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Deep, recent reads ranked by depth and freshness.

  1. Automate medical coding with Step Functions and Amazon Bedrock AgentCore

    Automating medical coding requires a hybrid approach that combines deterministic orchestration with bounded agentic reasoning to ensure safety, auditability, and human oversight. The team built a workflow using AWS Step Functions, AWS Lambda, and Amazon Bedrock AgentCore that evaluates terms cheapest-first via block-lists, exact matching, and finally an LLM agent for ambiguous cases. This design successfully autocodes confident cases while routing ambiguous ones to human reviewers with full audit trails and decision explanations.

    DEPTH ■■■■■15 min read3 days ago

    AWS

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  2. 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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  3. 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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  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. Multi-region disaster recovery for Amazon API Gateway WebSocket APIs

    Real-time applications using WebSocket connections face disruptions during regional AWS outages because connections are tied to specific regions. The team implemented an active-passive multi-region disaster recovery architecture using Route 53 DNS failover, DynamoDB Global Tables, an automated canary health probe, and client-side exponential backoff with jitter. This design automatically detects failures, redirects traffic, and restores client state without manual intervention.

    DEPTH ■■■■■10 min read11 days ago

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  6. 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

    FrontendMobile

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  7. How UTS established a modern curriculum data services foundation on AWS

    University of Technology Sydney rearchitected its curriculum data integration using serverless AWS services to decouple systems of record from downstream consumers. By implementing domain-driven design with an event-driven architecture and purpose-built persistence layers, the team achieved zero production incidents, low latency, and reduced operational overhead while managed by a single engineer.

    DEPTH ■■■■■9 min read11 days ago

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  8. 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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  9. Scope workloads and share resilience policies with AWS Resilience Hub

    Engineering teams often struggle to scope workloads and maintain up-to-date resilience policies in shared Kubernetes clusters after migrations or deployments. AWS Resilience Hub introduced features enabling Kubernetes label-based resource scoping, generative AI-powered dependency insights, and cross-account resilience policy sharing via AWS Organizations. These capabilities allow teams to isolate specific workloads, prioritize dependency investigations, and enforce centralized recovery standards.

    DEPTH ■■■■■14 min read11 days ago

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  10. 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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  11. Stopping business email compromise with AI-driven email security: How VIPRE protects modern enterprises on AWS

    VIPRE developed an AI-driven, cloud-native email security solution on AWS to protect enterprises against business email compromise and advanced phishing attacks. The system uses layered machine learning, semantic analysis, and dynamic sandboxing orchestrated via serverless containers and message queues to evaluate over half a million messages daily. In production testing, the architecture successfully identified thousands of BEC attempts while maintaining low-latency processing and reducing administrative overhead.

    DEPTH ■■■■■12 min read12 days ago

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  12. 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 read12 days ago

    Machine Learning

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  13. Bulk Executor for Amazon DynamoDB, Part 2: Lessons we learned the hard way

    Engineering a bulk execution tool for Amazon DynamoDB using AWS Glue required addressing several architectural challenges, including cost estimation, graceful job termination, and error handling across hundreds of parallel workers. The team overcame limitations in CloudWatch logging and the Spark connector by combining serverless execution with direct API calls and distributed rate limiting. As a result, the tool provides a scalable, script-like interface for managing large-scale table operations safely.

    DEPTH ■■■■■14 min read12 days ago

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  14. 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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  15. Agentic antimicrobial resistance surveillance with AWS HealthOmics and Amazon Bedrock AgentCore

    Processing public bacterial sequencing data for antimicrobial resistance surveillance typically requires specialized bioinformatics and SQL skills. To streamline this process, the team built a reference architecture using AWS HealthOmics, Amazon S3 Tables, and an Amazon Bedrock AgentCore conversational agent that ingests raw reads, normalizes findings, and answers plain-language questions with cited evidence. The resulting system automates the path from public accession numbers to natural-language epidemiological answers.

    DEPTH ■■■■■10 min read13 days ago

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  16. 2026 World Cup: Breaking Records, Spiky Charts and Reliability at Scale

    Meta's infrastructure handled record-breaking traffic during the 2026 World Cup, including 30 million messages per second on WhatsApp, by relying on automated load balancing, capacity buffers, and targeted pre-builds. Traffic patterns revealed that surges occurred primarily during breaks rather than gameplay, requiring region-specific forecasting rather than cross-region load shifting. The systems maintained full reliability and allowed normal continuous deployment schedules to continue without manual intervention or system freezes.

    DEPTH ■■■■■5 min read10 days ago

    Infrastructure

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  17. Deploy Oracle Database step by step on Amazon EVS with FSx for ONTAP

    This post provides a step-by-step guide to deploying Oracle Database 19c on Amazon Elastic VMware Service using Amazon FSx for NetApp ONTAP as an NFS datastore. It covers provisioning storage, mounting datastores, installing Oracle, configuring SnapMirror for cross-region disaster recovery, and outlining four migration paths. The result is a fully functional enterprise database deployment that preserves existing operational workflows.

    DEPTH ■■■■■11 min read3 weeks ago

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  18. Shipping Media Over QUIC at Meta Scale for Instagram Live Ingest

    Meta deployed the emerging Media over QUIC (MoQ) protocol for Instagram Live ingest on iOS and Android to replace their legacy RUSH protocol. By using edge translation to avoid backend rewrites and a phased rollout strategy, the team achieved metric parity with the old protocol without regressions. This deployment establishes a foundation to extend MoQ across Meta's applications for lower-latency and more resilient video streaming.

    DEPTH ■■■■■8 min read13 days ago

    FrontendMobile

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  19. Architect highly available Oracle Database on Amazon EVS and FSx for ONTAP

    Enterprises migrating Oracle databases to Amazon Elastic VMware Service face challenges with storage latency, disaster recovery, and operational consistency. The team designed a highly available architecture combining Amazon EVS bare metal instances with Amazon FSx for NetApp ONTAP NFS datastores and cross-region SnapMirror replication. The resulting setup delivers sub-millisecond storage latency, preserved VMware operational workflows, and robust disaster recovery capabilities.

    DEPTH ■■■■■12 min read3 weeks ago

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  20. Deploy open source Regional availability tools in your VPC

    Engineering teams planning multi-Region architectures often struggle with evaluating AWS service availability and managing compliance risks. The team built and open-sourced two VPC-hosted solutions that deploy an automated Regional availability dashboard and a workload analysis pipeline using CloudTrail and CloudFormation. This setup allows organizations to securely filter and inspect the 20 to 30 services they actually use instead of hundreds.

    DEPTH ■■■■■13 min read3 weeks ago

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