workflow-orchestration-patterns

Automation & Intégrations

Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.

Documentation

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
External system processes asynchronously
Sends signal to resume workflow
Workflow continues with response

Use Cases:

Human approval workflows
Webhook callbacks
Long-running external processes

State Management and Determinism

Automatic State Preservation

How Temporal Works (Source: docs.temporal.io/workflows):

Complete program state preserved automatically
Event History records every command and event
Seamless recovery from crashes
Applications restore pre-failure state

Determinism Constraints

Workflows Execute as State Machines:

Replay behavior must be consistent
Same inputs → identical outputs every time

Prohibited in Workflows (Source: docs.temporal.io/workflows):

❌ Threading, locks, synchronization primitives
❌ Random number generation (random())
❌ Global state or static variables
❌ System time (datetime.now())
❌ Direct file I/O or network calls
❌ Non-deterministic libraries

Allowed in Workflows:

workflow.now() (deterministic time)
workflow.random() (deterministic random)
✅ Pure functions and calculations
✅ Calling activities (non-deterministic operations)

Versioning Strategies

Challenge: Changing workflow code while old executions still running

Solutions:

1.Versioning API: Use workflow.get_version() for safe changes
2.New Workflow Type: Create new workflow, route new executions to it
3.Backward Compatibility: Ensure old events replay correctly

Resilience and Error Handling

Retry Policies

Default Behavior: Temporal retries activities forever

Configure Retry:

Initial retry interval
Backoff coefficient (exponential backoff)
Maximum interval (cap retry delay)
Maximum attempts (eventually fail)

Non-Retryable Errors:

Invalid input (validation failures)
Business rule violations
Permanent failures (resource not found)

Idempotency Requirements

Why Critical (Source: docs.temporal.io/activities):

Activities may execute multiple times
Network failures trigger retries
Duplicate execution must be safe

Implementation Strategies:

Idempotency keys (deduplication)
Check-then-act with unique constraints
Upsert operations instead of insert
Track processed request IDs

Activity Heartbeats

Purpose: Detect stalled long-running activities

Pattern:

Activity sends periodic heartbeat
Includes progress information
Timeout if no heartbeat received
Enables progress-based retry

Best Practices

Workflow Design

1.Keep workflows focused - Single responsibility per workflow
2.Small workflows - Use child workflows for scalability
3.Clear boundaries - Workflow orchestrates, activities execute
4.Test locally - Use time-skipping test environment

Activity Design

1.Idempotent operations - Safe to retry
2.Short-lived - Seconds to minutes, not hours
3.Timeout configuration - Always set timeouts
4.Heartbeat for long tasks - Report progress
5.Error handling - Distinguish retryable vs non-retryable

Common Pitfalls

Workflow Violations:

Using datetime.now() instead of workflow.now()
Threading or async operations in workflow code
Calling external APIs directly from workflow
Non-deterministic logic in workflows

Activity Mistakes:

Non-idempotent operations (can't handle retries)
Missing timeouts (activities run forever)
No error classification (retry validation errors)
Ignoring payload limits (2MB per argument)

Operational Considerations

Monitoring:

Workflow execution duration
Activity failure rates
Retry attempts and backoff
Pending workflow counts

Scalability:

Horizontal scaling with workers
Task queue partitioning
Child workflow decomposition
Activity batching when appropriate

Additional Resources

Official Documentation:

Temporal Core Concepts: docs.temporal.io/workflows
Workflow Patterns: docs.temporal.io/evaluate/use-cases-design-patterns
Best Practices: docs.temporal.io/develop/best-practices
Saga Pattern: temporal.io/blog/saga-pattern-made-easy

Key Principles:

1.Workflows = orchestration, Activities = external calls
2.Determinism is non-negotiable for workflows
3.Idempotency is critical for activities
4.State preservation is automatic
5.Design for failure and recovery
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