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Deep, recent reads ranked by depth and freshness.

Data Engineeringremove filterDistributed Systemsremove filterReliabilityremove filterClear all

  1. 01The Pragmatic Engineer · architecture

    The Pulse: Anthropic builds its own source control system

    Anthropic experienced a massive increase in code merges due to the heavy use of AI coding agents, which quickly overwhelmed standard Git scaling limits and CI checkouts. To solve this, a small engineering team built a custom centralized version control system called Scion backed by Google Spanner and Cloud Storage, along with a code review tool called Antique. This move successfully migrated the entire monorepo off Git and eliminated bottlenecks, though the architecture drew controversy over similarities to Meta's Mononoke.

    DEPTH ■■■■■12 min read3 days ago

    ArchitectureDistributed Systems

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  2. 02Grab · 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 read5 days ago

    MobileReliability

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  3. 03Zalando · postmortem

    Thundering herd of circuit breakers

    An engineering team investigated why a client-side circuit breaker repeatedly failed to close on its own after an outage. By exporting OpenTelemetry traces into a custom visualization tool, they discovered that low probe traffic caused the autoscaler to scale down the service to minimum capacity, triggering a thundering herd of requests and immediate timeouts the moment the circuit breaker closed. Adjusting the system to account for capacity and probe representativeness prevents this oscillation.

    DEPTH ■■■■■10 min read2 weeks ago

    MicroservicesObservabilityReliability

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  4. 04Grab · architecture

    Smarter personalization: How property data helps us understand user price sensitivity

    Existing user personalization systems fail to systematically account for residential property values, leading to one-dimensional profiles and regional blind spots. A conceptual four-step method is proposed that combines public property data, large language models, building-level price estimation, and hierarchical clustering to classify user affluence. The approach remains unimplemented, with future viability depending on technical validation, data quality, and privacy approvals.

    DEPTH ■■■■■4 min read2 weeks ago

    Data EngineeringMachine Learning

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  5. 05Grab · architecture

    GrabMart data for faster disease outbreak detection

    The organization proposes a conceptual data pipeline to analyze aggregated GrabMart transaction data for symptom-related product demand, aiming to supplement clinical surveillance for disease outbreaks. The design relies on data aggregation, statistical baseline comparisons, and privacy safeguards like differential privacy without involving individual health inference. The system remains in an early planning phase requiring rigorous validation, privacy review, and public health oversight.

    DEPTH ■■■■■5 min read13 days ago

    Data EngineeringMachine Learning

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