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01Cloudflare · architecture
Origin Range Requests: Serving large files without range-request tuning
Cloudflare replaced a legacy, fixed-size range caching design that suffered from bandwidth waste and memory pressure with a Pingora-based chunk coordinator. The new implementation dynamically combines cached chunks and aligned origin fetches to serve range requests accurately without manual tuning. This approach cut p99 time to first byte in half for R2 storage and reduced tiered cache traffic by six percent.
DEPTH ■■■■■8 min read2 days ago
Databases Performance Redis
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02GitHub · architecture
The bridge to agent-scale Git infrastructure
GitHub faced infrastructure capacity limits and a 25ms cross-region network round trip when migrating repositories to Azure. The team changed the storage quorum from repository-wide locks to per-reference serialization and introduced ephemeral virtual replicas backed by object storage. This raised write throughput, prevented slow replicas from blocking traffic, and decoupled read scaling from the write quorum.
DEPTH ■■■■■8 min read4 days ago
Infrastructure
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03Meta · architecture
The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Do
Meta engineers reduced hallucinations and improved reliability in their data pipeline agents by replacing a single heavyweight LLM orchestrator with a thin deterministic router and fourteen specialized subagents. The thin orchestrator handles routing and reliability checks through a fixed protocol, while isolated subagents execute domain reasoning. This architecture reduced configuration preparation time from a day to under an hour.
DEPTH ■■■■■7 min read6 days ago
Machine Learning
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04Cloudflare · architecture
Bringing post-quantum cryptography to geographically fenced key management
Cloudflare introduced a post-quantum geographically restricted key manager in closed beta to enforce data sovereignty and protect customers against harvest-now-decrypt-later attacks. The team implemented a hybrid ML-KEM-768 and X25519 cryptographic design that separates globally distributed wrapped private keys from regionally restricted root keys. This ensures that decryption keys are only accessible within authorized geographical boundaries and fails closed if validation fails.
DEPTH ■■■■■12 min read2 days ago
Security
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05Meta · architecture
Inside Prometheus: Meta’s Journey to a Gigawatt-Scale Supercluster
Meta built Prometheus, a gigawatt-scale AI supercluster designed to scale up to one million GPUs using multi-generation NVIDIA hardware and specialized backend Ethernet networks. The team achieved high goodput and significantly reduced system interruptions by implementing an in-rack sparing strategy, parallelism-aware fault tolerance, and close co-engineering with vendors. These infrastructure advancements allowed the team to successfully train frontier foundational models like Muse Wonder.
DEPTH ■■■■■17 min read6 days ago
Infrastructure Machine Learning
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06GitHub · architecture
From 2,500 requests to 24: Rebuilding star history without the stargazers
GitHub faced abuse and performance issues because tools were scraping user identities to reconstruct repository star history. The engineering team collaborated with maintainers to build a purpose-built aggregate endpoint that returns daily star counts without identities and filters by time before aggregation. This reduced request volume from thousands to a few dozen and eliminated heavy database scans.
DEPTH ■■■■■8 min read11 days ago
Microservices
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07Cloudflare · performance
Cutting our inference bill by 68% by being obsessive about optimization
An engineering team investigated a steady rise in AI code review costs and found that cache misses and redundant model calls were driving up expenses. By restructuring system prompts to enable cross-repository prompt caching, eliminating wasted tool calls, and switching to more efficient models, the team cut inference costs by 68% while also significantly improving review latency.
DEPTH ■■■■■15 min read6 days ago
Machine Learning
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08Meta · practice
How Meta Built Forum With AI-Native Engineering
Meta engineers built the Forum app using a human-on-the-loop AI agent workflow that automated planning, building, testing, and verification. By shifting focus from code generation to automated verification, tooling improvements, and architectural legibility, the team reached feature parity in eight weeks while catching systemic memory issues early.
DEPTH ■■■■■8 min read10 days ago
Frontend Mobile
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09Dropbox · architecture
Evolving our calendar assistant Reclaim to be AI-native without starting over
Dropbox engineers evolved their calendar assistant, Reclaim, to support natural-language AI requests by building a custom agent platform that integrates with existing scheduling logic. They utilized a shared action system and a Preview Mode backed by Redis to ensure AI suggestions are consistent and reviewable before affecting real calendars. This approach allows the product to adopt AI capabilities without fragmenting its core architecture or duplicating functionality.
DEPTH ■■■■■7 min read3 weeks ago
Infrastructure Machine Learning
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10Cloudflare · performance
Yandex outage: Data shows that instead of going dark, malicious bots went on the move
Following physical strikes on Yandex data centers, overall HTTP traffic from the network dropped significantly, leading to speculation that malicious bot farms had been disabled. However, traffic analysis revealed that search crawling simply decreased while malicious automation quickly migrated to other hosting providers with identical fingerprints. Consequently, overall malicious bot traffic remained flat, demonstrating that network disruptions do not stop portable automated workloads.
