369 articles from Meta Engineering.
We’re introducing ZGateway, the proxy we are using to unify traffic through ZippyDB, Meta’s most widely-used key value store. As a bonus, it also enables admission control, load balancing, cross-region resilience, and richer operations. ZippyDB is the most widely used key value store at Meta, backing product metadata, counters, and configuration, and can serve billions […]
We’ve built an AI agent that acts as a secondary expert for a given domain, making deep specialist knowledge readily available and preserved for anyone in an organization to access, share, and build upon. This is not a typical domain-specific agent. Its novelty comes from integrating two layers: A structured, auditable knowledge architecture separates what […]
Training and serving frontier AI models depends on fast, reliable networks that move data between GPUs without wasting compute cycles. To meet this challenge at scale, Meta designed MetaRoCE – a clean-sheet RDMA transport protocol purpose-built for AI workloads on commodity Ethernet. We’re releasing the MetaRoCE specification, a reference software implementation and a compliance test […]
MTIA 300 is the first of Meta’s family of in-house training and inference accelerators optimized for training ranking and recommendation models. We’re sharing how MTIA 300’s built-in NIC chiplets allow it to meet the communication needs associated with training recommendation models with superior performance over general-purpose GPUs. By co-designing MTIA’s communication library, HCCL, alongside t
WhatsApp is committed to helping people stay safe while protecting the privacy of their messages. As scam tactics evolve — from impersonation to social engineering to AI-generated lures — we’re always evolving as well, so that our protections stay ahead of scammers while protecting people’s personal messages with end-to-end encryption. Today, we’re sharing an early […]
Every day, Meta’s recommendation platforms handle billions of user interactions, generating rich temporal signals that capture individual preferences and intent across products, ads, and content. In our 2024 post on sequence learning for ads recommendations, we showed how modeling the order and timing of user actions (rather than relying on static, manually engineered sparse features) […] Read Mor
Meta’s Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations across Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs. This post goes into the details on how we achieved: doubling end-to-end (E2E) training efficiency to 20–25% Model FLOPs Utilization (MFU) while scaling training FLOPs 4x in […]
Hierarchical Interest Representation is a research area for Meta Ads. We’re exploring an upstream representation layer over the universe of Ads entities – users, advertisers, products, services – learning unified embeddings that connect users’ inferred interests with the breadth of what advertisers offer in their deep funnel ads. The innovations in Hierarchical Interest Representation are […] Read
TL; DR At Meta’s scale, a few milliseconds of latency degradation can have a significant negative impact on ads performance. When a Linux kernel upgrade risked regressing latency across Meta’s ad serving fleet, we turned to sched_ext — the upstream, BPF-based extensible scheduling framework — to build a scheduling policy customized to the Ads delivery […]
Over the past several years, model capabilities and training dataset sizes have experienced exponential growth. During the past year or so, the time between new-frontier-model releases has gone down from months to weeks. Reliable and fast access to storage is important to both the speed and computational cost of this AI innovation. If AI is […]
This year marks Meta’s 10th consecutive year as a sponsor of the Python Software Foundation (PSF), the charitable organization dedicated to advancing, supporting, and protecting the open-source Python programming language and the community that sustains it. Python is one of the world’s most influential programming languages, and we use it across our engineering stack, from […]
Smart glasses like the Ray-Ban Meta and Oakley Meta Vanguards need to pack enough energy to power features like cameras, speakers, AI workloads, and even a display. But it all has to fit into the glasses’ temple arms. So how do you place a battery with enough power to run a pair of smart glasses […]
Adopting AV1 for real-time communication at Meta has been a multi-year effort spanning codec selection, device eligibility, rate control, and error resilience. We’re sharing the technical and operational challenges while deploying AV1 and expanding coverage, and how we addressed them for real-time communication. We’re presenting several technologies for improving AV1 call quality, including rate c
We’re introducing Instantaneous PowerLoss Storm, a new testing paradigm within Meta’s infrastructure for handling and mitigating instant or zero-notice power loss in our data centers. We’re sharing: how we built readiness to tolerate instant failures into our existing systems with defense-in-depth strategies; tradeoffs made in implementing it, and how we validated our readiness. Disaster preparedn
We’re introducing SilverTorch, a reimagining of recommendation systems that unifies all retrieval components for user generated content under a unified architecture. SilverTorch shows up to 23.7x higher throughput compared to the state-of-the-art approaches. It’s also showing 20.9x more compute cost efficiency compared to a CPU-based solution while also improving accuracy. Our research paper, “Sil
