workflow-orchestration-patterns

# Workflow Orchestration Patterns

Master workflow orchestration architecture with Temporal, covering fundamental design decisions, resilience patterns, and best practices for building reliable distributed systems.

## When to Use Workflow Orchestration

### Ideal Use Cases (Source: docs.temporal.io)

- **Multi-step processes** spanning machines/services/databases
- **Distributed transactions** requiring all-or-nothing semantics
- **Long-running workflows** (hours to years) with automatic state persistence
- **Failure recovery** that must resume from last successful step
- **Business processes**: bookings, orders, campaigns, approvals
- **Entity lifecycle management**: inventory tracking, account management, cart workflows
- **Infrastructure automation**: CI/CD pipelines, provisioning, deployments
- **Human-in-the-loop** systems requiring timeouts and escalations

### When NOT to Use

- Simple CRUD operations (use direct API calls)
- Pure data processing pipelines (use Airflow, batch processing)
- Stateless request/response (use standard APIs)
- Real-time streaming (use Kafka, event processors)

## Critical Design Decision: Workflows vs Activities

**The Fundamental Rule** (Source: temporal.io/blog/workflow-engine-principles):
- **Workflows** = Orchestration logic and decision-making
- **Activities** = External interactions (APIs, databases, network calls)

### Workflows (Orchestration)

**Characteristics:**
- Contain business logic and coordination
- **MUST be deterministic** (same inputs → same outputs)
- **Cannot** perform direct external calls
- State automatically preserved across failures
- Can run for years despite infrastructure failures

**Example workflow tasks:**
- Decide which steps to execute
- Handle compensation logic
- Manage timeouts and retries
- Coordinate child workflows

### Activities (External Interactions)

**Characteristics:**
- Handle all external system interactions
- Can be non-deterministic (API calls, DB writes)
- Include built-in timeo