369 articles from Meta Engineering.
As we focus on our goal of achieving net zero emissions in 2030, we also aim to create a common taxonomy for the entire industry to measure carbon emissions. We’re sharing details on a new methodology we presented at the 2025 OCP regional EMEA summit that leverages AI to improve our understanding of our IT […]
At Open Compute Project Summit (OCP) 2025, we’re sharing details about the direction of next-generation network fabrics for our AI training clusters. We’ve expanded our network hardware portfolio and are contributing new disaggregated network platforms to OCP. We look forward to continued collaboration with OCP to open designs for racks, servers, storage boxes, and motherboards […]
Meta open-sourced React over a decade ago to help developers build better user experiences. Since then, React has grown into one of the world’s most popular open source projects, powering over 50 million websites and products built by companies such as Microsoft, Shopify, Bloomberg, Discord, Coinbase, the NFL, and many others. With React Native, React […]
OpenZL is a new open source data compression framework that offers lossless compression for structured data. OpenZL is designed to offer the performance of a format-specific compressor with the easy maintenance of a single executable binary. You can get started with OpenZL today by visiting our Quick Start guide and the OpenZL GitHub repository. Learn more […]
We’re introducing Candle, a new submarine cable connecting countries across East Asia and Southeast Asia. We’re also announcing several updates to our subsea cables across the Asia-Pacific, including the completion of the Bifrost cable system. The Asia-Pacific (APAC) region is home to over 58% of the world’s internet users1 – many who rely on robust […]
Key Takeways: With billions of Android app users, we’re always looking to improve the Meta app experience, and in this post, we explore the ways we’ve leveraged Android’s Baseline Profiles to significantly improve their performance. We discuss the performance challenges we’ve faced as Meta’s apps, how the needs of users have become more complex over […]
Following our keynote presentations at FSE 2025 and Eurostar 2025, we’re delving further into the development of Meta’s Automated Compliance Hardening (ACH) tool, an LLM-based tool for software testing that is automating aspects of compliance adherence at Meta, while accelerating developer and product velocity. By leveraging LLMs we’ve been able to overcome the barriers that […]
Imagine being able to use AI to create 3D virtual worlds using prompts as easily as you can generate images. The intersection of AI and VR was one of the biggest topics at Meta Connect this year. In his keynote, Mark Zuckerberg shared his vision of a future where anyone can create virtual worlds using […]
Over the past 21 years, Meta has grown exponentially from a small social network connecting a few thousand people in a handful of universities in the U.S. into several apps and novel hardware products that serve over 3.4 billion people throughout the world. Our infrastructure has evolved significantly over the years, growing from a […]
AI is everywhere and, as network engineers, we are right in the thick of it: building the network infrastructure for AI. This year, at our largest @Scale:Networking ever, engineers from Meta, ByteDance, Google, Microsoft, Oracle, AMD, Broadcom, Cisco, and NVIDIA came together to share our latest experiences in architecting, designing, operating, and debugging our AI […]
Today, Meta, Vodafone, and Google released a white paper, “Video Streaming with the AV1 Video Codec in Mobile Devices,” detailing the benefits of the AV1 codec, an advanced video compression technique, to enhance the streaming video experience on mobile devices. The white paper recommends that: Vendors of core processors (SoCs) should evaluate the adoption of […]
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We’re sharing how Meta is applying machine learning (ML) and diversity algorithms to improve notification quality and user experience. We’ve introduced a diversity-aware notification ranking framework to reduce uniformity and deliver a more varied and engaging mix of notifications. This new framework reduces the volume of notifications and drives higher engagement rates through more diverse […] Re
The Kotlin incremental compiler has been a true gem for developers chasing faster compilation since its introduction in build tools. Now, we’re excited to bring its benefits to Buck2 – Meta’s build system – to unlock even more speed and efficiency for Kotlin developers. Unlike a traditional compiler that recompiles an entire module every time, […]
In this post, we explore the ways we’re evolving Meta’s data warehouse to facilitate productivity and security to serve both human users and AI agents. We detail how we’re developing agents that help users making data access requests to get to the data they need, and that help data owners process requests and maintain security. […]
