that is the only way we determine what to do next. We use transactional guarantees to ensure that work is either done and tracked, or not at all. There is no "limbo" state — at the worst case, we'd rather retry already-done work with idempotency keys than drop work. Since there is no implicit state in the work loop, it can be restarted easily on any downtime (or scaled horizontally for high load). Finally, with standardized logs in our event history, we can share observability and debugging tooling between users. You can also make an analogy to the difference between "filename version control" and git — Using event histories as your source of truth is comparable to a git repo that reflects all git commits to date.But there's one last problem to deal with - how exactly should the developer specify the full state machine?Requirement 3: Workflows-as-CodeThe prototypical workflow state machine is a JSON or YAML file listing a sequence of steps. But this abuses configuration formats for expressing code. it doesn't take long before you start adding features like conditional branching, loops, and variables, until you have an underspecified Turing complete "domain specific language" hiding out in your JSON/YAML schema.[ { "first_step": { "call": "http.get", "args": { "url": "https://www.example.com/callA" }, "result": "first_result" } }, { "where_to_jump": { "switch": [ { "condition": "${first_result.body.SomeField < 10}", "next": "small" }, { "condition": "${first_result.body.SomeField < 100}", "next": "medium" } ], "next": "large" } }, { "small": { "call": "http.get", "args": { "url": "https://www.example.com/SmallFunc" }, "next": "end" } }, { "medium": { "call": "http.get", "args": { "url": "https://www.example.com/MediumFunc" }, "next": "end" } }, { "large": { "call": "http.get", "args": { "url": "https://www.example.com/LargeFunc" }, "next": "end" } } ] This example happens to be from Google, but you can compare similar config-driven syntaxes from Argo, Amazon, and Airflow. The bottom line is you ultimately find yourself hand-writing the Abstract Syntax Tree of something you can read much better in code anyway:async function dataPipeline() { const { body: SomeField } = await httpGet("https://www.example.com/callA") if (SomeField < 10) { await httpGet("https://www.example.com/SmallFunc") } else if (SomeField < 100) { await httpGet("https://www.example.com/MediumFunc") } else { await httpGet("https://www.example.com/BigFunc") } } The benefit of using general purpose programming languages to define workflows — Workflows-as-Code — is that you get to the full set of tooling that is already available to you as a developer: from IDE autocomplete to linting to syntax highlighting to version control to ecosystem libraries and test frameworks. But perhaps the biggest benefit of all is the reduced need for context switching from your application language to the workflow language. (So much so that you could copy over code and get reliability guarantees with only minor modifications.)This config-vs-code debate arises in multiple domains: You may have encountered this problem in AWS provisioning (CloudFormation vs CDK/Pulumi) or CI/CD (debugging giant YAML files for your builds). Since you can always write code to interpret any declarative JSON/YAML DSL, the code layer offers a superset of capabilities.The Challenge of DIY SolutionsSo for our mission critical, long-running work, we've identified three requirements: We want an orchestration engine between services. We want to use event sourcing to track and resume system state. We want to write all this with code rather than config languages. Respectively, these solve the pain points of reliability boilerplate, implementing observability/recovery, and modeling arbitrary business logic.If you were to build this on your own: You can find an orchestration engine off the shelf, though few have a strong open source backing. You'd likely start with a logs-as-afterthought system, and accumulating inconsistencies over time until they are critical enough to warrant a rewrite to a homegrown event sourcing framework with stronger guarantees. As you generalize your system for more use cases, you might start off using a JSON/YAML config language, because that is easy to parse. If it were entrenched and large enough, you might create an "as Code" layer just as AWS did with AWS CDK, causing an impedance mismatch until you rip out the underlying declarative layer. Finally, you'd have to make your system scale for many users (horizontal scaling + load balancing + queueing + routing) and many developers (workload isolation + authentication + authorization + testing + code reuse).Temporal as the "iPhone solution"When Steve Jobs introduced the iPhone in 2007, he introduced it as "a widescreen iPod with touch controls, a revolutionary mobile phone, and a breakthrough internet communications device", before stunning the audience: "These are not three separate devices. This is ONE device."This is the potential of Temporal. Temporal has opinions on how to make each piece best-in-class, but the tight integration creates a programming paradigm that is ultimately greater than the sum of its parts: You can build a UI that natively understands workflows as potentially infinitely long running business logic, exposing retry status, event history, and code input/outputs. You can build workflow migration tooling that verifies that old-but-still-running workflows have been fully accounted for when migrating to new code. You can add pluggable persistence so that you are agnostic to what databases or even what cloud you use, helping you be cloud-agnostic. You can run polyglot teams — each team can work in their ideal language, and only care about serializable inputs/outputs when calling each other, since event history is language-agnostic. There are more possibilities I can't talk about yet. The Business Case for TemporalA fun anecdote about how I got the job: through blogging.While exploring the serverless ecosystem at Netlify and AWS, I always had the nagging feeling that it was incomplete and that the most valuable work was always "left as an exercise to the reader". The feeling crystallized when I rewatched DHH's 2005 Ruby on Rails demo and realized that there was no way the serverless ecosystem could match up to it. We broke up the monolith to scale it, but there were just too many pieces missing.I started analyzing cloud computing from a "Jobs to Be Done" framework and wrote two throwaway blogposts called Cloud Operating Systems and Reconstituting the Monolith. My ignorant posting led to an extended comment from a total internet stranger telling me all the ways I was wrong. Lenny Pruss, who was ALSO reading my blogpost, saw this comment, and got Ryland to join Temporal as Head of Product, and he then turned around and pitched (literally pitched) me to join.One blogpost, two jobs. Learn in Public continues to amaze me by the luck it creates.Still, why would I quit a comfy, well-paying job at Amazon to work harder for less money at a startup like this? Extraordinary people. At its core, betting on any startup is betting on the people. The two cofounders of Temporal have been working on variants of this problem for over a decade each at AWS, Microsoft, and Uber. They have attracted an extremely high caliber team around them, with centuries of distributed systems experience. I report to the Head of Product, who is one of the fastest scaling executives Sequoia has ever seen. Extraordinary adoption. Because it reinvents service orchestration, Temporal (and its predecessor Cadence) is very horizontal by nature. Descript uses it for audio transcription, Snap uses it for ads reporting, Hashicorp uses it for infrastructure provisioning, Stripe uses it for the workflow engine behind Stripe Capital and Billing, Coinbase uses it for cryptocurrency transactions, Box uses it for file transfer, Datadog uses it for CI/CD, DoorDash uses it for delivery creation, Checkr uses it for background checks. Within each company, growth is viral; once one team sees successful adoption, dozens more follow suit within a year, all through word of mouth. Extraordinary results. After migrating, Temporal users report production issues falling from once-a-week to near-zero. Accidental double-spends have been discovered and fixed, saving millions in cold hard cash. Teams report being able to move faster, thanks to testing, code reuse, and standardized reliability. While the value of this is hard to quantify, it is big enough that users organically tell their friends and list Temporal in their job openings. Huge potential market growth. The main thing you bet on when it comes to Temporal is that its primary competition really is homegrown workflow systems, not other engines like Airflow, AWS Step Functions, and Camunda BPMN. In other words, even though Temporal should gain market share, the real story is market growth, driven by the growing microservices movement and developer education around best-in-class orchestration. At AWS and Netlify, I always felt like there was a missing capability in building serverless-first apps — duct-taping functions and cronjobs and databases to do async work — and it all fell into place the moment I saw Temporal. I'm betting that there are many, many people like me, and that I can help Temporal reach them. High potential value capture. Apart from market share and market growth, any open source project has the additional challenge of value capture, since users can self-host at any time. I mostly subscribe to David Ulevitch's take that open source SaaS is basically outsourcing ops. I haven't talked about Temporal's underlying architecture but it has quite a few moving parts and takes a lot of skill and system understanding to operate. For reasons I won't get into, Temporal scales best on Cassandra and that alone is enough to make most want to pay someone else to handle it. Great expansion opportunities. Temporal is by nature the most direct source of truth on the most valuable, mission critical workflows of any company that adopts it. It can therefore develop the most mission critical dashboard and control panel. Any source of truth also becomes a natural aggregation point for integrations, leaving open the possibility of an internal or third party service marketplace. With the Signals and Queries features, Temporal easily gets data in and out of running workflows, making it an ideal foundation for the sort of human-in-the-loop work for the API Economy. Imagine toggling just one line of code to A/B test vendors and APIs, or have Temporal learn while a domain expert manually executes decision processes and take over when it has seen enough. As a "high-code" specialist in reliable workflows, it could be a neutral arms dealer in the "low-code" gold rush, or choose to get into that game itself. If you want to get really wild, the secure distributed execution model of Workflow workers could be facilitated by an ERC-20 token. (to be clear... everything listed here is personal speculation and not the company roadmap) There is much work to do, though. Temporal Cloud needs a lot of automation and scaling before it becomes generally available. Temporal's UI is in the process of a full rewrite. Temporal's docs need a lot more work to fully explain such a complex system with many use cases. Temporal still doesn't have a production-ready Node.js or Python SDK. And much, much, more to do before Temporal's developer experience becomes accessible to the majority of developers.If what I've laid out excites you, take a look at our open positions (or write in your own!), and join the mailing list!Further Reading Orchestration Yan Cui's guide to Orchestration vs Choreography InfoQ: Coupling Microservices - a non-Temporal focused discussion of Orchestration A Netflix Guide to Microservices Event Sourcing Martin Fowler on Event Sourcing Kickstarter's guide to Event Sourcing Code over Config ACloudGuru's guide to Terraform, CloudFormation, and AWS CDK Serverless Workflow's comparison of Workflow specification formats Temporal Dealing with failure - when to use Workflows The macro problem with microservices - Temporal in context of microservices Designing A Workflow Engine from First Principles - Temporal Architecture Principles Writing your first workflow - 20min code video Case studies and External Resources from our users

