
Database Sharding Strategies and Trade-Offs
A practical guide to database sharding — covering partitioning strategies, shard key selection, cross-shard queries, and the operational complexity that comes with distributing data.
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A practical guide to database sharding — covering partitioning strategies, shard key selection, cross-shard queries, and the operational complexity that comes with distributing data.

A practical guide to consensus algorithms — covering Raft, Paxos, and leader election patterns with real-world examples of when and why distributed systems need them.

How to implement timeouts, retries, and backoff strategies that prevent cascading failures in distributed architectures.

A deep dive into rate limiting algorithms with implementations, trade-offs, and guidance on choosing the right approach for your API.

Network failures mean requests are retried — idempotent API design ensures that processing the same request twice produces the same result, preventing duplicate charges and orders.

When a downstream service is failing, continuing to send requests makes everything worse — the circuit breaker pattern stops the cascade by failing fast.

Event-driven systems decouple producers from consumers through asynchronous message passing — but eventual consistency, ordering guarantees, and idempotency introduce real complexity.

RabbitMQ, Redis Streams, or Kafka — understanding the messaging patterns behind decoupled, resilient systems and when each tool fits.