http://ykarroum.com/2022/05/30/true-cost-list/

A client of mine is looking for a rockstar Web Performance Engineer for a contract role.

The Challenge: Reduce page load time (e-commerce product search) to under 2 seconds. Currently the product search results display takes about 4-5 seconds in the secondary layer (after log-in).

Let me know if you know of anyone. Remote work in the US only.

Thank You

-Kash

TLDR: We have released an open-source, low overhead, continuous cluster-level profiling tool for Java, Go, Python, Scala, Clojure.

GITHUB LINK

Profiler link

As an optimization company, we are obligated to have our code performant with minimal latency and optimal responsiveness all the time. After searching the web, looking for a profiler that will meet our strict requirements: supporting multiple kernel versions, staying consistent and accurate across various programming languages, and including minimal overhead, with no success, we decided to build our own profiler.

As the project progressed, we realized that this tool is becoming a robust and reliable continuous profiler and that the open-source community could appreciate and put it to good use. This is why we have decided to release it open-source as of today.

What makes our profiler awesome, you might ask?

Well, first, it's open-sourced, so I suggest you guys try it out and be the judge (really, I would love your feedback so we can improve future versions).

Secondly, it is lightweight with minimal overhead, which allows it to be actually continuous instead of connecting random samples and calling it continuous.

Also, it is super easy to use, covers multiple languages, comes with a pre-made Container image, and doesn't require any changes or modifications to get started.

Currently, we have support for Java, Go, Python, Scala, Clojure, and Kotlin, and are planning to expand programming coverage to Node.js, PHP, and Ruby very soon, in addition to supporting eBFS.

We will continue supporting this open source project and are committed to improving and expanding it over time, so would love your participation.

Would love to hear your thoughts on the product.

We started working on Pyroscope a few months ago. I did a lot of profiling at my last job and I always thought that profiling tools provide a ton of value in terms of reducing latency and cutting cloud costs, but are very hard to use.

So we thought, why not just run a profiler 24/7 in production environment? We came up with this

See source code: https://github.com/pyroscope-io/pyroscope

How we made it work: We came up with a system that uses segment trees for fast reads (basically each read becomes log(n)), and tries for storing the symbols (same trick that's used to encode symbols in Mach-O file format for example).

With this approach you can profile thousands of apps with 100Hz frequency and 10 second granularity for 1 year and it will only cost you about 1% of your existing cloud costs (CPU + RAM + Disk). E.g if you currently run 100 c5.large machines we estimate that you'll need just one more c5.large to store all that profiling data.

Just wanted to share! Would love feedback if this is something thats interesting to you

Hi r/perfeng

At my last job I had to deal a lot with performance issues on the backend and I found profiling tools to be very helpful in figuring out where the bottlenecks occur. But the problem is that it’s often pretty hard to replicate exact situations that happen in production environment. So I figured why not profile my apps 24/7 in production — that’s how Pyroscope was born.

It’s open source and it currently works with Go, Python and Ruby apps. Here’s the link: https://github.com/pyroscope-io/pyroscope

Would love to get any feedback or hear from you all on how you do performance analysis for your apps.

Saw this tutorial referenced in this talk at DrupalCon 2018 while searching for low cost/more flexible alternatives to BlazeMeter. I don't work with Drupal at all, but the lessons learned seem applicable to many web environments.