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🗣️ @stef3a breaks down why Kubernetes optimization initiatives fail. He identifies two critical barriers: technical complexity of configuring parameters and organizational misalignment between teams with conflicting incentives Watch the interview: ku.bz/rdbv-kvWt

Cloudspecs: Cloud Hardware Evolution Through the Looking Glass cs.cit.tum.de/fileadmin/w00c…

🗣️ @stef3a announces the launch of @akamaslabs Insights, a new platform module for Kubernetes teams to optimize performance and efficiency of Kubernetes applications Watch the interview: ku.bz/rdbv-kvWt Read the announcement: ku.bz/mlYTxPC6x

Hey JVM folks, I'm using JFR to study JVM startup performance. Super convenient, everything in one place. However, CPU usage is rounded to 1s granularity, which is too coarse. Same with jfr print. Any way I can sub-second data?

Super happy to share my experience on AI-driven, automated tuning JVM performance and efficiency. Join me if you're in Milan!

Optimize Kubernetes environments with Akamas & SpeedScale! 🚀 SpeedScale captures real production traffic while Akamas runs AI-driven experiments for continuous optimization. Say goodbye to guesswork! Full blog post 👇 akamas.io/events/java-on-kub…

🎯 What does AI-powered #optimization actually look like? With Akamas, you define the goal — performance, cost, or SLOs — and our AI tunes your entire stack: pods, #JVM, #Kubernetes configs, and more. Watch how it works with @StefanoDoni & @loadtester 👉 akamas.io/resources/autonomo…

Next week, @stef3a and I will be talking about Java on Kubernetes, Performance Challenges and Solutions. We would love to hear from you with this survey: ➡️ docs.google.com/forms/d/e/1F… Just a few minutes of your time.

Join me and the awesome @brunoborges to learn the secrets of JVM performance on K8s! How people configure Java & K8s, JVM horizontal vs vertical scaling, K8s requests&limits, biggest config mistakes people do, future trends of JVM & K8s perf, and more!

I like making GPUs go brrt at @modal. I wrote up what I've learned along the way in an extension to the GPU Glossary -- our "CUDA Docs for Humans". Introducing: the GPU 𝔓𝔢𝔯𝔣𝔬𝔯𝔪𝔞𝔫𝔠𝔢 Glossary. modal.com/gpu-glossary/perf

“Container-aware GOMAXPROCS” by Michael Pratt and Carlos Amedee — go.dev/blog/container-aware-… #golang

Wrong node sizes in #Kubernetes will either squeeze your pods or waste 💰 Autoscaling needs tuning to avoid “stranded capacity.” 🛠️ Choose the right instance types, monitor workloads, and cut costs. 👉 Learn how Akamas can help: hubs.li/Q03BWX-90

In the past, people without JVM knowledge tuned JVMs based on random data from the Internet. Nowadays, people without JVM knowledge and no understanding of LLMs tune JVMs based on recommendations from LLMs which were trained on the same random data. Is this progress?

Performance measurements… and the people who love them blog.cloudflare.com/loving-p…

The case of the vanishing CPU: A Linux kernel debugging story buff.ly/3YqAGry

The series on Chromium, "Inside Look at Modern Web Browser," is a visual treat that gives an overview of what happens when you visit that URL. Browser engines are complex software that uses a mix of languages like C, C , ASM, and others for faster and native performance akin to an OS. The JS engines that are part of these are state-of-the-art work on compilers, JIT, and many advanced topics like SIMD and intrinsics covered under low-level programming and OS. Keeping complexities aside, these articles will give you all you need to understand the amazing engineering inside the browser engines. Repost for broader reach to curious folks and follow for more such interesting engineering about browsers. Part 1 - CPU, GPU, Memory, and multi-process architecture developer.chrome.com/blog/in…

Feature request for the node.js runtime: would be great to see the names of the runtime threads. Super useful to see CPU usage of garbage collector threads from htop @matteocollina The JVM has that since many years - see my post below x.com/stef3a/status/10804059…

Calligraphy with sand x.com/i/status/1851966875531…

Webinar today on Performance Tuning with @martin_spier, former Performance Engineer at Netflix! Join us here: lu.ma/3xnfb05d