Workflow Orchestration Patterns

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

Use this skill when

• Working on workflow orchestration patterns tasks or workflows
• Needing guidance, best practices, or checklists for workflow orchestration patterns

Do not use this skill when

• The task is unrelated to workflow orchestration patterns
• You need a different domain or tool outside this scope

Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

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 timeouts and retry logic
• Must be idempotent (calling N times = calling once)
• Short-lived (seconds to minutes typically)

Example activity tasks:

• Call payment gateway API
• Write to database
• Send emails or notifications
• Query external services

Design Decision Framework

Does it touch external systems? → Activity
Is it orchestration/decision logic? → Workflow

Core Workflow Patterns

1. Saga Pattern with Compensation

Purpose: Implement distributed transactions with rollback capability

Pattern (Source: temporal.io/blog/compensating-actions-part-of-a-complete-breakfast-with-sagas):

For each step:
  1. Register compensation BEFORE executing
  2. Execute the step (via activity)
  3. On failure, run all compensations in reverse order (LIFO)

Example: Payment Workflow

1. Reserve inventory (compensation: release inventory)
2. Charge payment (compensation: refund payment)
3. Fulfill order (compensation: cancel fulfillment)

Critical Requirements:

• Compensations must be idempotent
• Register compensation BEFORE executing step
• Run compensations in reverse order
• Handle partial failures gracefully

2. Entity Workflows (Actor Model)

Purpose: Long-lived workflow representing single entity instance

Pattern (Source: docs.temporal.io/evaluate/use-cases-design-patterns):

• One workflow execution = one entity (cart, account, inventory item)
• Workflow persists for entity lifetime
• Receives signals for state changes
• Supports queries for current state

Example Use Cases:

• Shopping cart (add items, checkout, expiration)
• Bank account (deposits, withdrawals, balance checks)
• Product inventory (stock updates, reservations)

Benefits:

• Encapsulates entity behavior
• Guarantees consistency per entity
• Natural event sourcing

3. Fan-Out/Fan-In (Parallel Execution)

Purpose: Execute multiple tasks in parallel, aggregate results

Pattern:

• Spawn child workflows or parallel activities
• Wait for all to complete
• Aggregate results
• Handle partial failures

Scaling Rule (Source: temporal.io/blog/workflow-engine-principles):

• Don't scale individual workflows
• For 1M tasks: spawn 1K child workflows × 1K tasks each
• Keep each workflow bounded

4. Async Callback Pattern

Purpose: Wait for external event or human approval

Pattern:

• Workflow sends request and waits for signal
• Ex