Why is determinism critical for Temporal workflows?

Determinism ensures that when a workflow is replayed after a failure or migration, it produces the exact same sequence of commands, allowing the system to reconstruct its state accurately without re-executing side effects.

What is the difference between a Workflow and an Activity?

Workflows handle orchestration logic and must be deterministic to ensure replayability, while Activities perform external interactions like API calls or database writes and can be non-deterministic.

When should I use the Saga pattern in distributed systems?

Use the Saga pattern for distributed transactions that require 'all-or-nothing' semantics across multiple services, allowing you to execute compensating actions to roll back state if a later step fails.

How does this skill handle activity failures and retries?

It provides patterns for configuring exponential backoff, maximum retry attempts, and implementing idempotency keys to ensure that activities can be safely retried until they succeed or fail permanently.

Temporal Workflow Orchestration Patterns

Name: Temporal Workflow Orchestration Patterns
Author: carloscroc

bycarloscroc

API開発

Designs durable, distributed workflows using Temporal to manage complex long-running processes and microservice orchestration.

概要

Master the architecture of distributed systems with specialized guidance on Temporal workflow orchestration. This skill provides implementation patterns for complex business logic, ensuring reliability through the separation of workflows and activities, the application of Saga patterns for distributed transactions, and the enforcement of determinism constraints. It is an essential resource for developers building resilient backend services that require automatic state persistence, sophisticated error recovery, and human-in-the-loop capabilities.

主な機能

Implementation of Saga patterns with automated compensation logic for distributed transactions
Best practices for activity idempotency, heartbeat monitoring, and custom retry policies
Guidance on automatic state management and seamless recovery from infrastructure failures
0 GitHub stars
Design patterns for fan-out/fan-in parallel execution and scalable child workflows
Framework for separating deterministic orchestration logic from non-deterministic external activities

ユースケース

Managing long-running entity lifecycles such as subscription billing or inventory tracking
Building complex e-commerce order fulfillment systems with multi-step rollback capabilities
Orchestrating multi-step infrastructure automation and CI/CD deployment pipelines

概要

主な機能

Implementation of Saga patterns with automated compensation logic for distributed transactions
Best practices for activity idempotency, heartbeat monitoring, and custom retry policies
Guidance on automatic state management and seamless recovery from infrastructure failures
0 GitHub stars
Design patterns for fan-out/fan-in parallel execution and scalable child workflows
Framework for separating deterministic orchestration logic from non-deterministic external activities

ユースケース

Managing long-running entity lifecycles such as subscription billing or inventory tracking
Building complex e-commerce order fulfillment systems with multi-step rollback capabilities
Orchestrating multi-step infrastructure automation and CI/CD deployment pipelines