DEPTH ■■■■■8 min read11 days ago
Incidents & Postmortems
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11Meta · architecture
Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI
Meta developed GEM, a unified recommendation foundation model using an LLM-style architecture called Kunlun to handle heterogeneous ads data across multiple surfaces. The team implemented block attention, custom low-precision kernels, and post-training intelligence transfer techniques like LoopFM and Solaris to scale training efficiency and bypass real-time serving latency bottlenecks. The resulting system delivered an 18.9% conversion improvement and a 12% click-through rate increase across Meta ads surfaces.
DEPTH ■■■■■15 min read12 days ago
Machine Learning
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12GitHub · architecture
Building Git infrastructure for agent-scale development
GitHub is redesigning its Git infrastructure to handle the massive surge in concurrent read and write operations driven by agentic software development and high-volume workloads. The team is decoupling storage from compute by leveraging Azure Blob Storage for durability and lightweight compute workers for requests, which separates scaling dimensions. In internal benchmarks, this approach achieves up to 35 times higher write throughput and independent read scalability.
DEPTH ■■■■■9 min read2 weeks ago
Infrastructure
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13Cloudflare · postmortem
Inside Hyperdrive: How we solved a rare Hyperdrive MySQL caching bug
During the beta of MySQL support for Hyperdrive, engineers investigated rare empty query responses and connection hangs occurring in 0.001% of requests. They discovered that sharing the data center cache between client and endpoint nodes caused protocol capability mismatches when translating MySQL wire messages. The team resolved the issue by standardizing the cache to always store responses encoded with canonical Hyperdrive capabilities.
DEPTH ■■■■■9 min read11 days ago
MySQL
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14Meta · architecture
OCP Summit 2026: Powering AI with Open Innovations in Scale-Up, Scale-Out, and Scale-Across Networks
Meta shared its next-generation open networking infrastructure for AI at the OCP Summit 2026, including liquid-cooled 102.4T switch platforms, multiplane scale-out fabrics, and Ethernet-based scale-up solutions. The team also highlighted collaborative industry standards like ESUN and OSPA to unify hardware and transport layers. These open innovations aim to support massive gigawatt-scale AI clusters across diverse data center environments.
DEPTH ■■■■■12 min read13 days ago
Machine Learning
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15GitHub · architecture
Staying Evergreen: How we automated secure access and repo hygiene in a shared org
Manual repository housekeeping and access reviews for outside collaborators become difficult to maintain as organizations scale. The team built Evergreen, a GitHub App that automates quarterly access reviews and stale repository archiving using native platform features and IssueOps. This automation successfully enforces secure defaults by revoking unanswered access while maintaining a full audit trail in git history.
DEPTH ■■■■■8 min read10 days ago
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16Cloudflare · architecture
Under the hood, off the hot path: How D1 scales to millions of databases
Cloudflare scaled its serverless SQLite database, D1, to support millions of databases by decoupling the control plane from the data plane. The team used distributed metadata caching via Workers KV, optimized database connections through Hyperdrive, and implemented a self-correcting heartbeat mechanism. This architecture prevents centralized bottlenecks and allows D1 to handle rapid on-demand database creation efficiently.
DEPTH ■■■■■22 min read12 days ago
Databases
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17Cloudflare · scaling
Rewinding the exponential: How we keep hardware usage down
Cloudflare tackled exponential traffic growth against linear hardware growth by continuously evolving their data pipeline architecture over five years. Key optimizations included breaking up monolithic schemas, switching to zstd compression, decoupling pipeline transit from database replication, decentralizing sampling, and moving aggregations earlier in the pipeline. These strategies significantly reduced backbone bandwidth usage, network congestion, and storage requirements while preserving data quality.
DEPTH ■■■■■12 min read12 days ago
Infrastructure
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18Meta · architecture
GenRecs Tokenization: Transforming Ads Recommendation at Meta with Stable Model Vocabulary
Meta implemented GenRecs Tokenization to replace dedicated item IDs with a stable semantic vocabulary for ads recommendation. Using a three-stage encoding and quantization pipeline, the system enables language models to reason about ad content and user preferences simultaneously. This approach resulted in a +0.35% lift in conversions and improved cold-start performance for new entities.
DEPTH ■■■■■6 min read6 days ago
Machine Learning
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19GitHub · migration
Improving site performance by shipping more CSS
GitHub faced performance degradation on server-side rendering and initial page loads due to scaling issues with its CSS-in-JS solution. The engineering team executed a multi-year migration to CSS Modules and eliminated dynamic styling props using incremental rollouts, wrapper components, and automation tools. This resulted in significant performance gains, including 55% faster server-side rendering and the complete removal of styled-components.
DEPTH ■■■■■8 min read4 weeks ago
Frontend Performance
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20Cloudflare · architecture
Filter, reshape, and redact logs before export with Transformers
Cloudflare integrated SQL-based log transformation directly into its Logpush export pipeline, allowing customers to filter, redact, and reshape logs before delivery. The team chose to embed the Apache DataFusion engine in-process using Rust and Go across an Arrow IPC boundary to ensure high throughput and avoid network latency. As a result, the system processes high-volume log streams efficiently while maintaining predictable resource usage and strict delivery reliability.
DEPTH ■■■■■8 min read13 days ago
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