We’re exploring Meta’s Federation Platform, a scalable set of tools for managing compliance-related tasks, along with Privacy Waves, our method for batching these tasks and ensuring accountability. Together, the Federation Platform and Privacy Waves create a structured, effective, and sustainable approach to operationalizing privacy work, enabling Meta to safeguard user data for the billions of […
The state of the research Diff Risk Score (DRS) is an AI-powered technology built at Meta that predicts the likelihood of a code change causing a production incident, also known as a SEV. Built on a fine-tuned Llama LLM, DRS evaluates code changes and metadata to produce a risk score and highlight potentially risky code […]
What if you could control any device using only subtle hand movements? New research from Meta’s Reality Labs is pointing even more firmly toward wrist-worn devices using surface electromyography (sEMG) becoming the future of human-computer interaction. But how do you develop a wrist-worn input device that works for everyone? Generalization has been one of the […]
ExecuTorch is the PyTorch inference framework for edge devices developed by Meta with support from industry leaders like Arm, Apple, and Qualcomm. Running machine learning (ML) models on-device is increasingly important for Meta’s family of apps (FoA). These on-device models improve latency, maintain user privacy by keeping data on users’ devices, and enable offline functionality. […]
Meta has developed Privacy Aware Infrastructure (PAI) and Policy Zones to enforce purpose limitations on data, especially in large-scale batch processing systems. Policy Zones integrates with Meta’s exabyte-scale data warehouse and processing systems, using runtime enforcement and SQL parsing to propagate and enforce privacy annotations across millions of daily data flows per day, performing trill
Hardware faults can have a significant impact on AI training and inference. Silent data corruptions (SDCs), undetected data errors caused by hardware, can be particularly harmful for AI systems that rely on accurate data for training as well as providing useful outputs. We are sharing methodologies we deploy at various scales for detecting SDC across […]
Meta has developed an open-source AI tool to design concrete mixes that are stronger, more sustainable, and ready to build with faster—speeding up construction while reducing environmental impact. The AI tool leverages Bayesian optimization, powered by Meta’s BoTorch and Ax frameworks, and was developed with Amrize and the University of Illinois Urbana-Champaign (U of I) […]
Have you ever worked is legacy code? Are you curious what it takes to modernize systems at a massive scale? Pascal Hartig is joined on the latest Meta Tech Podcast by Elaine and Buping, two software engineers working on a bold project to rewrite the decades-old C code in one of Meta’s core messaging libraries […]
We are proud to announce that Meta has officially joined the Kotlin Foundation as a gold member, marking a significant milestone in our ongoing commitment to Kotlin and the broader Android development ecosystem. Over the past several years, Meta engineers have been actively migrating our extensive Android codebase—comprising tens of millions of lines—from Java to […]
Meta is partnering with V.tal to extend the Malbec subsea cable to Porto Alegre, Brazil by 2027. With this new extension, Malbec will become the first subsea cable to land in the state of Rio Grande do Sul, bringing more connectivity to millions of people in Southern Brazil and neighboring countries. Malbec will improve the […]
In this post, we explore how Instagram has successfully scaled its algorithm to include over 1000 ML models without sacrificing recommendation quality or reliability. We delve into the intricacies of managing such a vast array of models, each with its own performance characteristics and product goals. We share insights and lessons learned along the way—from […]
As Meta has launched new, innovative products leveraging generative AI (GenAI), we need to make sure the underlying infrastructure components evolve along with it. Applying infrastructure knowledge and optimizations have allowed us to adapt to changing product requirements, delivering a better product along the way. Ultimately, our infrastructure systems need to balance our need to […]
Back in 2017, engineers at Meta sought to create a type checker for Instagram’s typed Python codebase. Years later, as the type system continued to evolve, that type checker eventually became Pyrefly. Pyrefly is a new type checker and IDE experience for Python, written with Rust, and now available for the entire Python community to […]
Today we are announcing an alpha version of Pyrefly, an open source Python type checker and IDE extension crafted in Rust. Pyrefly is a static type checker that analyzes Python code to ensure type consistency and help you catch errors throughout your codebase before your code runs. It also supports IDE integration and CLI usage […]
Meta and NVIDIA collaborated to accelerate vector search on GPUs by integrating NVIDIA cuVS into Faiss v1.10, Meta’s open source library for similarity search. This new implementation of cuVS will be more performant than classic GPU-accelerated search in some areas. For inverted file (IVF) indexing, NVIDIA cuVS outperforms classical GPU-accelerated IVF build times by up […]
