How does this skill help with distributed transactions?

It provides implementation details for the Saga pattern, which allows you to register compensating actions for every step of a process to ensure safe rollbacks across multiple services.

When should I avoid using workflow orchestration?

You should avoid it for simple CRUD operations, pure data processing pipelines like Airflow, stateless request/response APIs, or real-time streaming needs.

What is the core difference between a workflow and an activity?

Workflows handle orchestration logic and must be deterministic (same input always equals same output), while activities handle external interactions like API calls and databases which can be non-deterministic.

Why is determinism required in Temporal workflows?

Determinism is critical because Temporal uses 'replay' to recover state after a crash. If the workflow logic isn't deterministic, it could take a different path during recovery, causing state corruption.

Temporal Workflow Orchestration

Name: Temporal Workflow Orchestration
Author: as4584

byas4584

API 개발

Architect durable distributed systems using Temporal patterns for stateful workflow management and resilient microservice orchestration.

소개

This skill provides expert-level guidance for designing reliable distributed systems using Temporal.io. It bridges the gap between complex business logic and execution resilience by detailing the critical separation between deterministic workflows and non-deterministic activities. Users will learn to implement advanced patterns such as Sagas for distributed transactions, entity workflows for long-lived state, and robust error-handling strategies including idempotency and heartbeating, ensuring applications remain consistent even across infrastructure failures.

주요 기능

0 GitHub stars
Implementation patterns for the Saga pattern and compensating actions in distributed transactions
Resilience strategies including exponential backoff, retry policies, and idempotency keys
Best practices for workflow determinism, state preservation, and event history management
Scalability patterns for high-volume tasks using fan-out/fan-in and child workflows
Comprehensive guidance on separating deterministic orchestration from non-deterministic activities

사용 사례

Building multi-step business processes like order fulfillment, bookings, and approvals
Automating complex infrastructure deployments and CI/CD pipelines with state recovery
Managing long-running entity lifecycles such as user accounts or shopping carts

소개

주요 기능

0 GitHub stars
Implementation patterns for the Saga pattern and compensating actions in distributed transactions
Resilience strategies including exponential backoff, retry policies, and idempotency keys
Best practices for workflow determinism, state preservation, and event history management
Scalability patterns for high-volume tasks using fan-out/fan-in and child workflows
Comprehensive guidance on separating deterministic orchestration from non-deterministic activities

사용 사례

Building multi-step business processes like order fulfillment, bookings, and approvals
Automating complex infrastructure deployments and CI/CD pipelines with state recovery
Managing long-running entity lifecycles such as user accounts or shopping carts