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Deep, recent reads ranked by depth and freshness.

  1. 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

    DatabasesPerformanceRedis

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  2. PHP2Shell: GitLab helps find and remediate critical PHP flaws

    Critical remote code execution vulnerabilities known as PHP2Shell affect the PHP engine across multiple versions, requiring immediate runtime updates to fixed versions or patched distribution packages. The team utilized platform features like container scanning, code search, and automated agent workflows to locate PHP projects and remediate vulnerabilities. Operators must also check logs and environments for signs of compromise as framework updates and input validations cannot prevent these engine-level flaws.

    DEPTH ■■■■■10 min read3 days ago

    ArchitectureSecurity

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  3. 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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  4. 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

    InfrastructureMachine Learning

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  5. 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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  6. 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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  7. 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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  8. 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

    InfrastructureMachine Learning

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  9. 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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  10. Data Mesh at Grab (Part III): Operationalizing data reliability with automated DPIs

    Grab addressed runtime data reliability issues in its data mesh by implementing automated Data Production Issues (DPIs). The system uses an incident orchestrator to detect contract breaches, a Data Health API for cross-platform root cause analysis, and Hugo for automated remediation. This approach resolved 86.9 percent of incidents automatically and made mean time to resolve six times faster.

    DEPTH ■■■■■12 min read8 weeks ago

    DatabasesObservability

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