Werner Vogels’ Post

"Since 2018, we have increasingly leveraged Rust for critical workloads across various [AWS] services like S3, EC2, DynamoDB, Lambda, Fargate, and Nitro, especially in scenarios where hardware costs are expected to dominate over time." We've seen a lot of success with Rust at AWS, including our work on Firecracker, on Lambda's container dataplane, and on many other systems we've built. I love the fact that we can get memory safety without compromising performance or efficiency. I also enjoy seeing how much less time my teams spend tuning runtimes or debugging memory issues. I also really appreciate this sentiment from Werner's post: "... this is not a call to rewrite everything in Rust. ... It’s about using the right tool for the right job. This means questioning the status quo, and continuously looking for ways to incrementally optimize your systems – to tinker with things and measure what happens." Make decisions about programming languages the same way you make all critical engineering decisions: with data!

We always hear about the importance of continuous learning, so it's nice to actually see it in action from senior leadership. This inspired me to make my first pull request in #Rust to add #Markdown support for the CLI. As someone who spent a long time working in tech docs, there's a special place in my heart for markup that's easy to read and write without any button clicks. Full disclaimer, I'm new to Rust, and got a lot of help from Amazon Q and Claude 3 Sonnet. So if you know a better way to do this, make another pull request to improve it. You won't hurt my feelings. I'm here for iterative improvement. https://lnkd.in/gHvZaA42

Efficiences not only improve performance, it also reduces costs and computational power consumption. “If you take nothing else away from this post, I encourage you to actively look for efficiencies in all aspects of your work. Tinker. Measure. Because everything has a cost, and cost is a pretty good proxy for a sustainable system.” #softwaredevelopment

This is a fun blog post about first steps with Rust -- and what looks like a legitimately useful tool!

I'm honored to be mentioned by Werner Vogels in his latest blog post, where he explores the importance of tinkering and the potential of Rust for building efficient and sustainable systems. The post highlights how experimentation and leveraging new technologies can drive innovation in software development. If you're interested in the future of building systems, this is a must-read! 🦀

I love this hands-on approach! Tinkering is where the magic happens, it's how we truly grasp new technologies and spark innovation. Rust is a fantastic choice for building efficient and reliable systems, and turning a proof of concept into a working CLI is a great way to learn the language. We should encourage this culture of experimentation and continuous learning within our teams. It's not just about the end product, but the journey of exploration and discovery that leads to true mastery. Kudos Werner on building Distill CLI and sharing it with the community! 👏 #RustLang #DevOps #ContinuousLearning

Interesting article by Werner Vogels , on the new Distill CLI, which can be used for media summerization (think getting notes out of a recorded meeting). But I found his explanation of the rapid growth, and the amazing performance gains and sustainable nature of the programming language Rust very enlightening #aws #rust

🚀 Exciting news in the Rust and AWS communities! 🚀 On June 8th, Werner Vogels announced **distill CLI**, an efficient, Rust-powered tool for media summarization. 📜🔧 Check out his blog for more details: [Introducing Distill CLI](https://lnkd.in/dfUT4cmf) Notably, companies like Discord and Figma have achieved remarkable performance improvements by adopting Rust. Discord moved their Read States service from Go to Rust, resulting in a 10x speed increase and nearly 100x reduction in worst tail latencies. Similarly, Figma rewrote performance-sensitive parts of their multiplayer service in Rust, seeing a 6x reduction in peak average CPU usage per machine. 🌟💪 AWS is also embracing Rust with the general availability of Cargo support in CodeArtifact, enabling the storage of Rust libraries (crates) in CodeArtifact. 📦✨ More info: [AWS CodeArtifact and Cargo Support](https://lnkd.in/dYY_fgtU) As more customers leverage Rust for their critical workloads, AWS is providing robust building blocks. AWS Lambda, for instance, can now process HTTP events more efficiently with Rust. 🚀⚡️ Learn more here: [Rust HTTP Events in AWS Lambda](https://lnkd.in/diubf8bM) #RustLang #AWS #Serverless #Performance #CloudComputing #Innovation #TechNews #CodeArtifact #DistillCLI

I'm excited to announce the release of my newest article! 🚀 In this piece, I explore the smooth fusion of Celery, FastAPI, Docker, and Flower for the purpose of coordinating, running, and overseeing asynchronous tasks. Covering everything from task prioritization to live tracking, the article reveals how these tools combine to create high-performance, expandable applications. I invite you to give it a read and let me know your impressions! Should you find it insightful, please consider giving it a thumbs up, sharing it, or leaving a comment. #celery #fastapi #flower #machinelearning #mlops

Innovating Chaos Engineering: A Vision for Randomness, Parallelism Hello, tech enthusiasts! 👋 In the ever-evolving landscape of Chaos Engineering, we’re on the cusp of something exciting. Today, let’s explore a groundbreaking concept: the integration of randomness and parallelism into Chaos Engineering scenarios. It’s an idea that could redefine how we test and enhance system resilience. 🌪️ Randomness: Imagine Chaos Engineering experiments that embrace unpredictability. The ability to introduce controlled randomness into fault scenarios can bring us closer to real-world chaos, where failures don’t follow predictable patterns. It’s about uncovering vulnerabilities that thrive in the unexpected. 🚀 Parallelism: Modern systems thrive on concurrency. Chaos Engineering should too. The idea of parallelism means we can conduct multiple chaos experiments simultaneously, truly stress-testing our systems’ resilience. Think of it as a way to prepare for handling multiple disruptions happening concurrently. 💡Amazon Web Services (AWS) FIS, Chaos Studio for Microsoft Azure, Litmus, Chaos Mesh by Cloud Native Computing Foundation (CNCF), Harness and ChaosNative : While these open-source frameworks and AWS FIS, Azure Chaos Studio have been instrumental in orchestrating controlled chaos experiments, I’m not sure they currently provide these features. This leads us to the exciting question: could we expand their capabilities to introduce randomness and parallelism? The vision here is not limited to AWS or Azure; it’s a concept that could impact the entire Chaos Engineering landscape. It’s an invitation to the community to join in and share thoughts, insights, and experiences. What could the future of Chaos Engineering look like with these enhancements? How could we collectively push the boundaries of system resilience? Let’s explore this visionary idea together. Share your views, suggestions, and dreams in the comments below. Together, we can shape the future of Chaos Engineering. 💡💬 #ChaosEngineering #Innovation #TechDiscussion #Randomness #Parallelism #AWSFIS #aws #awscloud #azure #kubernetes