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Module 10: Production Patterns

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Stub module — Full content to be generated. This file defines the scope and prerequisites so the topic roadmap is complete.

Overview

There is a substantial gap between "async code that works in development" and "async service that runs reliably in production for months." This module bridges that gap. Topics covered: graceful shutdown (draining in-flight work before exiting on SIGTERM), health check endpoints, worker pool patterns, structured logging in async contexts, and distributed tracing integration. These are not nice-to-haves — they are the difference between a service that can be operated and one that cannot.

Table of Contents

  1. Overview
  2. Prerequisites
  3. Objectives
  4. Theory
  5. Key Concepts
  6. Examples
  7. Common Pitfalls
  8. Cross-Links
  9. Summary

Prerequisites

  • Module 09: Testing Async Code
  • Module 07: Performance Patterns
  • Module 06: Structured Concurrency

Objectives

By the end of this module, you will be able to:

  1. Implement graceful shutdown: handle SIGTERM, drain pending work, close connections
  2. Write health check endpoints that verify event loop, database, and dependency health
  3. Build worker pool services that scale with configurable concurrency
  4. Add structured logging to async services with proper correlation IDs
  5. Integrate OpenTelemetry tracing in an asyncio service
  6. Diagnose production async issues: event loop blocking, task leaks, slow callbacks

Theory

Full content to be generated. Topics to cover:

  • Graceful shutdown: loop.add_signal_handler(SIGTERM, ...), draining queues, cancelling background tasks, awaiting cleanup
  • Health checks: liveness vs. readiness probes; async health check patterns
  • Worker pool architecture: configurable parallelism, dynamic scaling
  • Structured logging: structlog with asyncio; avoiding log contention
  • Context variables: contextvars.ContextVar for request-scoped data (trace IDs, user context) in async code
  • OpenTelemetry: async span propagation, context manager patterns
  • Debugging production: asyncio.set_event_loop_policy(), loop.set_debug(True), aiomonitor
  • Task leak detection: asyncio.all_tasks() monitoring

Key Concepts

To be filled in when this module is fully generated.

Examples

To be filled in when this module is fully generated.

Common Pitfalls

To be filled in when this module is fully generated.

  • [[async-python/modules/09_testing-async]] — prerequisite
  • [[async-python/modules/11_capstone-project]] — the capstone requires a production-ready service with graceful shutdown and health checks
  • [[systems-architecture]] — graceful shutdown and health checks are architectural concerns not specific to asyncio

Summary

To be filled in when this module is fully generated.