Netflix Tech Stack
Netflix's tech stack through clients, backend services, data systems, and observability.
Architecture case studies that trace how real companies changed systems under growth, incidents, cost pressure, and shifting product demands.
Netflix's tech stack through clients, backend services, data systems, and observability.
Uber’s API layer shifted from one gateway to layered domain-specific gateways.
Discord scaled message storage by moving from MongoDB to Cassandra to ScyllaDB.
Netflix API evolution from monolith to aggregation gateway and federated graph.
Uber's stack for real-time dispatch, platform services, data, and operations.
Slack messages flow through durable writes, fan-out, and live client sync.
Shopify payment system principles for retries, isolation, idempotency, and flow control.
Reddit architecture for high-read traffic, community workloads, and gradual scaling.
Airbnb’s move from a Rails monolith to service boundaries shaped by team ownership.
Netflix Java usage across microservices, tooling, and JVM operations.
Large frontend monorepos through dependency graphs, selective builds, and tooling.
Netflix's CI/CD pipeline through planning, immutable artefacts, rollout control, and telemetry.
Netflix's architecture through clients, edge services, data platforms, and content delivery.
Large scale push messaging with filtering, scheduling, and provider fan-out.
Airbnb architecture from monolith growth to service boundaries and platform scaling.
Netflix's database stack through workload-specific storage, caching, and analytics systems.
Four Netflix caching patterns for latency reduction, scale, and stream delivery.
Push notification architecture for routing, preferences, delivery, and retries.
Large video uploads through chunked ingest, transcoding pipelines, and global storage.
Tweet recommendation through candidate retrieval, ranking, filtering, and mixing.
Stack Overflow architecture through a read-heavy monolith, SQL, and caching.
Uber's CI/CD stack for builds, testing, deployment, and release control.
Event-driven architecture through schemas, SDKs, gateways, and platform governance.
Levelsfyi scaling with Google Sheets, manual workflows, and gradual backend evolution.
Meta’s SapFix pipeline finds reproducible crashes and proposes constrained repairs.
Telegram security through cloud chat encryption and optional secret chats.
Pinterest clone-time reduction through shallower Git fetches in build pipelines.
How Figma scaled Postgres with replication, partitioning, and workload isolation.