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SRE & Ops

446 articles on SRE & Ops.

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SRE & Ops — MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet

MetaRoCE: A New RDMA Transport Built for AI-Scale Ethernet

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 […]

CWChris Wiltz·August 24, 2026SRE & Ops
SRE & Ops — MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines

MTIA 300: Meta’s First Training Chip with Built-in NICs and Communication-Offloading Engines

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

CWChris Wiltz·August 24, 2026SRE & Ops
SRE & Ops — The next generation of MCP

The next generation of MCP

The next version of MCP has a rewritten, stateless core that just works on Workers. We cover upgrades to the protocol, the new feature lifecycle and SDK migration path, and hear from early adopters already running it in production.

MCMatt CareyMatt Carey·August 6, 2026SRE & Ops
SRE & Ops — From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking

From User Sequences to Scaling Laws: A Multi-Stage Architecture for Meta’s Ads Ranking

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

CWChris Wiltz·August 5, 2026SRE & Ops
SRE & Ops — Building Slack agents can be easy

Building Slack agents can be easy

Build and deploy Slack agents in a single session. This skill handles configuration, secrets, and deployment, taking you from idea to production with just a conversation with your coding agent.

VVercel·July 14, 2026SRE & Ops
SRE & Ops — Agentic Infrastructure

Agentic Infrastructure

The shift to agentic infrastructure. For fifty years, infrastructure assumed a human operator. Someone to configure the server, click the deploy button, or read the logs.

VVercel·July 2, 2026SRE & Ops
SRE & Ops — Meta’s AI Storage Blueprint at Scale

Meta’s AI Storage Blueprint at Scale

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 […]

CWChris Wiltz·July 1, 2026SRE & Ops
SRE & Ops — Lights Out, Systems On: Validating Instant Power Loss Readiness

Lights Out, Systems On: Validating Instant Power Loss Readiness

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

CWChris Wiltz·June 3, 2026SRE & Ops
SRE & Ops — Migrating Data Ingestion Systems at Meta Scale

Migrating Data Ingestion Systems at Meta Scale

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 […]

CWChris Wiltz·May 12, 2026SRE & Ops
SRE & Ops — How Meta Is Strengthening End-to-End Encrypted Backups

How Meta Is Strengthening End-to-End Encrypted Backups

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 […]

CWChris Wiltz·May 1, 2026SRE & Ops
SRE & Ops — Agents can now create Cloudflare accounts, buy domains, and deploy

Agents can now create Cloudflare accounts, buy domains, and deploy

Starting today, agents can now be Cloudflare customers. They can create a Cloudflare account, start a paid subscription, register a domain, and get back an API token to deploy code right away. Humans can be in the loop to grant permission, but there’s no need to go to the dashboard, copy and paste API tokens, or enter credit card details.

SBSid, Brendan Irvine BroqueSid, Brendan Irvine Broque·April 30, 2026SRE & Ops
SRE & Ops — Capacity Efficiency at Meta: How Unified AI Agents Optimize Performance at Hyperscale

Capacity Efficiency at Meta: How Unified AI Agents Optimize Performance at Hyperscale

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

CWChris Wiltz·April 16, 2026SRE & Ops
SRE & Ops — Escaping the Fork: How Meta Modernized WebRTC Across 50+ Use Cases

Escaping the Fork: How Meta Modernized WebRTC Across 50+ Use Cases

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 […]

CWChris Wiltz·April 9, 2026SRE & Ops
SRE & Ops — Trust But Canary: Configuration Safety at Scale

Trust But Canary: Configuration Safety at Scale

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 […]

CWChris Wiltz·April 8, 2026SRE & Ops
SRE & Ops — How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines

How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines

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 […]

CWChris Wiltz·April 6, 2026SRE & Ops
SRE & Ops — KernelEvolve: How Meta’s Ranking Engineer Agent Optimizes AI Infrastructure

KernelEvolve: How Meta’s Ranking Engineer Agent Optimizes AI Infrastructure

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

CWChris Wiltz·April 2, 2026SRE & Ops
SRE & Ops — AI for American-Produced Cement and Concrete

AI for American-Produced Cement and Concrete

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 […]

CWChris Wiltz·March 30, 2026SRE & Ops
SRE & Ops — A one-line Kubernetes fix that saved 600 hours a year

A one-line Kubernetes fix that saved 600 hours a year

When we investigated why our Atlantis instance took 30 minutes to restart, we discovered a bottleneck in how Kubernetes handles volume permissions. By adjusting the fsGroupChangePolicy, we reduced restart times to 30 seconds.