On its face the new Friend Bubbles feature looks simple enough. It highlights Reels your friends have watched and reacted to. But sometimes the features that seem the most straightforward require the deepest engineering work. On this episode of the Meta Tech Podcast, Pascal Hartig chats with Subasree and Joseph, two software engineers from the Facebook […]
Meta’s data ingestion system, which our engineering teams leverage for up-to-date snapshots of the social graph, has recently undergone a significant revamp to enhance its reliability at scale. Moving from our legacy system to our new architecture required a large-scale migration of our entire data ingestion system. We’re sharing the solutions and strategies that enabled […]
We’re rolling out version 1.1 of Labyrinth, the encrypted storage system and protocol that secures messages and history on Messenger. Labyrinth 1.1 enhances the reliability of end-to-end encrypted backups with a new sub-protocol that helps messages survive the loss of a device, a switched device, and long gaps between sign-ins. Read our updated white paper, […]
The HSM-based Backup Key Vault Meta’s HSM-based Backup Key Vault provides the foundation for end-to-end encrypted backups for WhatsApp and Messenger. The system allows people to protect their backed-up message history with a recovery code, ensuring that the recovery code is stored in tamper-resistant hardware security modules (HSMs) and is inaccessible to Meta, cloud storage […]
We’ve fundamentally transformed Facebook Groups Search to help people more reliably discover, sort through, and validate community content that’s most relevant to them. We’ve adopted a new hybrid retrieval architecture and implemented automated model-based evaluation to address the major friction points people experience when searching community content. Under this new framework, we’ve made tangib
We’re sharing insights into Meta’s Capacity Efficiency Program, where we’ve built an AI agent platform that helps automate finding and fixing performance issues throughout our infrastructure. By leveraging encoded domain expertise across a unified, standardized tool interface these agents help save power and free up engineers’ time away from addressing performance issues to innovating on […] Read
We’re sharing lessons learned from Meta’s post-quantum cryptography (PQC) migration to help other organizations strengthen their resilience as industry transitions to post-quantum cryptography standards. We’re proposing the idea of PQC Migration Levels to help teams within organizations manage the complexity of PQC migration for their various use cases. By outlining Meta’s approach to this work […
At Meta, WebRTC powers real-time audio and video across various platforms. But forking a large open-source project like WebRTC within our monorepo presents unique challenges – over time, an internal fork can drift behind upstream, cutting itself off from community upgrades. We’re sharing how we escaped this “forking trap” – from building a dual-stack architecture […]
As AI increases developer speed and productivity it also increases the need for safeguards. On this episode of the Meta Tech Podcast, Pascal Hartig sits down with Ishwari and Joe from Meta’s Configurations team to discuss how Meta makes config rollouts safe at scale. Listen in to learn about canarying and progressive rollouts, the health checks […]
AI coding assistants are powerful but only as good as their understanding of your codebase. When we pointed AI agents at one of Meta’s large-scale data processing pipelines – spanning four repositories, three languages, and over 4,100 files – we quickly found that they weren’t making useful edits quickly enough. We fixed this by building […]
This is the second post in the Ranking Engineer Agent blog series exploring the autonomous AI capabilities accelerating Meta’s Ads Ranking innovation. The previous post introduced Ranking Engineer Agent’s ML exploration capability, which autonomously designs, executes, and analyzes ranking model experiments. This post covers how to optimize the low-level infrastructure that makes those models run
Meta continues to lead the industry in utilizing groundbreaking AI Recommendation Systems (RecSys) to deliver better experiences for people, and better results for advertisers. To reach the next frontier of performance, we are scaling Meta’s Ads Recommender runtime models to LLM-scale & complexity to further a deeper understanding of people’s interests and intent. This increase […]
Meta is continuing its long-term roadmap to help the construction industry leverage AI to produce high-quality and more sustainable concrete mixes, as well as those exclusively produced in the United States. Concurrent with the 2026 American Concrete Institute (ACI) Spring Convention, Meta is releasing a new AI model for designing concrete mixes – Bayesian Optimization […]
Friend bubbles in Facebook Reels highlight Reels your friends have liked or reacted to, helping you discover new content and making it easier to connect over shared interests. This article explains the technical architecture behind friend bubbles, including how machine learning estimates relationship strength and ranks content your friends have interacted with to create more […]
Meta’s Ranking Engineer Agent (REA) autonomously executes key steps across the end-to-end machine learning (ML) lifecycle for ads ranking models. This post covers REA’s ML experimentation capabilities: autonomously generating hypotheses, launching training jobs, debugging failures, and iterating on results. Future posts will cover additional REA capabilities. REA reduces the need for manual interv
