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
Tag: Distributed Systems
Event Sourcing in Practice: Building a System That Never Forgets
Most systems today use CRUD: read the current state, modify a row, write it back. The database remembers where things
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The Saga Pattern: Coordinating Distributed Transactions in Microservices
Distributed transactions are one of those problems that look simple until you split your monolith into services. In a single
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Zero Trust Microservices: Implementing mTLS in Go
Most microservice architectures still rely on an outdated security model: trust everything inside the network, and defend the perimeter. The
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Implementing Idempotency in Go: Keys, Stores, and Patterns for Reliable APIs
Networks are unreliable. Clients retry requests. Messages get delivered twice. In a distributed system, the question isn’t whether a duplicate
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Rate Limiting Strategies for Production APIs: From Token Buckets to Distributed Throttling
Every public API has a ceiling. Whether you’re running a SaaS platform, a microservice cluster, or a simple REST endpoint,
The Saga Pattern: Distributed Transactions Without the Pain
When a single database holds all your data, transactions are straightforward: begin, commit, rollback. But in a microservices architecture, where
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Hard-Won Engineering Truths: Lessons That Survive Every Tech Cycle
Not “secret knowledge.” More like scars, pattern recognition, and things you only really believe after seeing them fail in production.
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The Outbox Pattern: Solving the Dual-Write Problem in Event-Driven Microservices
Event-driven architecture is the default for most microservices systems today. Services communicate by publishing events to a message broker —
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