最新情報を "ながら" でキャッチアップ！ ラジオ感覚放送 「毎日AWS」 おはようございます、火曜日担当の古川です。 今日は 6/18に出たアップデートをピックアップしてご紹介 感想は Twitter にて「#サバワ」をつけて投稿してください！ ■ トークスクリプト https://blog.serverworks.co.jp/aws-update-2021-06-18-1 ■ UPDATE PICKUP AWS Step FunctionsにてWorkflow Studioが使用可能に ■ サーバーワークスSNS Twitter / Facebook ■ サーバーワークスブログ サーバーワークスエンジニアブログ

Tenemos la visita de Guillermo Menendez, Solutions Architect del área de Energía y nos viene a contar sobre los procesos de MLOps para machine learning e inteligencia artificial.Guillermo Menendez - @_gmcorral_Guillermo Menendez Corral es un solutions architect en Amazon Web Services dedicado al área de Energía. Tiene mas de 15 años de experiencia diseñando y construyendo aplicativos y actualmente ayuda a grandes clientes en sus arquitecturas de cloud, con un foco en Analytics y Machine Learning.Rodrigo Asensio - @rasensioBasado en Barcelona, España, Rodrigo es responsable de un equipo de Solution Architecture del segmento Enterprise que ayuda a grandes clientes en sus migraciones masivas al cloud, en transformación digital y proyectos de innovación.LinksSageMaker para preparar , crear entrenar y desplegar modelos de ML https://aws.amazon.com/sagemaker/SageMaker Feature Store para almacenar features de nuestro dataset https://aws.amazon.com/sagemaker/feature-store/SageMaker Autopilot para construir y entrenar modelos automaticamente https://aws.amazon.com/sagemaker/autopilot/SageMaker Studio el IDE para ML https://aws.amazon.com/sagemaker/studio/SageMaker Model Monitor para monitorizar modelos de ML en producción https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.html SageMaker Pipelines CI/CD para Machine Learning https://aws.amazon.com/sagemaker/pipelines/ AWS Step Functions para orquestación de CI/CD de ML https://aws.amazon.com/step-functions/Managed Apache Airflow para orquestación de CI/CD de ML https://aws.amazon.com/managed-workflows-for-apache-airflow/SageMaker Ground Truth preparacion y etiquetado de datos https://aws.amazon.com/sagemaker/groundtruth/SageMaker Pre Processing para pre procesamiento de datos https://aws.amazon.com/blogs/aws/amazon-sagemaker-processing-fully-managed-data-processing-and-model-evaluation/SageMaker Debugger para poder visualizar detalles del entrenamiento del modelo https://aws.amazon.com/sagemaker/debugger/SageMaker Experiments para grabar y categorizar experimentos https://aws.amazon.com/blogs/aws/amazon-sagemaker-experiments-organize-track-and-compare-your-machine-learning-trainings/Managed Spot Training para abaratar costes https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html

