Tag: distributed-systems

How to design and implement idempotent API endpoints that safely handle retries, duplicate requests, and network failures without side effects.

Choose between synchronous and asynchronous communication patterns for resilient microservices architectures.

Implement resilient retry strategies with exponential backoff, jitter, and circuit breaker integration for transient failure recovery.

Orchestrate complex business processes with workflow engines, state machines, and long-running task coordination across distributed services.

Build resilient systems by intentionally injecting failures and observing how your distributed services respond and recover.

Design idempotent message processors that safely handle duplicate deliveries without side effects in async and event-driven systems.

Coordinate a single active instance among multiple distributed nodes to avoid conflicts and split-brain scenarios.

Distribute data across nodes with partitioning so each node owns a shard. Horizontal scaling without shared state, with locality and fault isolation per partition.

Reliably publish domain events by persisting them in an outbox table within the same database transaction as the business operation.

A practical guide to microservices: benefits, trade-offs, common patterns, and when to choose them over monoliths. Covers decomposition strategies and operational complexity.

A practical guide to system design interviews: scalability, databases, caching, load balancing, microservices, and how to structure your answer.

A practical guide comparing ACID and BASE consistency models: when to choose strong consistency, when to accept eventual consistency, and how each affects system design.

A practical guide to the CAP theorem: consistency, availability, and partition tolerance. Learn how to choose the right trade-offs for your application.

A thorough guide to message queues: when to use RabbitMQ, Kafka, or SQS. Covers patterns, throughput, ordering, and operational considerations.