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workflow-orchestration-patterns

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from rmyndharis/antigravity-skills

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What it does

Guides developers in designing resilient distributed workflows using Temporal, focusing on workflow-activity separation, saga patterns, and state management for complex system orchestration.

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workflow-orchestration-patterns

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AddedFeb 4, 2026

Skill Details

SKILL.md

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.

Overview

# 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 β†’ 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? β†’ Activity

Is it orchestration/decision logic? β†’ 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 Γ— 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 β†’ 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:

  • βœ… workflow.now() (deterministic time)
  • βœ… workflow.random() (deterministic random)
  • βœ… Pure functions and calculations
  • βœ… 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