Even seemingly simple engineering tasks — like updating an API — can become monumental undertakings when you’re dealing with millions of lines of code and thousands of engineers, especially if the changes are security-related. Nowhere is this more apparent than in mobile security, where a single class of vulnerability can be replicated across hundreds of […]
We’re sharing the technical details behind how Advanced Browsing Protection (ABP) in Messenger protects the privacy of the links clicked on within chats while still warning people about malicious links. We hope that this post has helped to illuminate some of the engineering challenges and infrastructure components involved for providing this feature for our users. […]
FFmpeg is truly a multi-tool for media processing. As an industry-standard tool it supports a wide variety of audio and video codecs and container formats. It can also orchestrate complex chains of filters for media editing and manipulation. For the people who use our apps, FFmpeg plays an important role in enabling new video experiences […]
Meta recognizes the long-term benefits of jemalloc, a high-performance memory allocator, in its software infrastructure. We are renewing focus on jemalloc, aiming to reduce maintenance needs and modernize the codebase while continuing to evolve the allocator to adapt to the latest hardware and workloads. We are committed to continuing to develop jemalloc development with the […]
We are open-sourcing the initial version of RCCLX – an enhanced version of RCCL that we developed and tested on Meta’s internal workloads. RCCLX is fully integrated with Torchcomms and aims to empower researchers and developers to accelerate innovation, regardless of their chosen backend. Communication patterns for AI models are constantly evolving, as are hardware […]
WHAT IT IS The rise of agentic software development means code is being written, reviewed, and shipped faster than ever before across the entire industry. It also means that testing frameworks need to evolve for this rapidly changing landscape. Faster development demands faster testing that can catch bugs as they land in a codebase, without […]
We’re sharing details of the role backend aggregation (BAG) plays in building Meta’s gigawatt-scale AI clusters like Prometheus. BAG allows us to seamlessly connect thousands of GPUs across multiple data centers and regions. Our BAG implementation is connecting two different network fabrics – Disaggregated Schedule Fabric (DSF) and Non-Scheduled Fabric (NSF). Once it’s complete our AI […] Read Mor
We’re sharing a novel approach to enabling cross-device passkey authentication for devices with inaccessible displays (like XR devices). Our approach bypasses the use of QR codes and enables cross-device authentication without the need for an on-device display, while still complying with all trust and proximity requirements. This approach builds on work done by the FIDO […]
WhatsApp has adopted and rolled out a new layer of security for users – built with Rust – as part of its effort to harden defenses against malware threats. WhatsApp’s experience creating and distributing our media consistency library in Rust to billions of devices and browsers proves Rust is production ready at a global scale. […]
We’ve improved personalized video recommendations on Facebook Reels by moving beyond metrics such as likes and watch time and directly leveraging user feedback. Our new User True Interest Survey (UTIS) model, now helps surface more niche, high-quality content and boosts engagement, retention, and satisfaction. We’re doubling down on personalization, tackling challenges like sparse user data […] Re
Build a large enough website with a large enough codebase, and you’ll eventually find that CSS presents challenges at scale. It’s no different at Meta, which is why we open-sourced StyleX, a solution for CSS at scale. StyleX combines the ergonomics of CSS-in-JS with the performance of static CSS. It allows atomic styling of components […]
The 2025 Typed Python Survey, conducted by contributors from JetBrains, Meta, and the broader Python typing community, offers a comprehensive look at the current state of Python’s type system and developer tooling. With 1,241 responses (a 15% increase from last year), the survey captures the evolving sentiment, challenges, and opportunities around Python typing in the […]
Incident investigation can be a daunting task in today’s digital landscape, where large-scale systems comprise numerous interconnected components and dependencies DrP is a root cause analysis (RCA) platform, designed by Meta, to programmatically automate the investigation process, significantly reducing the mean time to resolve (MTTR) for incidents and alleviating on-call toil Today, DrP is used [
We’re going behind the scenes of the Meta Ray-Ban Display, Meta’s most advanced AI glasses yet. In a previous episode we met the team behind the Meta Neural Band, the EMG wristband packaged with the Ray-Ban Display. Now we’re delving into the glasses themselves. Kenan and Emanuel, from Meta’s Wearables org, join Pascal Hartig on […]
Meta’s secure-by-default frameworks wrap potentially unsafe OS and third-party functions, making security the default while preserving developer speed and usability. These frameworks are designed to closely mirror existing APIs, rely on public and stable interfaces, and maximize developer adoption by minimizing friction and complexity. Generative AI and automation accelerate the adoption of secure
