Stefano Doni

AI-driven performance optimization. CTO @akamaslabs

[Stefano Doni @stef3a]

Can't wait to join the largest Java developers community in the US!

[Atlanta Java Users Group @atlantajug]

Modern Java apps on K8s often underperform—but tuning matters. 🚀

At #Devnexus, @stef3a from @AkamasLabs shows how AI-driven optimization can unlock 20–50% better JVM performance & efficiency beyond default settings.

🔗https://t.co/bWXTDcWJ1H

🎟️ Tickets https://t.co/cL8NXzyKyy

[KubeFM @K8sFM]

🗣️ @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: https://t.co/Ei5e8wvmdN

[Miguel Ángel Pastor @miguelinlas3]

Cloudspecs: Cloud Hardware Evolution Through the Looking Glass https://t.co/xajSt93g7N

[KubeFM @K8sFM]

🗣️ @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: https://t.co/Ei5e8wvmdN

Read the announcement: https://t.co/V5izhzp7id

[Stefano Doni @stef3a]

@richardstartin So the Datadog agent leverages JFR for data collection? Cool! How does it do that - continous recording on a file, or streaming? It doesn't need to restart the JVM I guess

[Stefano Doni @stef3a]

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?

[Stefano Doni @stef3a]

@ErikGahlin Thanks a lot Erik, exact mode is exactly what I need!

[Stefano Doni @stef3a]

@richardstartin Hi Richard, thx! Good point about overhead, I'll make sure to check with and without. I don't need profiling or thread-level data, I'm using the ContainerCPUUsage event as total CPU usage is enough for my use case, but I need it at finer granularity

[Stefano Doni @stef3a]

@jholusa @ApacheFlink Awesome thank you!

[Stefano Doni @stef3a]

Super happy to share my experience on AI-driven, automated tuning JVM performance and efficiency.

Join me if you're in Milan!

[JUG Milano @jugmilano]

🗓️ Giovedì 23 Ottobre 2025
👉 "Let AI Tune Your JVM: Autonomous Performance for Java App" in presenza e YouTube live!
🙏 presenta @stef3a

Hybrid mode:
🚨 per partecipare in presenza è richiesto questo form:https://t.co/HluDrmTHFN

⚠️
Dettagli: https://t.co/UjyDYcRyPs

[Akamas @AkamasLabs]

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 👇
https://t.co/nyNP3MKglR

[Stefano Doni @stef3a]

@nearyd @brunoborges @AkamasLabs Hi David, happy to chat!

[Akamas @AkamasLabs]

🎯 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 👉 https://t.co/Qrw20yTitS

[Bruno Borges @brunoborges]

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:

➡️ https://t.co/OpqJWS75jM

Just a few minutes of your time.

[Stefano Doni @stef3a]

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!

[Bruno Borges @brunoborges]

#Java on #Kubernetes: Lessons in Performance Engineering with Akamas and Microsoft.

Free webinar with myself and @stef3a --- on September 25th | 9am PT.

Register at --->

https://t.co/FnsbGmBuHt

[Charles 🎉 Frye @charles_irl]

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.

https://t.co/9IDfgGqVFX

[Go @golang]

“Container-aware GOMAXPROCS” by Michael Pratt and Carlos Amedee — https://t.co/KtiJSNu3sy

#golang

[Akamas @AkamasLabs]

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: https://t.co/0o3uKzGX7W

[Volker Simonis @volker_simonis]

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?