Sean Doyle (@cloudosmotic) presents "Fun with AWS Step Functions". Sean Doyle is a Principal Cloud Architect with over 20 years in the IT industry ranging from Systems Engineering to Automation and DevOps. Sean also held the titles of AWS Partner Ambassador and AWS Partner AI/ML Blackbelt. In this episode, Sean provides an overview of the AWS Step Functions service, the various use cases that they can potentially be used for, as well as a demonstration of using AWS Step Functions for a serverless ETL Workflow to prepare data for Machine Learning. Resources: https://aws.amazon.com/step-functions/faqs/ https://aws.amazon.com/step-functions/use-cases/ https://docs.aws.amazon.com/step-functions/latest/dg/sample-project-express-selective-checkpointing.html#sample-project-express-selective https://docs.aws.amazon.com/step-functions/latest/dg/sample-lambda-orchestration.html#sample-lambda-orchestration-create https://github.com/awslabs/aws-data-wrangler

In this Episode of AWS TechChat, we welcome Shai Perednik to the TechChat team as we perform a tech round up from September through to October of 2020. We covered a plethora of topics today, we started the show talking about price reductions with AWS IOT Events dropping a mammoth 86%. Amazon Connect our ever popular phone system in the cloud decreased telephony costs for outbound calls across six countries in Europe. We then moved to compute, more AWS Graviton 2 instances in more regions. Amazon RDS now has Graviton2 based instances with MySQL and Aurora and a new EC2 instance, the T4G has launched. AWS Backup now is crash consistent for Windows instances and we speak of AWS File Gateway performance upgrades. Apache Flink Kinesis consumer now supports EFO and HTTP 2 data retrieval. Lightsail offers an AMI like experience with OS blueprints and Amazon CloudWatch adds Prometheus support. On the container front, there are now security groups and customizable service IP ranges for EKS. AWS Lambda adds support in the console for AWS Step Functions, making the process of authoring state machines and Lambda functions even easier and there is now a quick start for Microsoft SQL Server Always On under Linux (Ubuntu). Amazon CloudFront launched Origin Shield which is another caching layer that collapses request from Edge Locations and Regional Edge Caches to the closest Regional Edge Cache to the origin, providing an increased cache hit ratio and a reduction of load on the origin. A great feature release if your application has a global audience Lastly Amazon EventBridge now offers DLQ support, wahoo.

This week, first we talk Enterprise News, discussing Acunetix new data retention policies, 5 things you should ask your web app pen test provider, Microsoft's open source tool for sniffing out Windows 10 bugs, Datadog unveils support for distributed tracing for AWS Step Functions via AWS X-Ray, and Gravwell's Data Fusion platform breaks the mold of legacy data ingestion engines! In our second segment, we welcome Ferruh Mavituna, CEO of Netsparker, to discuss Current Security Needs Of Modern Enterprise Companies! In our final segment, we welcome Jimmy Mesta, Director of Security Research at Signal Sciences, to discuss Securing Enterprise Digital Transformations!   Show Notes: https://securityweekly.com/esw199 Visit https://securityweekly.com/netsparker to learn more about them! Visit https://securityweekly.com/signalsciences to learn more about them!   Visit https://www.securityweekly.com/esw for all the latest episodes! Follow us on Twitter: https://www.twitter.com/securityweekly Like us on Facebook: https://www.facebook.com/secweekly

This week, first we talk Enterprise News, discussing Acunetix new data retention policies, 5 things you should ask your web app pen test provider, Microsoft's open source tool for sniffing out Windows 10 bugs, Datadog unveils support for distributed tracing for AWS Step Functions via AWS X-Ray, and Gravwell's Data Fusion platform breaks the mold of legacy data ingestion engines! In our second segment, we welcome Ferruh Mavituna, CEO of Netsparker, to discuss Current Security Needs Of Modern Enterprise Companies! In our final segment, we welcome Jimmy Mesta, Director of Security Research at Signal Sciences, to discuss Securing Enterprise Digital Transformations!   Show Notes: https://securityweekly.com/esw199 Visit https://securityweekly.com/netsparker to learn more about them! Visit https://securityweekly.com/signalsciences to learn more about them!   Visit https://www.securityweekly.com/esw for all the latest episodes! Follow us on Twitter: https://www.twitter.com/securityweekly Like us on Facebook: https://www.facebook.com/secweekly

Acunetix new data retention policies, 5 Things to Ask Your Web App Pen Test Provider, Microsoft's open source tool for sniffing out Windows 10 bugs, Datadog unveils support for distributed tracing for AWS Step Functions via AWS X-Ray, Gravwell's Data Fusion platform breaks the mold of legacy data ingestion engines, and more!   Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw199

Acunetix new data retention policies, 5 Things to Ask Your Web App Pen Test Provider, Microsoft's open source tool for sniffing out Windows 10 bugs, Datadog unveils support for distributed tracing for AWS Step Functions via AWS X-Ray, Gravwell's Data Fusion platform breaks the mold of legacy data ingestion engines, and more!   Visit https://www.securityweekly.com/esw for all the latest episodes! Show Notes: https://securityweekly.com/esw199

最新情報を "ながら" でキャッチアップ！ ラジオ感覚放送 「毎日AWS！」 おはようございます、サーバーワークスの加藤です。 今日は 9/3 に出たアップデート7件をご紹介。 感想は Twitter にて「#サバワ」をつけて投稿してください！ ■ UPDATE ラインナップ AWS Step Functions がペイロードサイズを 256KB に拡張 Amazon WorkDocs で全てのディレクトリユーザーの自動プロビジョニングをサポート BYOL を行った Amazon WorkSpaces で Microsoft Office Professional を利用できるように Amazon Polly のニューラルテキスト読み上げ機能が東京を含む複数リージョンで利用可能に AWS Elemental Media Live が AVC UHD 出力に対応 Amazon Aurora PostgreSQL が RDKit 拡張をサポート Amazon Aurora が PostgreSQL の新しいバージョンをサポート ■ サーバーワークスSNS Twitter / Facebook ■ サーバーワークスブログ サーバーワークスエンジニアブログ

