Tag: distributed-systems
Browse 15 practical software engineering resources tagged with "distributed-systems". Discover code recipes, design patterns, documentation templates, and in-depth guides to help you build, deploy, and maintain production-ready solutions involving distributed-systems. Each resource is written for engineers who ship real systems, with copy-paste examples and practical trade-offs.
Distributed Systems Engineering
Distributed systems connect independent components over a network. They enable scale and resilience but introduce failures in communication, consensus, time, and consistency that do not exist in single-node programs.
The resources below cover CAP theorem, consensus, leader election, idempotency, distributed transactions, failure modes, and observability. Each guide helps you reason about trade-offs and build systems that fail gracefully.
Every resource includes clear explanations, copy-paste code, and practical warnings. Use them to make informed decisions, avoid production pitfalls, and speed up your delivery. If you are just getting started, read the beginner-friendly articles first; if you are experienced, jump straight to the advanced patterns and architecture guides. New resources are added regularly, so bookmark this page and check back for the latest patterns.
Idempotent API Endpoints
How to design and implement idempotent API endpoints that safely handle retries, duplicate...
Microservices Communication Patterns
Choose between synchronous and asynchronous communication patterns for resilient microservices...
Retry with Exponential Backoff
Implement resilient retry strategies with exponential backoff, jitter, and circuit breaker...
Workflow Engines
Orchestrate complex business processes with workflow engines, state machines, and long-running task...
UUID Generation in Python, JavaScript, and Java
Generate universally unique identifiers (UUIDs) for database keys, session tokens, and resource...
Chaos Engineering
Build resilient systems by intentionally injecting failures and observing how your distributed...
Message Processing Idempotency
Make message processing idempotent so duplicate deliveries don't trigger side effects in...
Leader Election Pattern
Coordinate a single active instance among multiple distributed nodes to avoid conflicts and...
Geode Pattern
Distribute data across nodes with partitioning so each node owns a shard. Horizontal scaling...
Outbox Pattern
Reliably publish domain events by persisting them in an outbox table within the same database...
Microservices Architecture — When to Use and When Not To
A practical guide to microservices: benefits, trade-offs, common patterns, and when to choose them...
System Design Interview Guide: Key Concepts
A practical guide to system design interviews: scalability, databases, caching, load balancing,...
ACID vs BASE — Consistency Models Explained
A practical guide comparing ACID and BASE consistency models: when to choose strong consistency,...
CAP Theorem and Database Trade-offs
A practical guide to the CAP theorem: consistency, availability, and partition tolerance. Learn how...
Message Queues — RabbitMQ, Kafka, and SQS detailed analysis
A thorough guide to message queues: when to use RabbitMQ, Kafka, or SQS. Covers patterns,...