We’re introducing Zoomer, Meta’s comprehensive, automated debugging and optimization platform for AI. Zoomer works across all of our training and inference workloads at Meta and provides deep performance insights that enable energy savings, workflow acceleration, and efficiency gains in our AI infrastructure. Zoomer has delivered training time reductions, and significant QPS improvements, making i
We’re excited to share another advancement in the security of your conversations on Messenger: the launch of key transparency verification for end-to-end encrypted chats. This new feature enables an additional level of assurance that only you — and the people you’re communicating with — can see or listen to what is sent, and that no […]
We’ve released Ax 1.0, an open-source platform that uses machine learning to automatically guide complex, resource-intensive experimentation. Ax is used at scale across Meta to improve AI models, tune production infrastructure, and accelerate advances in ML and even hardware design. Our accompanying paper, “Ax: A Platform for Adaptive Experimentation” explains Ax’s architecture, methodology, and h
Connecting Africa and the World We’re excited to share the completion of the core 2Africa infrastructure, the world’s longest open access subsea cable system. 2Africa is a landmark subsea cable system that sets a new standard for global connectivity. This project is the result of years of collaboration, innovation, and a shared vision to connect […]
We’re sharing how we’ve enabled Dolby Vision and ambient viewing environment (amve) on the Instagram iOS app to enhance the video viewing experience. HDR videos created on iPhones contain unique Dolby Vision and amve metadata that we needed to support end-to-end Instagram for iOS is now the first Meta app to support Dolby Vision video, […]
Most people have heard of open-source software. But have you heard about open hardware? And did you know open source can have a positive impact on the environment? On this episode of the Meta Tech Podcast, Pascal Hartig sits down with Dharmesh and Lisa to talk about all things open hardware, and Meta’s biggest announcements […]
StyleX is Meta’s styling system for large-scale applications. It combines the ergonomics of CSS-in-JS with the performance of static CSS, generating collision-free atomic CSS while allowing for expressive, type-safe style authoring. StyleX was open sourced at the end of 2023 and has since become the standard styling system across Meta products like Facebook, Instagram, WhatsApp, […]
We’re sharing details about Meta’s Generative Ads Recommendation Model (GEM), a new foundation model that delivers increased ad performance and advertiser ROI by enhancing other ads recommendation models’ ability to serve relevant ads. GEM’s novel architecture allows it to scale with an increasing number of parameters while consistently generating more precise predictions efficiently. GEM propagat
At Meta, we use invisible watermarking for a variety of content provenance use cases on our platforms. Invisible watermarking serves a number of use cases, including detecting AI-generated videos, verifying who posted a video first, and identifying the source and tools used to create a video. We’re sharing how we overcame the challenges of scaling […]
How does Meta empower its product teams to harness GenAI’s power responsibly? In this post, we delve into how Meta addresses the challenges of safeguarding data in the GenAI era by scaling its Privacy Aware Infrastructure (PAI), with a particular focus on Meta’s AI glasses as an example GenAI use case. We’ll describe in detail […]
Disaggregated Schedule Fabric (DSF) is Meta’s next-generation network fabric technology for AI training networks that addresses the challenges of existing Clos-based networks. We’re sharing the challenges and innovations surrounding DSF and discussing future directions, including the creation of mega clusters through DSF and non-DSF region interconnectivity, as well as the exploration of alternati
At Meta, we are constantly pushing the boundaries of LLM inference systems to power applications such as the Meta AI App. We’re sharing how we developed and implemented advanced parallelism techniques to optimize key performance metrics related to resource efficiency, throughput, and latency. The rapid evolution of large language models (LLMs) has ushered in a […]
Sapling is a scalable, user-friendly, and open-source source control system that powers Meta’s monorepo. As discussed at the GitMerge 2024 conference session on branching, designing and implementing branching workflows for large monorepos is a challenging problem with multiple tradeoffs between scalability and the developer experience. After the conference, we designed, implemented, and open sourc
We’re sharing details on our journey to scale Meta’s Backbone network to support the increasing demands of new and existing AI workloads. We’ve developed new technologies and designs to address our 10x scaling needs and applying some of these same principles to help extend our AI clusters between multiple data centers. Meta’s Backbone network is […]
We’re presenting Design for Sustainability, a set of technical design principles for new designs of IT hardware to reduce emissions and cost through reuse, extending useful life, and optimizing design. At Meta, we’ve been able to significantly reduce the carbon footprint of our data centers by integrating several design strategies such as modularity, reuse, retrofitting, […]