@sudheerbhat.bsky.social

If you are running workload that matters from infra footprint perspective on #Java , then should have planned upgrade to Java25 6 months ago. We did the upgrade to 25 from 21 on 2 large footprint services. Throughput is up ~10%, very conservatively. #Java25 1/2

I hope every day you all are trying to cultivate joy. A kindness to a neighbor. A long walk. Poetry. Birdwatching. Meditation. Being silly and playing peekaboo in a checkout line with a cute baby. These are dark times, and joy is something the bastards cannot take from us. Fight for it.

Ran into an interesting thread starvation problem. After some digging, figured out that we had badly written code (when was it not). The take away is simple. Do not block indefinitely on future. DO NOT OVERENGINEER. Async is not easy. #Java

The LLM generated issue summaries/comparison look very bland and I tend to lose interest reading the same. Does anyone else feel the same too? The generated context generally over indexes on a particular aspect. May be I need getting used to, but currently its not helping. #AI

Love Caffeine cache. IMO, it just makes the cut as defacto in process cache impl. However, we only recently learned that for caches which needs to perform evictions (for eg: max size), cache initialized with .executor(Runnable::run) performs much better! #java #cache

5/ In general, work that shortens feedback loops is the most valuable "metaproject" work that can be done on a project. Doesn't matter what feedback loop: testing, compiling, deploying, getting customer feedback, analyzing data, whatever

Watching the tech industry unleash unpredictable software into production in the name of AI adoption, then spend twice as much time and money trying to limit the blast radius, proves humans should be investing in our own intelligence before allowing the machines to mimic us.

Very early prototype. Thought of giving the java-ffi a run. Took the zstd-jni as comparison and asked copilot to generate the ffi version with as minimal garbage as possible. In the first iteration ffi is slightly better than jni! Time to dig into generated code. @java #java #ffi

AI writing is like store-bought cake. It might be perfectly fine, maybe even as good as something you could make yourself, but it’s weird to give it to someone and say it’s homemade

We do some large scale NN inferencing on CPU. For us latency is paramount (sub ms). We have custom #java impl leveraging incubating vector. We ran benchmarks against Triton & ORT. Java impl is around 3 to 4x faster. One may say we haven't optimized the ORT/Triton well 1/2

if you love software and are feeling down about the state of software, find places where people are talking about building stuff, and most importantly, actually building stuff and talking about the specifics of the code

My colleague Sanjay Ghemawat & I have done a fair bit of performance tuning of various pieces of code. We wrote an internal Performance Hints document ~2 years ago as a way of identifying some general principles & we've recently published a version of it externally. Doc: abseil.io/fast/hints.h...

Bild

DRAM prices mooning will hurt everyone and might cause a consumer tech recession on its own in the next 12 months even without the AI bubble popping. Hyperscalers are going to jack up prices for cloud resources, electronics manufacturers (Apple, Samsung, etc.) will raise prices, this is gonna hurt.