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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Tag: Microservices
Dead Letter Queues in Kafka: Stop Poison Pills Before They Stop You
A message arrives that your consumer cannot parse. Maybe the producer shipped a new schema without telling anyone, maybe the
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Caching Strategies in Distributed Systems: Cache-Aside, Write-Through, and Surviving the Thundering Herd
Almost every service that survives its own traffic eventually grows a cache. The idea is simple: the database is slow
API Versioning Strategies That Age Well: Headers, Paths, and the Art of Not Breaking Clients
Somewhere between the first integration and the hundredth, every API team hits the same wall: the change you need to
Circuit Breakers in Go: Stopping Cascading Failures Before They Start
Every distributed system has a breaking point. The downstream service you depend on will fail — not “might” fail, will
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CQRS and Event Sourcing in Go: Building Systems That Remember Every Decision
Most CRUD applications follow a predictable pattern: a single database table serves both reads and writes, the same model validates
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Dynamic Secrets: Killing Long-Lived Credentials in Distributed Systems
Most security incidents in distributed systems don’t start with a zero-day exploit. They start with a leaked credential — a
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Zero Trust Architecture in Microservices: Identity, mTLS, and Authorization Policies
The traditional security model for microservices relies on a perimeter: hard outer shell, soft trusted interior. Once a request passes
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Change Data Capture with Debezium: Streaming Database Changes to Kafka
Every production database tells a continuous story — orders placed, statuses updated, accounts created. But most applications treat their database
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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