In this Episode of AWS TechChat, Shane and Gabe perform a tech round up from July through to August of 2020 We started with containers as we spoke about ACK or the AWS Controller for Kubernetes which means you can leverage AWS services directly in or your Kubernetes applications. Amazon EKS now supports UDP load balancing with the NLB and sticking with Amazon EKS, it is now included in Compute Savings plan A huge win for customers. Still with containers, Amazon ECS now has launched the new ECS Optimized Inferentia AMI making it easier for customers to run Inferentia based containers on ECS. Compute wise, Inferentia based EC2 instances (Inf1) are now available in additional regions and EC2 Launch is now at v2 with a range of new features, I particularly like you can rename the administrator account. Graviton 2 based instances make their way in to a heap more regions, that is super awesome and they can now be consumed by Amazon EKS, and sticking with EKS with Fargate it can now mount AWS EFS based file systems Amazon Bracket is generally available which is development environment for you to explore and build quantum algorithms, test them on quantum circuit simulators, and run them on different quantum hardware technologies. We introduced a new EBS storage class, IO2 which fits in between IO1 and GP2 based volumes. It has 5 9s of durability and up to 64 000IOPS per volume On the development front, AWS Step Functions adds support for string manipulation, new comparison operators, and improved output processing, Amazon API Gateway adds integration with five AWS services, meaning you no longer need to proxy through code as well as Amazon API GW supporting enhanced observability via access logs. Amazon Lightsail now has a CDN, Lightsail CDN, which is backed by Amazon CloudFront it offers three fixed-price data plans, including an introductory plan that’s free for 12 months CloudFront, adds additional geo-location headers for more fine grain geo-tagging as-well as cache key and origin request policies providing more options to control and configure headers, query strings, and cookies that can be used to compute the cache key or forwarded to your origin. Lastly we introduced AWS Glue version 2 which has some some sizeable changes around functionality, cost and speed.

最新情報を "ながら" でキャッチアップ！ ラジオ感覚放送 「毎日AWS！」 おはようございます、サーバーワークスの加藤です。 今日は 8/13 に出たアップデート11件をご紹介。 感想は Twitter にて「#サバワ」をつけて投稿してください！ ■ UPDATE ラインナップ マネージド量子コンピューティングサービス Amazon Braket が一般利用可能に (ハンズオンブログ) AWS Transfer Family に暗号化アルゴリズムを選択するための事前定義されたセキュリティポリシーを追加 Amazon EC2 に新しいインスタンスタイプが追加 - 第2世代AMD EPYCプロセッサを利用した Amazon EC2 C5ad が利用可能に Amazon QuickSight がフォルダーや新しい計算エディタなどいくつかの新しい機能を追加 Amazon EKS が NLB を用いた UDPロードバランシングに対応 AWS Lambda がイベントソースとして新たに Amazon Managed Streaming for Apache Kafka をサポート Amazon EC2 Inf1 インスタンスが東京リージョンを含む複数リージョンで利用可能に AWS Systems Manager Explorer がAWSサポートケースのサマリを提供開始 AWS Step Functions が文字列操作、新しい比較演算子、改善されたエクスポート処理をサポート Amazon API Gateway がアクセスログを通して拡張された監視機能をサポートするように AWS Solutions Library に機械学習による予測精度の向上という新しいソリューションが追加 ■ サーバーワークスSNS Twitter / Facebook ■ サーバーワークスブログ サーバーワークスエンジニアブログ

Netflix runs all of its infrastructure on Amazon Web Services. This includes business logic, data infrastructure, and machine learning. By tightly coupling itself to AWS, Netflix has been able to move faster and have strong defaults about engineering decisions. And today, AWS has such an expanse of services that it can be used as a platform to build custom tools.Metaflow is an open source machine learning platform built on top of AWS that allows engineers at Netflix to build directed acyclic graphs for training models. These DAGs get deployed to AWS as Step Functions, a serverless orchestration platform.Savin Goyal is a machine learning engineer with Netflix, and he joins the show to talk about the machine learning challenges within Netflix, and his experience working on Metaflow. We also talk about DAG systems such as AWS Step Functions and Airflow.

Muchas veces existen soluciones pre-configuradas dentro de los proveedores de nube, que son una forma rápida de completar una solución completa, en este caso vamos a hablar de cómo hacer streaming de video desde AWS. De dónde sale esta necesidad, que es el video bajo demanda. Son varios los componentes que se utilizan dentro de este script, tales como: AWS Step Functions, AWS Elemental MediaConvert, AWS Lambda, DynamoDB, CloudWatch, Amazon Simple Notification Service, Amazon S3, Amazon Simple Queue Serice, Amazon Cloud Front. Si gustan revisar esta implementación, les dejó el enlace en la notas del episodio: https://aws.amazon.com/es/solutions/implementations/video-on-demand-on-aws/ Mi correo: — jonatan@simplementenube.com Para más información puedes visitar: — https://jonatanchinchilla.com/podcasts/

Disponible también en: Google Podcast Spotify Apple Podcast Google Podcast Spotify Apple Podcast Muchas veces existen soluciones pre-configuradas dentro de los proveedores de nube, que son una forma rápida de completar una solución completa, en este caso vamos a hablar de cómo hacer streaming de video desde AWS.Son varios los componentes que se utilizan dentro de este script, tales como: AWS Step Functions, AWS Elemental MediaConvert, AWS Lambda, DynamoDB, CloudWatch, Amazon Simple Notification Service, Amazon S3, Amazon Simple Queue Serice, Amazon Cloud Front.Si gustan revisar esta implementación, les dejó el enlace en la notas del episodio:https://aws.amazon.com/es/solutions/implementations/video-on-demand-on-aws/  Mi correo: jonatan@simplementenube.com  Para más información puedes visitar: https://jonatanchinchilla.com/podcasts/

This week Tim Bray joins Simon to discuss a new capability in AWS Step Functions. Express Workflows are a new type of AWS Step Functions workflow type that cost-effectively orchestrate AWS compute, database, and messaging services at event rates greater than 100,000 events per second. Express Workflows automatically start in response to events such as HTTP requests via Amazon API Gateway, AWS Lambda requests, AWS IoT Rules Engine actions, and over 100 other AWS and SaaS event sources from Amazon EventBridge. Express Workflows is suitable for high-volume event processing workloads such as IoT data ingestion, streaming data processing and transformation, and high-volume microservices orchestration. https://aws.amazon.com/blogs/aws/new-aws-step-functions-express-workflows-high-performance-low-cost/

In this episode, I cover new features on Amazon Personalize (recommendation & personalization), Amazon Polly (text to speech), and Apache MXNet (Deep Learning). I also point out new notebooks for Amazon SageMaker Debugger, a couple of recent videos that I recorded, and an upcoming SageMaker webinar.⭐️⭐️⭐️ Don't forget to subscribe to be notified of future episodes ⭐️⭐️⭐️Additional resources mentioned in the podcast:* Amazon Polly Brand Voice: https://aws.amazon.com/blogs/machine-learning/build-a-unique-brand-voice-with-amazon-polly/* Amazon SageMaker Debugger notebooks: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/sagemaker-debugger* Numpy for Apache MXNet: https://medium.com/apache-mxnet/a-new-numpy-interface-for-apache-mxnet-incubating-dbb4a4096f9f* Automating Amazon SageMaker workflows with AWS Step Functions: https://www.youtube.com/watch?v=0kMdOi69tjQ* Deploying Machine Learning Models with mlflow and Amazon SageMaker: https://www.youtube.com/watch?v=jpZSp9O8_ew* SageMaker webinar on February 27th: https://pages.awscloud.com/AWS-Online-Tech-Talks_2020_0226-MCL.htmlThis podcast is also available in video: https://youtu.be/KE83Aw6UvHk For more content, follow me on:* Medium https://medium.com/@julsimon * Twitter https://twitter.com/@julsimon