Meta and Quansight have improved key libraries in the Python Ecosystem. There is plenty more to do and we invite the community to help with our efforts. We’ll look at two key efforts in Python’s packaging ecosystem to make packages faster and easier to use: 🚀 Unlock performance wins for developers through free-threaded Python – […]
Meta develops infrastructure all across the globe to transport information and content for the billions of people using our services around the world. At the core of this infrastructure are aggregation points – like data centers – and the digital cables that connect them. Subsea cables – the unseen digital highways of the internet – […]
We are introducing AutoPatchBench, a benchmark for the automated repair of vulnerabilities identified through fuzzing. By providing a standardized benchmark, AutoPatchBench enables researchers and practitioners to objectively evaluate and compare the effectiveness of various AI program repair systems. This initiative facilitates the development of more robust security solutions, and also encourage
We are inspired by the possibilities of AI to help people be more creative, productive, and stay closely connected on WhatsApp, so we set out to build a new technology that allows our users around the world to use AI in a privacy-preserving way. We’re sharing an early look into Private Processing, an optional capability […]
Managing and understanding large-scale data ecosystems is a significant challenge for many organizations, requiring innovative solutions to efficiently safeguard user data. Meta’s vast and diverse systems make it particularly challenging to comprehend its structure, meaning, and context at scale. To address these challenges, we made substantial investments in advanced data understanding technologi
Open source has played an essential role in the tech industry and beyond. Whether in the AI/ML, web, or mobile space, our open source community grew and evolved while connecting people worldwide. At Meta Open Source, 2024 was a year of growth and transformation. Our open source initiatives addressed the evolving needs and challenges of […]
Mobile GraphQL is a framework used at Meta for fetching data in mobile applications using GraphQL, a strongly-typed, declarative query language. At Meta it handles data fetching for apps like Facebook and Instagram. Sabrina, a software engineer on Meta’s Mobile GraphQL Platform Team, joins Pascal Hartig on the Meta Tech podcast to discuss the evolution […]
Multimodal AI – models capable of processing multiple different types of inputs like speech, text, and images – have been transforming user experiences in the wearables space. With our Ray-Ban Meta glasses, multimodal AI helps the glasses see what the wearer is seeing. This means anyone wearing Ray-Ban Meta glasses can ask them questions about […]
The growth of data and need for increased power efficiency are leading to innovative storage solutions. HDDs have been growing in density, but not performance, and TLC flash remains at a price point that is restrictive for scaling. QLC technology addresses these challenges by forming a middle tier between HDDs and TLC SSDs. QLC […]
Meta has been working to shift its Android codebase from Java to Kotlin, a newer language for Android development that offers some key advantages over Java. We’ve even open sourced various examples and utilities we used to in our migration to manipulate Kotlin code. So how do you translate roughly tens of millions of lines of Java […]
Meta’s Anti Scraping team focuses on preventing unauthorized scraping as part of our ongoing work to combat data misuse. In order to protect Meta’s changing codebase from scraping attacks, we have introduced static analysis tools into our workflow. These tools allow us to detect potential scraping vectors at scale across our Facebook, Instagram, and even […]
Today, we’re announcing our most ambitious subsea cable endeavor yet: Project Waterworth. Once complete, the project will reach five major continents and span over 50,000 km (longer than the Earth’s circumference), making it the world’s longest subsea cable project using the highest-capacity technology available. Project Waterworth will bring industry-leading connectivity to the U.S., India, Brazi
In 2024, our bug bounty program awarded more than $2.3 million in bounties, bringing our total bounties since the creation of our program in 2011 to over $20 million. As part of our defense-in-depth strategy, we continued to collaborate with the security research community in the areas of GenAI, AR/VR, ads tools, and more. We […]
WHAT IT IS Meta’s Automated Compliance Hardening (ACH) tool is a system for mutation-guided, LLM-based test generation. ACH hardens platforms against regressions by generating undetected faults (mutants) in source code that are specific to a given area of concern and using those same mutants to generate tests. When applied to privacy, for example, ACH automates […]
