CoFeed

Meta

Diff Authoring Time: Measuring developer productivity at Meta

At Meta, we’re always looking for ways to enhance the productivity of our engineers and developers.

Meta

OCP Summit 2024: The open future of networking hardware for AI

At Open Compute Project Summit (OCP) 2024, we’re sharing details about our next-generation network fabric for our AI training clusters.

Meta

Meta’s open AI hardware vision

At the Open Compute Project (OCP) Global Summit 2024, we’re showcasing our latest open AI hardware designs with the OCP community.

Meta

Inside Bento: Jupyter Notebooks at Meta

This episode of the Meta Tech Podcast is all about Bento, Meta’s internal distribution of Jupyter Notebooks, an open-source web-based comput...

Meta

AI Lab: The secrets to keeping machine learning engineers moving fast

The key to developer velocity across AI lies in minimizing time to first batch (TTFB) for machine learning (ML) engineers.

Meta

The key to a happy Rust/C++ relationship

The history of Rust at Meta goes all the way back to 2016, when we first started using it for source control.

Meta

Leveraging AI for efficient incident response

We’re sharing how we streamline system reliability investigations using a new AI-assisted root cause analysis system.

Meta

Serverless Jupyter Notebooks at Meta

At Meta, Bento, our internal Jupyter notebooks platform, is a popular tool that allows our engineers to mix code, text, and multimedia in a ...

Meta

Composable data management at Meta

In recent years, Meta’s data management systems have evolved into a composable architecture that creates interoperability, promotes reusabil...

Meta

Logarithm: A logging engine for AI training workflows and services

Systems and application logs play a key role in operations, observability, and debugging workflows at Meta.

Meta

How DotSlash makes executable deployment simpler

Andres Suarez and Michael Bolin, two software engineers at Meta, join Pascal Hartig (@passy) on the Meta Tech Podcast to discuss the ins and...

Meta

Aligning Velox and Apache Arrow: Towards composable data management

We’ve partnered with Voltron Data and the Arrow community to align and converge Apache Arrow with Velox, Meta’s open source execution engine...

Meta

Meta loves Python

By now you’re already aware that Python 3.

Meta

DotSlash: Simplified executable deployment

We’ve open sourced DotSlash, a tool that makes large executables available in source control with a negligible impact on repository size, th...

Meta

Lazy is the new fast: How Lazy Imports and Cinder accelerate machine learning at Meta

At Meta, the quest for faster model training has yielded an exciting milestone: the adoption of Lazy Imports and the Python Cinder runtime.

Meta

AI debugging at Meta with HawkEye

HawkEye is the powerful toolkit used internally at Meta for monitoring, observability, and debuggability of the end-to-end machine learning ...

Meta

5 Things you didn’t know about Buck2

Meta has a very large monorepo, with many  different programming languages.

Meta

Meta contributes new features to Python 3.12

Python 3.

Meta

Arcadia: An end-to-end AI system performance simulator

We’re introducing Arcadia, Meta’s unified system that simulates the compute, memory, and network performance of AI training clusters.

Meta

What’s it like to write code at Meta?

Ever wonder what it’s like to write code at Meta’s scale? On the latest episode of the Meta Tech Podcast, Meta engineer Pascal Hartig (@pass...

Meta

Scheduling Jupyter Notebooks at Meta

At Meta, Bento is our internal Jupyter notebooks platform that is leveraged by many internal users.

Meta

Introducing Immortal Objects for Python

Instagram has introduced Immortal Objects – PEP-683 – to Python.

Meta

Fixit 2: Meta’s next-generation auto-fixing linter

Fixit is dead! Long live Fixit 2 – the latest version of our open-source auto-fixing linter.

Meta

Meta developer tools: Working at scale

Every day, thousands of developers at Meta are working in repositories with millions of files.