FINRA ingests up to 100 billion trading data records daily that need to be obfuscated securely when moving them. This data replication and obfuscation supports production data analysis, setup environments for user acceptance testing (UAT), and troubleshooting production issues. With the automated, one-click solution, FINRA teams can leverage the pipelines and within hours (versus days) get data for analysis, development, and testing. The solution is serverless, leveraging AWS Step Functions, AWS Lambda, Amazon ECS/AWS Fargate, Amazon SNS, and Amazon SQS. FINRA plans to open source this by the end of this year so attendees will be able to adopt the solution.

Machine learning involves more than just training models; you need to source and prepare data, engineer features, select algorithms, train and tune models, and then deploy those models and monitor their performance in production. Learn how Amazon Consumer Payments uses Amazon SageMaker, AWS Glue, AWS Step Functions, Amazon API Gateway, AWS Lambda, AWS Batch, Amazon Elastic Container Registry (Amazon ECR), and AWS CloudFormation to automate a CI/CD framework for business-critical machine learning workloads at scale.

This presentation was recorded prior to re:Invent. Home buyers value the ability to experience a home before visiting it. To empower them to do so, Zillow launched its 3D Home tour product nationwide in March 2019. Zillow built a highly performant, scalable, and reliable computer vision and media processing pipeline powered by AWS Step Functions, AWS Lambda, Amazon DynamoDB, Amazon CloudWatch, and Amazon S3. This architecture enabled Zillow to provide an immersive experience that continues to enhance and transform the home buying process. In this talk, Zillow discusses the evaluation process for its chosen technologies, and it provides an in-depth breakdown of the architecture and resulting cost savings.

Symantec's Norton Storage Platform offers online backup as a service to protect data from accidental deletion and malware. In this session, hear from Norton about the challenges it had managing Cassandra clusters at scale and why it migrated its metadata database from Cassandra to DynamoDB. Norton then dives into an innovative method it used to migrate its data using AWS Step Functions.

Although this Global Partner Summit session is open to anyone, it is geared toward current and potential AWS Partner Network Partners. Serverless technology allows you to build modern applications with increased agility and lower total cost of ownership. You can focus on product innovation and shorten your time-to-market without worrying about provisioning, maintaining, and scaling servers for backend components such as compute, databases, storage, stream processing, and message queueing. In this session, learn how to start innovating with serverless services like AWS Lambda, Amazon API Gateway, Amazon EventBridge, and AWS Step Functions. We conclude the session with customer stories of accelerating innovation and driving business value with the help of our APN partners.

Lazy Loading routes has been the de facto way of reducing the bundle sizes in Angular when it comes to code splitting. Angular makes its so much easier to achieve that with its powerful Angular Router’s API and Schematics. Code splitting non route based modules is something which is possible in Angular but lacks simpler API. In this talk, we will first look at how to code split on Component level, and then look at how Angular Loadable makes it simpler and adds tons of features required for component level code splitting. It takes its inspiration from React Loadable’s features and Angular Router’s configurations, and simplifies even more with Schematics for adding ngx-loadable and generating lazy loaded modules. Zama Khan Mohammed is a Software Architect, author of the book, Angular Projects (https://angularprojects.com), mentor, technical writer and a father. He has a Master’s Degree in Computer Science and has loads of experience in Software Development using technologies such as Angular, React, D3.js, AWS (Step Functions, Lambda, CloudFormation, S3) etc. He has a keen interest in Software Development as well as Machine Learning, and he feels passionate about teaching and mentoring his interests to others. --- Video of episode: https://youtu.be/oeT6r7Qd6OI --- Support this podcast: https://anchor.fm/angularair/support

Jeremy chats with Rowan Udell about the benefits of state machines, the core functionality and advanced features of AWS Step Functions, and some recommendations for building smarter serverless workflows.

Join Dr. Pete and Shane as they cover the latest AWS Tech Round-Up. In this episode, they touch on topics relevant to all gamuts of IT. They start the show with a deep dive of AWS Step Functions Local and AWS Step Functions support for Tag Based Permissions. They then pivot to ALB (Application Load Balancer) announcement as ALB now supports ARR (Advanced Request Routing). They wrap up the episode with an introduction to AWS Deep Learning Containers.

Keeping track of state and orchestrating the components of a distributed application is complex. AWS Step Functions makes the job simpler, faster, and more intuitive. In this session, learn how to leverage AWS Step Functions to design and run workflows for your serverless, containerized, and instance-based architectures. We explore practical applications of orchestration spanning different industries and workloads. For each, we walk through the architecture, lessons learned, and business outcomes. Expect to leave this session with a practical understanding of how to use orchestration to express your application's business logic more productively while improving its resilience.

Data and events are the lifeblood of any modern application. By using stateless, loosely coupled microservices communicating through events, developers can build massively scalable systems that can process trillions of requests in seconds. In this talk, we cover design patterns for using Amazon SQS, Amazon SNS, AWS Step Functions, AWS Lambda, and Amazon S3 to build data processing and real-time notification systems with unbounded scale and serverless cost characteristics. We also explore how these approaches apply to practical use cases, such as training machine learning models, media processing, and data cleansing.

Learn how you can build, train, and deploy machine learning workflows for Amazon SageMaker on AWS Step Functions. Learn how to stitch together services, such as AWS Glue, with your Amazon SageMaker model training to build feature-rich machine learning applications, and you learn how to build serverless ML workflows with less code. Cox Automotive also shares how it combined Amazon SageMaker and Step Functions to improve collaboration between data scientists and software engineers. We also share some new features to build and manage ML workflows even faster.

Learn how Fox and Discovery modernized their media processing workflows to positively impact operations and business results. In this session, we examine each company's production architecture and learn how they utilize AWS services such as AWS Elemental Media Services, AWS Lambda, AWS Step Functions, Amazon API Gateway, and container toolsets. You also get insights into new business capabilities enabled by their AWS serverless architecture, including automation of content assembly and quality control as well as increased customer engagement with personalization and improved processing performance.

