Temporal Workflow Design
Overview
Help design and implement durable workflows using Temporal.io - an open-source platform for building reliable applications that automatically recover from failures.
When to Use Temporal
- •Long-running processes: Multi-step workflows that span hours, days, or weeks
- •AI/Agent orchestration: Resilient AI pipelines that need state management
- •Order fulfillment: Maintain transaction integrity across service failures
- •Human-in-the-loop: Workflows requiring human approval steps
- •Financial transactions: Durable ledgers tracking transactions reliably
- •CI/CD pipelines: Deployments with built-in retries and rollbacks
Core Concepts
Workflows: Durable functions that define the overall process. They automatically capture state at each step and resume from failures.
Activities: Individual tasks within a workflow (API calls, database operations, file processing). These are the units that can fail and be retried.
Workers: Processes that execute workflows and activities. They poll task queues for work.
Signals: External inputs that can modify workflow behavior mid-execution.
Queries: Read-only operations to inspect workflow state without affecting execution.
Task Queues: Named queues that route work to appropriate workers.
Design Process
1. Identify the workflow boundary:
- •What triggers the workflow?
- •What's the final outcome?
- •How long might it run?
2. Break into activities:
- •What are the discrete steps?
- •Which steps can fail and need retries?
- •What are the retry policies for each?
3. Define state and signals:
- •What state needs to persist between steps?
- •What external events need to modify the workflow?
- •What information should be queryable?
4. Plan failure modes:
- •What happens if an activity fails permanently?
- •Are there compensation/rollback requirements?
- •How should timeouts be handled?
Supported Languages
- •TypeScript/JavaScript
- •Python
- •Go
- •Java
- •C# (.NET)
- •PHP
- •Ruby
Implementation Patterns
Saga Pattern: Long-running transactions with compensation on failure.
State Machine: Workflows that transition between defined states.
Pipeline: Sequential processing with optional parallelization.
Fan-out/Fan-in: Parallel activity execution with aggregated results.
Polling: Periodic checks until a condition is met.
Human-in-the-Loop: Wait for external signals (approvals, reviews).
Best Practices
- •Keep workflows deterministic - no random values, current time, or I/O in workflow code
- •Put all non-deterministic operations in activities
- •Use meaningful workflow and activity names
- •Set appropriate retry policies per activity type
- •Use timeouts at both workflow and activity levels
- •Design for idempotency in activities
- •Use versioning for workflow updates in production