System Design for DevOps · Module 04

Communication and Asynchronous Processing

How parts of a system talk: decouple producers and consumers with queues and streams, protect workers with backpressure and batching, design APIs that are safe to retry and rate-limited, and let a service mesh handle discovery, mTLS and traffic policy.

Practice interactively →

What you will learn

• Choose between synchronous calls, message queues and event streams
• Fix push-overload with pull-based consumers, backpressure and batching
• Design idempotent, paginated, versioned and rate-limited APIs
• Explain service discovery and what a service mesh adds

Lessons

1. Message Queues and Event Streams

   Message queues and streams let producers hand off work without waiting for consumers; consumers pull at their own pace, so a slow or crashed consumer no longer breaks the producer. Queues distribute tasks, streams keep an ordered, replayable log.

2. Backpressure, Batching and Throughput

   When input grows faster than a pipeline can process it, queues fill, latency explodes and nodes fall over; backpressure, bounded queues, batching, parallel workers and autoscaling on backlog keep throughput stable.

3. API Design: Idempotency, Pagination and Rate Limiting

   Good APIs are predictable under failure and load: idempotency keys make retries safe, cursor pagination keeps large lists fast, versioning avoids breaking clients, and rate limiting protects the service with clear 429 responses.

4. Service Discovery and Service Mesh

   Services find each other through DNS-based discovery; a service mesh adds a sidecar or node proxy to every workload to handle mTLS, retries, timeouts, traffic splitting and telemetry without changing application code.