This week Simon takes you though an extensive set of things new and interesting - hopefully something for everyone! Shownotes: Amazon Aurora Backtrack – Turn Back Time - AWS News Blog | https://aws.amazon.com/blogs/aws/amazon-aurora-backtrack-turn-back-time/ Amazon Aurora Publishes General, Slow Query and Error Logs to Amazon CloudWatch | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-aurora-publishes-general-slow-query-and-error-logs-to-amazon-cloudwatch/ Amazon RDS for Oracle Supports New X1 and X1e Instance Types | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-rds-for-oracle-supports-new-x1-and-x1e-instance-types/ Amazon RDS Supports Outbound Network Access from PostgreSQL Read Replicas for Commercial Regions | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-rds-supports-outbound-network-access-from-postgresql-read-replicas/ Amazon RDS Database Preview Environment is now available | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-rds-database-preview-environment-now-available/ Modifiable sqlnet.ora Parameters for RDS Oracle | https://aws.amazon.com/about-aws/whats-new/2018/05/modifiable-sqlnet-ora-parameters-for-rds-oracle/ AWS Database Migration Service Supports IBM Db2 as a Source | https://aws.amazon.com/about-aws/whats-new/2018/04/aws-dms-supports-ibm-db2-as-a-source/ AWS Database Migration Service Supports R4 Instance Types | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-database-migration-service-supports-r4-instance-types/ Amazon Redshift Adds New CloudWatch Metrics for Easy Visualization of Cluster Performance | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-redshift-adds-new-cloudwatch-metrics-for-easy-visualization-of-cluster-performance/ AWS Storage Gateway VTL Expands Backup Application Support with NovaStor DataCenter | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-storage-gateway-vtl-adds-support-for-novastor-datacenter/ Amazon Macie Adds New Dashboard Making It Easier to Identify Publicly Accessible Amazon Simple Storage Service Objects | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-macie-adds-new-dashboard-to-identify-publicly-accessible-amazon-simple-storage-service-objects/ Introducing Optimize CPUs for Amazon EC2 Instances | https://aws.amazon.com/about-aws/whats-new/2018/05/introducing-optimize-cpus-for-amazon-ec2-instances/ Announcing General Availability of Amazon EC2 Bare Metal Instances | https://aws.amazon.com/about-aws/whats-new/2018/05/announcing-general-availability-of-amazon-ec2-bare-metal-instances/ Introducing Amazon EC2 Fleet | https://aws.amazon.com/about-aws/whats-new/2018/04/introducing-amazon-ec2-fleet/ Introducing Amazon EC2 C5d Instances | https://aws.amazon.com/about-aws/whats-new/2018/05/ introducing-amazon-ec2-c5d-instances/ Amazon EC2 Spot Instances now Support Red Hat BYOL | https://aws.amazon.com/about-aws/whats-new/2018/04/amazon-ec2-spot-instances-now-support-red-hat-byol/ Get Latest Console Output on EC2 Instances | https://aws.amazon.com/about-aws/whats-new/2018/05/get-latest-console-output-on-ec2-instances/ Amazon ECS Service Discovery Supports Bridge and Host Container Networking Modes | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-ecs-service-discovery-supports-bridge-and-host-container-/ Amazon ECS Adds SSM Parameter for Launching ECS-Optimized EC2 Instances using AWS CloudFormation | https://aws.amazon.com/about-aws/whats-new/2018/05/ecs-adds-ssm-parameter-for-launching-ecs-optimized-ec2-amis/ AWS Elastic Beanstalk Supports Apache Tomcat v8.5 and Apache HTTP Server v2.4 | https://aws.amazon.com/about-aws/whats-new/2018/05/elastic-beanstalk-supports-apache-tomcat-v8_5-and-apache-http-server-v2_4/ AWS Elastic Beanstalk Adds Support for Health Events in Amazon CloudWatch Logs | https://aws.amazon.com/about-aws/whats-new/2018/05/AWS-elastic-beanstalk-adds-support-for-health-events-in-amazon-cloudWatch-logs/ Application Load Balancer Announces Slow Start Support for its Load Balancing Algorithm | https://aws.amazon.com/about-aws/whats-new/2018/05/application-load-balancer-announces-slow-start-support/ Application Load Balancer and Network Load Balancer now Support Resource- and Tag-based Permissions | https://aws.amazon.com/about-aws/whats-new/2018/05/alb-and-nlb-now-support-resource--and-tag-based-permissions/ Amazon Simple Queue Service Server-Side Encryption is Now Available in 13 Additional Regions | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-sqs-server-side-encryption-is-now-available-in-16-aws-regions/ AWS CloudFormation now Supports AWS Budgets as a Resource for CloudFormation Templates, Stacks, and StackSets | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-cloudformation-supports-aws-budgets-resource/ AWS CloudFormation Supports FIPS 140-2 Validated API Endpoints in US Regions | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-cloudformation-supports-fips-140-2-validated-api-endpoints-i/ AWS Auto Scaling Scaling Plans Can Now be Created Using AWS CloudFormation | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-auto-scaling-scaling-plans-can-now-be-created-using-aws-cloudformation/ Amazon Translate is now supported in AWS Mobile SDK for Android and iOS | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-translate-is-now-supported-in-aws-mobile-sdk-for-android-and-ios/ Amazon AppStream 2.0 Now Supports Administrative Controls for Limiting File Movement, Clipboard, and Printing | https://aws.amazon.com/about-aws/whats-new/2018/05/appstream2-now-supports-administrative-controls-for-limiting-file-movement-cipboard-printing/ Amazon Inspector Adds Ability to Run Security Assessments on Amazon EC2 Instances Without Adding Tags | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-inspector-adds-ability-to-run-security-assessments-on-amazon-ec2-instances-without-adding-tags/ The AWS Organizations Console is Now Available in Eight New Languages | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-organizations-console-now-available-eight-new-languages/ Amazon Cognito Now Supports the Capability to Add Custom OIDC-providers | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-cognito-now-supports-the-capability-to-add-custom-oidc-providers/ Alexa now lets you schedule 1:1 meetings and move meetings in your calendar | https://aws.amazon.com/about-aws/whats-new/2018/05/alexa-now-lets-you-schedule-1-1-meetings-and-move-meetings-in-yo/ Amazon Chime brings Meetings and Chat to Your Browser with a New Web Application | https://aws.amazon.com/about-aws/whats-new/2018/05/Amazon_Chime_brings_Meetings_and_Chat_to_Your_Browser_with_a_New_Web_Application/ The AWS Secrets Manager Console Is Now Available in Italian and Traditional Chinese | https://aws.amazon.com/about-aws/whats-new/2018/05/new-aws-secrets-manager-console-language-support-italian-traditional-chinese/ Amazon Inspector Now Supports Amazon Linux 2018.03 and Ubuntu 18.04 LTS | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-inspector-now-supports-amazon-linux-2018-03-and-ubuntu-18-04/ Higher Throughput Workflows for AWS Step Functions | https://aws.amazon.com/about-aws/whats-new/2018/05/higher-throughput-workflows-for-aws-step-functions/ New Developer Preview: Use Amazon Polly Voices in Alexa Skills | https://aws.amazon.com/about-aws/whats-new/2018/05/new-developer-preview-use-amazon-polly-voices-in-alexa-skills/ AWS CodeCommit Supports Branch-Level Permissions | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-codecommit-supports-branch-level-permissions/ AWS CodeBuild Adds Support for Windows Builds | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-codebuild-adds-support-for-windows-builds/ AWS CodeBuild Supports VPC Endpoints | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-codebuild-supports-vpc-endpoints/ AWS CodeBuild Now Supports Local Testing and Debugging | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-codebuild-now-supports-local-testing-and-debugging/ AWS CodePipeline Supports Push Events from GitHub via Webhooks | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-codepipeline-supports-push-events-from-github-via-webhooks/ AWS SAM CLI Simplifies Building Serverless Apps with the SAM init Command | https://aws.amazon.com/about-aws/whats-new/2018/04/aws-sam-cli-releases-new-init-command/ Optimized TensorFlow 1.8 Now Available in the AWS Deep Learning AMIs to Accelerate Training on Amazon EC2 C5 and P3 Instances | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-deep-learning-amis-optimized-tensorflow-18/ AWS Systems Manager Helps You Collect Inventory on All Managed Instances in a Single Click | https://aws.amazon.com/about-aws/whats-new/2018/05/systems-manager-adds-1-click-experience-to-enable-inventory/ Amazon WorkSpaces Introduces Mouse Support on iPad Devices | https://aws.amazon.com/about-aws/whats-new/2018/05/Amazon-WorkSpaces-Introduces-Mouse-Support-on-iPad-Devices/ Lambda@Edge Adds Support for Node.js v8.10 | https://aws.amazon.com/about-aws/whats-new/2018/05/lambda-at-edge-adds-support-for-node-js-v8-10/ Major Updates Come to Script Canvas with Lumberyard Beta 1.14 – Available Now | https://aws.amazon.com/about-aws/whats-new/2018/05/major-updates-come-to-script-canvas-with-lumberyard-beta-114-available-now/ Introducing Real-Time IoT Device Monitoring with Kinesis Data Analytics | https://aws.amazon.com/about-aws/whats-new/2018/05/introducing-real-time-iot-device-monitoring-with-kinesis-data-analytics/ Introducing the IoT Device Simulator | https://aws.amazon.com/about-aws/whats-new/2018/05/introducing-the-iot-device-simulator/ What's New with Amazon FreeRTOS - Amazon Web Services | https://aws.amazon.com/about-aws/whats-new/2018/05/esp32-qualified-for-amazon-freertos/ Introducing Amazon GameLift Target Tracking for Autoscaling | https://aws.amazon.com/about-aws/whats-new/2018/05/introducing-amazon-gamelift-target-tracking-for-autoscaling/ Copying Encrypted Amazon EBS Snapshots Under Custom CMK now Completes Faster With Less Storage | https://aws.amazon.com/about-aws/whats-new/2018/05/copying-encrypted-amazon-ebs-snapshots-under-custom-cmk-now-completes-faster-with-less-storage/ Amazon GuardDuty Adds Capability to Automatically Archive Findings | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-guardduty-adds-capability-to-automatically-archive-findings1/ Monitor your Reserved Instance coverage by receiving alerts via AWS Budgets | https://aws.amazon.com/about-aws/whats-new/2018/05/reserved-instance-coverage-alerts-via-aws-budgets/ Stream Real-Time Data in Apache Parquet or ORC Format Using Amazon Kinesis Data Firehose | https://aws.amazon.com/about-aws/whats-new/2018/05/stream_real_time_data_in_apache_parquet_or_orc_format_using_firehose/ Amazon Kinesis Data Analytics Application Monitoring using Amazon CloudWatch | https://aws.amazon.com/about-aws/whats-new/2018/05/kinesis_data_analytics_application_monitoring_using_cloudwatch/ Amazon EMR now supports M5 and C5 instances | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-emr-now-supports-m5-and-c5-instances/ Thinkbox Deadline Supports 3ds Max 2019 and Vue 2016 | https://aws.amazon.com/about-aws/whats-new/2018/05/thinkbox-deadline-supports-3ds-max-2019-and-vue-2016/ Amazon Elasticsearch Service Offers Additional Cost Savings with Reserved Instances | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-elasticsearch-service-offers-additional-cost-savings-with-reserved-instances/ Announcing Amazon EC2 H1 Instances Price Reduction | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-ec2-h1-pricing-reduction/ AWS Service Catalog Launches Ability to Copy Products Across Regions | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-service-catalog-launches-ability-to-copy-products-across-regions/ AWS Service Catalog Introduces the Ability to Chain the Launch of Multiple Products | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-service-catalog-introduces-the-ability-to-chain-the-launch-of-multiple-products/ Amazon DynamoDB Encryption Client Is Now Available in Python | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-dynamodb-encryption-client-available-in-python/ AWS Config Adds Support for AWS X-Ray | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-config-adds-support-for-aws-x-ray/ AWS Config Adds Support for AWS Lambda | https://aws.amazon.com/about-aws/whats-new/2018/04/aws-config-adds-support-for-aws-lambda/ AWS Amplify Introduces Service Worker Capabilities to Enable High-Quality Progressive Web Apps. | https://aws.amazon.com/about-aws/whats-new/2018/05/aws-amplify-service-worker-capabilities/ Amazon Sumerian is Generally Available | https://aws.amazon.com/about-aws/whats-new/2018/05/amazon-sumerian-is-generally-available/

