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When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Pinterest Engineering cut Apache Spark out-of-memory failures by 96% using improved observability, configuration tuning, and automatic memory retries. Staged rollout, dashboards, and proactive memory adjustments stabilized data pipelines, reduced manual intervention, and lowered operational overhead across tens of thousands of daily jobs.
Franka Passing discusses the architectural shift of Duolingo’s 500+ backend services to Kubernetes. She explains the move toward GitOps with Argo CD, the transition to IPv6-only pods, and the "cellular architecture" used to isolate environments. She shares "reports from the trenches" on managing developer trust, navigating AWS rate limits, and productionizing early adopter services.
How can you focus in a sea of results from a large regression test suite? This article describes a stochastic approach that relies on some degree of redundancy in your CI regression test set. This approach does not guarantee you will catch every bug every time, but it gives you your best bet of not missing the subtle signatures of all the bugs uncovered by your CI regression test suite runs.
In this episode, Thomas Betts and Adi Polak talk about the need for context engineering when interacting with LLMs and designing agentic systems. Prompt engineering techniques work with a stateless approach, while context engineering allows AI systems to be stateful.
A 600-run benchmark by Ruby committer Yusuke Endoh tested Claude Code across 13 languages, implementing a simplified Git. Ruby, Python, and JavaScript were the fastest and cheapest, at $0.36- $0.39 per run. Statistically typed languages cost 1.4-2.6x more. Adding type checkers to dynamic languages imposed 1.6-3.2x slowdowns. Full dataset available on GitHub.
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Pinterest Reduces Spark OOM Failures by 96% Through Auto Memory Retries
Pinterest Engineering cut Apache Spark out-of-memory failures by 96% using improved observability, configuration tuning, and automatic memory retries. Staged rollout, dashboards, and proactive memory adjustments stabilized data pipelines, reduced manual intervention, and lowered operational overhead across tens of thousands of daily jobs.
By Leela KumiliPresentation: Duolingo's Kubernetes Leap
Franka Passing discusses the architectural shift of Duolingo’s 500+ backend services to Kubernetes. She explains the move toward GitOps with Argo CD, the transition to IPv6-only pods, and the "cellular architecture" used to isolate environments. She shares "reports from the trenches" on managing developer trust, navigating AWS rate limits, and productionizing early adopter services.
By Franka PassingArticle: A Better Alternative to Reducing CI Regression Test Suite Sizes
How can you focus in a sea of results from a large regression test suite? This article describes a stochastic approach that relies on some degree of redundancy in your CI regression test set. This approach does not guarantee you will catch every bug every time, but it gives you your best bet of not missing the subtle signatures of all the bugs uncovered by your CI regression test suite runs.
By James Bornefelt WestfallPodcast: Context Engineering with Adi Polak
In this episode, Thomas Betts and Adi Polak talk about the need for context engineering when interacting with LLMs and designing agentic systems. Prompt engineering techniques work with a stateless approach, while context engineering allows AI systems to be stateful.
By Adi PolakDynamic Languages Faster and Cheaper in 13-Language Claude Code Benchmark
A 600-run benchmark by Ruby committer Yusuke Endoh tested Claude Code across 13 languages, implementing a simplified Git. Ruby, Python, and JavaScript were the fastest and cheapest, at $0.36- $0.39 per run. Statistically typed languages cost 1.4-2.6x more. Adding type checkers to dynamic languages imposed 1.6-3.2x slowdowns. Full dataset available on GitHub.
By Steef-Jan Wiggers