InfoQ Homepage Microservices Content on InfoQ
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Uber Automates Dependency Analysis across its Service Mesh
Uber has developed an automated dependency analysis system that uses RPC middleware and production metrics to correlate caller and downstream failures. The approach classifies dependencies as fail-close, fail-open, or unknown and addresses limitations of sampled distributed tracing for rare failures across Uber’s large service mesh.
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Stateless MCP Removes Session Affinity Requirements for AWS Server Deployments
AWS details how the latest Model Context Protocol specification removes protocol-level sessions, sticky-session requirements, and session storage for remote MCP servers. The change enables independent request routing and simpler horizontal scaling while shifting application state, retries, observability, and idempotency concerns to other layers.
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Uber Redesigns M3DB Sharding with Subclusters to Limit Failure Impact
Uber has redesigned shard placement in M3DB with fixed size subclusters to limit the impact of node failures, maintenance, and cluster scaling. The approach bounds shard dependencies, preserves replica isolation, and uses a greedy algorithm to select shard migrations while avoiding a separate rebalancing pass and unnecessary data movement.
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Agoda Replaces 72-Shard SQL Server Price Cache with DragonflyDB
Agoda migrated its 1.5 TB hotel Price Cache from 72 SQL Server shards to DragonflyDB to handle growing read and write volumes. The migration used staged dual reads, parity validation, gradual traffic shifting, and decentralized failover detection. Agoda reports an approximately eightfold reduction in P99 read latency, with two DragonflyDB clusters providing high availability.
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Netflix Reworks Conductor for 420 Million Monthly Workflow Executions and 10X Larger Workflows
Netflix has reworked its Conductor workflow orchestration engine to handle larger workloads, increasing supported workflow size from about 2,500 to 30,000 tasks and reducing p99 workflow evaluation latency by about 40%. Conductor 4.0 separates workflow metadata from task data, moves evaluation to asynchronous processing, and introduces dynamic worker allocation and concurrency controls.
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Uber Builds GitFarm to Run Git Operations as a Service for Large-Scale Monorepos
Uber’s GitFarm provides Git operations as a centralized service, eliminating local repository clones across large scale monorepo workloads. The platform uses prewarmed checkouts, ephemeral sandboxes, repository synchronization, and gRPC streaming to reduce resource consumption and startup latency for automation services operating across thousands of repositories.
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How Netflix Scaled its Real-Time Service Map
Netflix has described how it redesigned the streaming pipeline behind Service Topology, its real-time service dependencies map, to support production scale. The system uses three stages to separate intermediary resolution from enrichment and persistence, propagates backpressure to Kafka rather than dropping records, and uses server-sent events instead of gRPC for high-volume internal transfers.
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Canva Shares S3 Based Architecture for Session Revocation across Hundreds of Millions of Sessions
Canva redesigned session revocation infrastructure to support 100M active sessions while reducing database lookups. The architecture uses Amazon S3 for durable revocation records and distributes compact, in-memory indexes to application gateways. Canva said the design improved deployment speed, reduced database infrastructure requirements, and cut the revocation cache memory footprint by 87.5%.
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JioHotstar Explains the Distributed Engineering behind Personalized Ad Requests at Streaming Scale
JioHotstar explains the distributed architecture behind its real-time ad request workflow, covering ad decisioning, waterfall tiering, pacing algorithms, latency optimization, and service coordination required to select and deliver personalized advertisements during streaming playback at scale.
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DoorDash Uses Envoy and Valkey for a 1.5M RPS Proxy Cache with 99.99999% Availability
DoorDash has developed Entity Cache, a transparent proxy caching platform built on Envoy and Valkey to reduce redundant service-to-service requests across its microservices architecture. Operating within DoorDash’s service mesh, the platform serves over 1.5M requests per second with 99.99999% availability through caching, event-driven invalidation, failure handling, and performance optimizations.
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How DoorDash Built an AI Shopping Assistant That Doesn’t Rely on the LLM Alone
DoorDash details the architecture behind Ask DoorDash, its AI-powered conversational shopping assistant, combining LLMs, specialized AI agents, MCP-based tooling, and an intelligence layer with persistent consumer memory and live backend data. Early results show up to 24% higher checkout conversion, 17% larger baskets, and improved intent accuracy using memory-backed sessions.
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Airbnb Shares Architecture behind Sitar-Agent Dynamic Configuration Sidecar for Kubernetes Services
Airbnb engineers detailed Sitar-agent, a Kubernetes sidecar for dynamic configuration delivery across tens of thousands of pods, processing updates several times per minute. The system was redesigned with Java, Amazon S3 snapshot bootstrapping, and a migration from Sparkey to SQLite to improve reliability, startup performance, and configuration availability at scale.
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How Netflix Maps Thousands of Microservices in Real-Time
Netflix has shared details about Service Topology. This internal system creates and updates a live dependency graph for thousands of microservices. It helps engineers see how services connect and resolve issues more quickly. The system merges three separate data sources into a single, queryable graph. It updates almost in real-time as traffic patterns shift.
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Shopify Reports 15X Faster Graphql Execution with Breadth First Engine
Shopify introduced GraphQL Cardinal, a new execution engine replacing depth-first traversal with breadth-first execution. The redesign improves large-scale GraphQL performance with up to 15x faster field execution, 6x lower GC overhead, and +4s P50 latency gains. It focuses on execution-layer efficiency and batched resolver processing for high-cardinality commerce queries.
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Cloudflare Introduces Workflows V2 with Deterministic Execution and 50K Concurrent Workflows
Cloudflare introduces Workflows V2, a redesigned distributed workflow orchestration system with deterministic replayable execution, improved observability, and major scaling upgrades, including 50,000 concurrent instances and 2M queued workflows. It supports AI agents, data pipelines, and background processing with improved reliability across distributed systems.