We’re sharing how Meta built support for data logs, which provide people with additional data about how they use our products. Here we explore initial system designs we considered, an overview of the current architecture, and some important principles Meta takes into account in making data accessible and easy to understand. Users have a variety […]
We’ve previously described why we think it’s time to leave the leap second in the past. In today’s rapidly evolving digital landscape, introducing new leap seconds to account for the long-term slowdown of the Earth’s rotation is a risky practice that, frankly, does more harm than good. This is particularly true in the data center […]
Introducing a new Android UI framework like Jetpack Compose into an existing app is more complicated than importing some AARS and coding away. What if your app has specific performance goals to meet? What about existing design components, integrations with navigation, and logging frameworks? On this episode of the Meta Tech Podcast Pascal Hartig is […]
Data lineage is an instrumental part of Meta’s Privacy Aware Infrastructure (PAI) initiative, a suite of technologies that efficiently protect user privacy. It is a critical and powerful tool for scalable discovery of relevant data and data flows, which supports privacy controls across Meta’s systems. This allows us to verify that our users’ everyday interactions […]
We’re sharing details about Strobelight, Meta’s profiling orchestrator. Strobelight combines several technologies, many open source, into a single service that helps engineers at Meta improve efficiency and utilization across our fleet. Using Strobelight, we’ve seen significant efficiency wins, including one that has resulted in an estimated 15,000 servers’ worth of annual capacity savings. Strobe
Do types actually make developers more productive? Or is it just more typing on the keyboard? To answer that question we’re revisiting Diff Authoring Time (DAT) – how Meta measures how long it takes to submit changes to a codebase. DAT is just one of the ways we measure developer productivity and this latest episode […]
Today’s rapidly evolving landscape of use cases that demand highly performant and efficient network infrastructure is placing new emphasis on how in-line amplifiers (ILAs) are designed and deployed. Meta’s ILA Evo effort seeks to reimagine how an ILA site could be deployed to improve speed and cost while making a step function improvement in power […]
We’re sharing details about Glean, Meta’s open source system for collecting, deriving, and working with facts about source code. In this blog post we’ll talk about why a system like Glean is important, explain the rationale for Glean’s design, and run through some of the ways we’re using Glean to supercharge our developer tooling at […]
Meta has been on a years-long undertaking to translate our entire Android codebase from Java to Kotlin. Today, despite having one of the largest Android codebases in the world, we’re well past the halfway point and still going. We’re sharing some of the tradeoffs we’ve made to support automating our transition to Kotlin, seemingly simple […]
How did the Threads iOS team maintain the app’s performance during its incredible growth? Here’s how Meta’s Threads team thinks about performance, including the key metrics we monitor to keep the app healthy. We’re also diving into some case studies that impact publish reliability and navigation latency. When Meta launched Threads in 2023, it became […]
How do you take a mixed reality (MR) headset from idea to finished product? Alfred Jones, VP of hardware engineering at Meta Reality Labs, joins Pascal Hartig (@passy) on the latest episode of the Meta Tech Podcast for a discussion on the realities (no pun intended) of building MR hardware. Jones shares his strategy for […]
We’re explaining the end-to-end systems the Facebook app leverages to deliver relevant content to people. Learn about our video-unification efforts that have simplified our product experience and infrastructure, in-depth details around mobile delivery, and new features we are working on in our video-content delivery stack. The end-to-end delivery of highly relevant, personalized, timely, and respo
Ten years after the introduction of PEP 484, we surveyed the current state of the Python type system and the tools developers are using. […]
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Andromeda is Meta’s proprietary machine learning (ML) system design for retrieval in ad recommendation focused on delivering a step-function improvement in value to our advertisers and people. This system pushes the boundary of cutting edge AI for retrieval with NVIDIA Grace Hopper Superchip and Meta Training and Inference Accelerator (MTIA) hardware through innovations in ML […]
AI plays a fundamental role in creating valuable connections between people and advertisers within Meta’s family of apps. Meta’s ad recommendation engine, powered by deep learning recommendation models (DLRMs), has been instrumental in delivering personalized ads to people. Key to this success was incorporating thousands of human-engineered signals or features in the DLRM-based recommendation syst