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Kelly Sommers
114.5K posts

Kelly Sommers
@kellabyte
🇨🇦 Backend Brat. Distributed Diva. Relentless Learner.
Canada Katılım Haziran 2009
357 Takip Edilen49.4K Takipçiler
Kelly Sommers retweetledi

This case study explains how Pinterest migrated its search system (Manas) to Kubernetes and tracked down a rare performance issue
They found cAdvisor’s memory metric scanning caused huge latency spikes
➤ ku.bz/BS18f9fpM

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I just got this email from Microsoft and it talks mostly about reducing copilot, app and UX fixes and thank god the Windows Update restarts.
Unfortunately it doesn’t talk about the more important kernel and driver level headaches that have been SO bad the last 4 years.
Tim Sweeney@TimSweeneyEpic
Great moves by Microsoft!
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Kelly Sommers retweetledi

Gwen Shapira has been responsible for full-stack performance at large organizations and a startup, and was kind enough to share the tradeoffs and lessons learned when it comes to delivering outstanding performance on a reduced budget. ow.ly/Skjp50YwOwV
#ScyllaDB

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Kelly Sommers retweetledi

#1 rule of selling to developers:
- be honest, like overly pedantically honest like a real engineer
- be real
that's it. that's all you have to do.
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Kelly Sommers retweetledi

In a new article, @kirshatrov shares a technique for safely breaking down the (MySQL) database cost of each downstream service's API calls by having the database return cost information so that the downstream service can log it.

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Insane that Paulina couldn’t find a drumming teacher that would accept her because she was too small.
Until one teacher finally said “leave her with me, she will be great”.
youtube.com/shorts/4WVWIo3…

YouTube
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Kelly Sommers retweetledi

Daniel Lemire, "How many branches can your CPU predict?," in Daniel Lemire's blog, March 18, 2026, lemire.me/blog/2026/03/1….
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Kelly Sommers retweetledi
Kelly Sommers retweetledi

What if you could write DataFrame logic once and run it on any SQL database?
Many data workflows begin with pandas for quick experimentation, while production pipelines might run on databases like PostgreSQL or BigQuery.
Moving from prototype to production usually means rewriting the same transformation logic in SQL. That translation takes time and can easily introduce errors.
Ibis solves this by letting you define transformations once in Python and compiling them into native SQL for 25+ backends automatically.
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🚀 Tools for Portable DataFrames in Python: bit.ly/4cPYEUD
#Python #DataScience #SQL #DataEngineer

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@KhuyenTran16 I’ve been thinking a lot about this lately.
I’ve also been curious about database local execution of DataFrame code. Like stored procs.
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Kelly Sommers retweetledi

@eonem Thank you for chiming in. I love this app and how people building bigger systems than I have built (my biggest is 2,000 nodes) can chime in and educate us all.
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@kellabyte Control planes often rely on intentional friction, so that over-admission can’t create instability while dealing with the resulting control plane event processing.
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