How can you manage preventative maintenance without having to learn low level SCADA languages? Simon speaks with Shane Baldacchino (Solutions Architect, AWS) about applying AWS Greengrass, AWS Step Functions and AWS Lambda@Edge. Watch Shane’s AWS DevDay Session: https://aws.amazon.com/devday/australia/on-demand-2017/ AWS IoT Blog: https://aws.amazon.com/blogs/iot/

The IARPA Machine Intelligence from Cortical Networks (MICrONS) program is a research endeavor created to improve neurally-plausible machine-learning algorithms by understanding data representations and learning rules used by the brain through structurally and functionally interrogating a cubic millimeter of mammalian neocortex. This effort requires efficiently storing, visualizing, and processing petabytes of neuroimaging data. The Johns Hopkins University Applied Physics Laboratory (APL) has developed an open-source, highly available service to manage these data, called the Boss. The Boss uses AWS to provide a cloud-native spatial database with an innovative storage hierarchy and auto-scaling capability to balance cost and performance. This system extensively uses serverless components to meet both scalability and cost requirements. In this session, we provide an overview of the Boss, and we focus on how the APL used Amazon DynamoDB, AWS Lambda, and AWS Step Functions for several high-throughput components of the system. We discuss both the challenges and successes with serverless technologies.

Serverless and AWS Lambda specifically enable developers to build super-scalable application components with minimal effort. You can use Amazon Kinesis and Amazon SQS to create a universal event stream to orchestrate Lambdas into much more complex applications. Now, using AWS Step Functions, we can build large distributed applications with Lambdas using visual workflows. See how Step Functions are different from Amazon SWF, how to get started with Step Functions, and how to use them to take your Lambda-based applications to the next level. We start with a few granular functions and stitch them up using Step Functions. As we build out the application, we add monitoring to ensure that changes we make actually improve things, not make them worse. Leave the session with actionable learnings for using Step Functions in your environment right away.   Session sponsored by Datadog

As serverless architectures become more popular, customers need a framework of patterns to help them identify how they can leverage AWS to deploy their workloads without managing servers or operating systems. This session describes reusable serverless patterns while considering costs. For each pattern, we provide operational and security best practices and discuss potential pitfalls and nuances. We also discuss the considerations for moving an existing server-based workload to a serverless architecture. The patterns use services like AWS Lambda, Amazon API Gateway, Amazon Kinesis Streams, Amazon Kinesis Analytics, Amazon DynamoDB, Amazon S3, AWS Step Functions, AWS Config, AWS X-Ray, and Amazon Athena. This session can help you recognize candidates for serverless architectures in your own organizations and understand areas of potential savings and increased agility. What's new in 2017: using X-Ray in Lambda for tracing and operational insight; a pattern on high performance computing (HPC) using Lambda at scale; how a query can be achieved using Athena; Step Functions as a way to handle orchestration for both the Automation and Batch patterns; a pattern for Security Automation using AWS Config rules to detect and automatically remediate violations of security standards; how to validate API parameters in API Gateway to protect your API back-ends; and a solid focus on CI/CD development pipelines for serverless, which includes testing, deploying, and versioning (SAM tools).

Serverless architectures let you build and deploy applications and services with infrastructure resources that require zero administration. In the past, you had to provision and scale servers to run your application code, install and operate distributed databases, and build and run custom software to handle API requests. Now, AWS provides a stack of scalable, fully-managed services that eliminates these operational complexities.  In this session, you will learn about serverless architectures, their benefits, and the basics of the AWS's serverless stack (e.g., AWS Lambda, Amazon API Gateway, and AWS Step Functions). We will discuss how to use serverless architectures for a variety of use cases including data processing, website backends, serverless applications, and “operational glue.” You will also get practical tips and tricks, best practices, and architecture patterns that you can take back and implement immediately.

Do you have daily, weekly, or monthly tasks that you would like to automate? Looking to link two or more AWS Lambda functions in long-running processes? Are you building applications using microservices or containers? AWS Step Functions makes it easy to coordinate the components of distributed applications using visual workflows. In this session, we will share how AWS customers like Yelp are using Step Functions to reliably build and scale multi-step applications such as order processing, report generation, and data transformation. You will learn how to reduce the time to deploy and change microservices and serverless applications, and automate IT infrastructure for improved resilience and security.

With serverless computing, you can build and run applications without the need for provisioning or managing servers. Serverless computing means that you can build web, mobile, and IoT backends, run stream processing or big data workloads, run chatbots, and more. In this session, learn how to get started with serverless computing with AWS Lambda, which lets you run code without provisioning or managing servers. We introduce you to the basics of building with Lambda. As part of that, we show how you can benefit from features such as continuous scaling, built-in high availability, integrations with AWS and third-party apps, and subsecond metering pricing. We also introduce you to the broader portfolio of AWS services that help you build serverless applications with Lambda, including Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, and more.

Vivint Solar is a leading full-service residential solar provider in the United States with more than 100,000 solar systems to its credit. Vivint Solar uses MicroStrategy on AWS to keep track of internal processes, including operations, finance, customer support, and human resources. With MicroStrategy on AWS, Vivint Solar could deploy a fully configured MicroStrategy environment in just an hour, giving their IT team more time to focus on other high-value projects. Today, Vivint Solar uses over 25 different AWS tools and services including, AWS Lambda, AWS Step Functions, Amazon SQS, AWS CloudFormation, and AWS CodeDeploy to track and analyze their data. Join us in this session to learn how Vivint Solar is using analytics to transform the way they do business and revolutionize the way people think about renewable energy. Session sponsored by MicroStrategy

AWS Step Functions makes it easy to coordinate AWS Lambda functions, run business workflows, and automate operations using state machines. The product has been live in the field for a year now, and it's time to learn from what people are doing with it. In this session, we'll present a series of innovative, high-impact, and just plain crazy applications of state machines from all sorts of customers. Guest-star Coca-Cola will show how they used Step Functions to support vending loyalty programs and product nutrition syndication. Managing application state is a central problem of building the serverless apps of the future; learn how Step Functions does it simply and scalably. Warning: there will be code!

AWS Step Functions is a new, fully-managed service that makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Step Functions is a reliable way to connect and step through a series of AWS Lambda functions so that you can build and run multi-step applications in a matter of minutes. This session shows how to use AWS Step Functions to create, run, and debug cloud state machines to execute parallel, sequential, and branching steps of your application, with automatic catch and retry conditions. We share how customers are using AWS Step Functions to reliably scale multi-step applications such as order processing, report generation, and data transformation–all without managing any infrastructure.

AWS Step Functions is a new, fully managed service that makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Step Functions is a reliable way to coordinate components and step through the functions of your application. A graphical console helps you arrange and visualize the components of your application as a series of steps. Step Functions automatically triggers and tracks each step and retries when there are errors so that your application executes in order―and as expected―every time. This session shows how to use Step Functions to create, run, and debug multi-service applications in a matter of minutes. We also share how customers are using Step Functions to reliably build and scale multi-step applications such as order processing, report generation, and data transformation―and to innovate faster.