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Read what ships.

Deep, recent reads ranked by depth and freshness.

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  1. 01Grab · architecture

    App stability at scale with a layered defense

    To maintain app stability amidst rapid weekly releases and AI-generated code, Grab uses a layered defense strategy covering prevention, release gates, and incident response. This pipeline includes static analysis via custom lint rules, multiple tiers of automated and manual testing, a pre-production early access build, staged rollouts, and feature flags with instant kill switches. As a result, critical defects are caught early in the development lifecycle before reaching the wider production user base.

    DEPTH ■■■■■16 min read4 days ago

    MobileReliability

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  2. 02Go · performance

    Better HTTP/1 connection reuse

    Failing to read an HTTP/1 response body completely prevents connection reuse, forcing clients to repeatedly pay the high cost of TCP and TLS handshakes. While developers previously had to implement complex manual body-draining logic, Go 1.27 introduces automatic asynchronous response draining in the net/http package. This improvement allows developers to simply close response bodies without worrying about connection pooling performance.

    DEPTH ■■■■■7 min read11 days ago

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  3. 03Grab · architecture

    Powering AI-led research through simulation

    The engineering team built a self-contained simulation platform called sim-rs to model marketplace dispatch dynamics and accelerate experimentation. By connecting automated software agents to this simulator with strict safety safeguards, the team successfully optimized strategy policies and simulator performance. This closed-loop lab environment allows agents to test ideas rapidly while ensuring that only valid, production-ready improvements are produced.

    DEPTH ■■■■■10 min read2 weeks ago

    Machine Learning

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  4. 04Go · architecture

    Arch-specific SIMD in Go

    Go 1.27 introduces the archsimd package to provide low-level architecture-specific SIMD intrinsics for amd64, arm64, and wasm without requiring assembly. The API uses sensible naming conventions, zero-cost type reinterpretation, and opaque masks to improve usability and maintainability while achieving high performance. The resulting design enables developers to write optimized vectorized code safely with proper runtime CPU feature checking and compiler optimizations.

    DEPTH ■■■■■12 min read3 weeks ago

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  5. 05Grab · architecture

    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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