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Inside Facebook’s video delivery system

Engineering at Meta

Were explaining the end-to-end systems the Facebook app leverages to deliver relevant content to people. At Facebooks scale, the systems built to support and overcome these challenges require extensive trade-off analyses, focused optimizations, and architecture built to allow our engineers to push for the same user and business outcomes.

Systems 68
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The Future of Reliable Data + AI—Observing the Data, System, Code, and Model

Monte Carlo

GitHub copilot can even code alongside you like your own pocket-sized Steve Wozniak. Table of Contents Understanding How Data + AI Can Break Data System Code Model Data + AI observability must cover inputs and outputs it is all or nothing Understanding How Data + AI Can Break Data + AI applications are complex.

Coding 52
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Data Migration Strategies For Large Scale Systems

Data Engineering Podcast

Summary Any software system that survives long enough will require some form of migration or evolution. When that system is responsible for the data layer the process becomes more challenging. This episode is supported by Code Comments, an original podcast from Red Hat. My thanks to the team at Code Comments for their support.

Systems 130
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Paying down tech debt: further learnings

The Pragmatic Engineer

Use tech debt payments to get into the flow and stay in it A good reason to add new comments to old code before you change it is to speed up a code review. When it takes me time to learn what code does, writing something down helps me remember what I figured out. Clarifying the code is even better.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails.

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Build faster with Buck2: Our open source build system

Engineering at Meta

Buck2, our new open source, large-scale build system , is now available on GitHub. Buck2 is an extensible and performant build system written in Rust and designed to make your build experience faster and more efficient. In our internal tests at Meta, we observed that Buck2 completed builds 2x as fast as Buck1. Why rebuild Buck?

Building 144
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A Tour Around Buck2, Meta's New Build System

Tweag

Buck2 is a from-scratch rewrite of Buck , a polyglot, monorepo build system that was developed and used at Meta (Facebook), and shares a few similarities with Bazel. As you may know, the Scalable Builds Group at Tweag has a strong interest in such scalable build systems. fix the code # fix code 7.

Systems 141
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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.