Distributed Rate Limiting in Go: GCRA, Redis, and the Pitfalls Nobody Warns You About
Every production rate limiter has two layers. The first layer is the algorithm: token bucket, leaky bucket, fixed window, sliding
Tag: distributed-systems
The Transactional Outbox Pattern in Go: Reliable Events Without Dual Writes
# POST 1: Transactional Outbox (Slot 10 backend) You update a row in your database, then publish an event to
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Load Balancing Beyond Round Robin: Least Outstanding Requests and Consistent Hashing
Here is a failure mode that shows up in every system with more than two backends: round robin distributes requests
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The Transactional Outbox Pattern: Reliable Events Without Distributed Transactions
Solve the dual-write problem with one extra table and SKIP LOCKED: a working Go implementation of the transactional outbox, plus the delivery-semantics gotchas that bite in production. … Continue readingThe Transactional Outbox Pattern: Reliable Events Without Distributed Transactions
Distributed Tracing in Go with OpenTelemetry
When a request crosses five services and the latency budget blows up, a single log line rarely tells you where
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The Strangler Fig Pattern: Incrementally Migrating Legacy Systems Without the Big Rewrite
Every engineering team eventually faces the same daunting question: what do we do with the legacy monolith? The temptation is
The Saga Pattern in Distributed Systems: Orchestrating Transactions Across Microservices
Every developer who has worked with microservices eventually hits the same wall: a single business operation needs to touch multiple
OpenTelemetry in 2026: Profiles, Arrow Pipelines, and the Path to Unified Observability
OpenTelemetry has had a remarkable 2026. What started as a project to unify traces, metrics, and logs has grown into
The Circuit Breaker Pattern in Go: Preventing Cascading Failures in Distributed Systems
When one service in a distributed system starts failing, the cascade can bring down everything downstream. A slow database connection
Event Sourcing in Practice: Building Audit-Friendly Systems with Python and PostgreSQL
Most applications store data the same way: overwrite the current state and move on. A customer changes their address? Update