BSBraxton SchaferBraxton Schafer·March 26, 2026SRE & Ops
SRE & Ops — Ranking Engineer Agent (REA): The Autonomous AI Agent Accelerating Meta’s Ads Ranking Innovation

Ranking Engineer Agent (REA): The Autonomous AI Agent Accelerating Meta’s Ads Ranking Innovation

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

CWChris Wiltz·March 17, 2026SRE & Ops
SRE & Ops — Investing in Infrastructure: Meta’s Renewed Commitment to jemalloc

Investing in Infrastructure: Meta’s Renewed Commitment to jemalloc

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 […]

CWChris Wiltz·March 2, 2026SRE & Ops
SRE & Ops — Building Prometheus: How Backend Aggregation Enables Gigawatt-Scale AI Clusters

Building Prometheus: How Backend Aggregation Enables Gigawatt-Scale AI Clusters

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

CWChris Wiltz·February 9, 2026SRE & Ops
SRE & Ops — Route leak incident on January 22, 2026

Route leak incident on January 22, 2026

An automated routing policy configuration error caused us to leak some Border Gateway Protocol prefixes unintentionally from a router at our Miami data center. We discuss the impact and the changes we are implementing as a result.

BTBryton, Tom StrickxBryton, Tom Strickx·January 23, 2026SRE & Ops
SRE & Ops — DrP: Meta’s Root Cause Analysis Platform at Scale

DrP: Meta’s Root Cause Analysis Platform at Scale

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 [

CWChris Wiltz·December 19, 2025SRE & Ops
SRE & Ops — Get better visibility for the WAF with payload logging

Get better visibility for the WAF with payload logging

The WAF provides ways for our customers to gain insight into why it takes certain actions. The more granular and precise the insight, the more reproducible and understandable it is. Revamped payload logging is one such method.

PPaschalPaschal·November 24, 2025SRE & Ops
SRE & Ops — Zoomer: Powering AI Performance at Meta’s Scale Through Intelligent Debugging and Optimization

Zoomer: Powering AI Performance at Meta’s Scale Through Intelligent Debugging and Optimization

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

CWChris Wiltz·November 21, 2025SRE & Ops
SRE & Ops — Cloudflare outage on November 18, 2025

Cloudflare outage on November 18, 2025

Cloudflare suffered a service outage on November 18, 2025. The outage was triggered by a bug in generation logic for a Bot Management feature file causing many Cloudflare services to be affected.

MPMatthew PrinceMatthew Prince·November 18, 2025SRE & Ops
SRE & Ops — Open Source Is Good for the Environment

Open Source Is Good for the Environment

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 […]

CWChris Wiltz·November 14, 2025SRE & Ops
SRE & Ops — Disaggregated Scheduled Fabric: Scaling Meta’s AI Journey

Disaggregated Scheduled Fabric: Scaling Meta’s AI Journey

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

CWChris Wiltz·October 20, 2025SRE & Ops
SRE & Ops — Branching in a Sapling Monorepo

Branching in a Sapling Monorepo

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

CWChris Wiltz·October 16, 2025SRE & Ops
SRE & Ops — 10X Backbone: How Meta Is Scaling Backbone Connectivity for AI

10X Backbone: How Meta Is Scaling Backbone Connectivity for AI

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 […]

PHPhil Hornshaw·October 16, 2025SRE & Ops
SRE & Ops — Design for Sustainability: New Design Principles for Reducing IT Hardware Emissions

Design for Sustainability: New Design Principles for Reducing IT Hardware Emissions

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, […]

CWChris Wiltz·October 14, 2025SRE & Ops
SRE & Ops — OCP Summit 2025: The Open Future of Networking Hardware for AI

OCP Summit 2025: The Open Future of Networking Hardware for AI

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 […]

CWChris Wiltz·October 13, 2025SRE & Ops
SRE & Ops — Introducing OpenZL: An Open Source Format-Aware Compression Framework

Introducing OpenZL: An Open Source Format-Aware Compression Framework

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 […]

CWChris Wiltz·October 6, 2025SRE & Ops
SRE & Ops — Creating AI agent solutions for warehouse data access and security

Creating AI agent solutions for warehouse data access and security

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. […]

PHPhil Hornshaw·August 13, 2025SRE & Ops
SRE & Ops — Federation Platform and Privacy Waves: How Meta distributes compliance-related tasks at scale

Federation Platform and Privacy Waves: How Meta distributes compliance-related tasks at scale

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 […

CWChris Wiltz·August 11, 2025SRE & Ops
SRE & Ops — How Meta keeps its AI hardware reliable

How Meta keeps its AI hardware reliable

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 […]

CWChris Wiltz·July 22, 2025SRE & Ops