microservices
Microservices distributed architecture pattern. Use for scalable systems.
Best use case
microservices is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Microservices distributed architecture pattern. Use for scalable systems.
Teams using microservices should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/microservices/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How microservices Compares
| Feature / Agent | microservices | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Microservices distributed architecture pattern. Use for scalable systems.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Microservices
Microservices architecture structures an application as a collection of loosely coupled, independently deployable services. Ideally, each service corresponds to a **Bounded Context** (DDD).
## When to Use
- Large teams (50+ devs) where coordination on a monolith slows down deployment.
- Modules have conflicting resource requirements (e.g., one needs huge RAM, another needs GPU).
- Need to scale specific parts of the system independently.
- **2025 Reality check**: Don't start with Microservices. Start with a Modular Monolith.
## Quick Start
```yaml
# docker-compose.yml (Simulated Microservices)
services:
order-service:
build: ./services/order
ports: ["3001:3000"]
environment:
- DB_HOST=order-db
inventory-service:
build: ./services/inventory
ports: ["3002:3000"]
api-gateway:
image: nginx
ports: ["80:80"]
depends_on:
- order-service
- inventory-service
```
## Core Concepts
### Independence
Each service owns its own data. Service A cannot query Service B's database directly; it must ask Service B via API.
### Inter-Service Communication
- **Synchronous**: HTTP/REST or gRPC (Request/Response). Tightly coupled in time.
- **Asynchronous**: Message Queues (RabbitMQ, Kafka, SQS). Decoupled in time.
### Database per Service
Ensures loose coupling. If a service needs data from another, use data replication (Events) or API composition.
## Common Patterns
### API Gateway
A single entry point for all clients. Handles routing, auth, rate limiting, and aggregation.
### Circuit Breaker
Detects failures and prevents the application from trying to perform the action that is doomed to fail (e.g., external service down), protecting the system.
### Saga Pattern
Managing distributed transactions. Since you can't have ACID across services, use Sagas (sequence of local transactions) with compensating actions for rollbacks.
## Best Practices
**Do**:
- Automate **CI/CD** and **Infrastructure as Code** (Terraform/K8s). You can't manage 50 services manually.
- Implement **Distributed Tracing** (OpenTelemetry) immediately.
- Define clear **Service Boundaries** (use DDD).
**Don't**:
- Don't share code libraries for domain logic (leads to "Distributed Monolith"). Share utils only.
- Don't use synchronous calls for everything (cascading failures).
- Don't underestimate the **Operational Complexity** (Logging, Monitoring, Auth).
## Troubleshooting
| Error | Cause | Solution |
| :------------------- | :--------------------------------------------- | :--------------------------------------------------------------------- |
| `Cascading Failure` | One service down takes down others. | Use Circuit Breakers and Timeouts. |
| `Data inconsistency` | Async updates failed. | Implement Sagas and Idempotent consumers. |
| `Latency` | Too many hops (service -> service -> service). | Use Caching, Aggregation at Gateway, or Event-Driven data replication. |
## References
- [Building Microservices (Sam Newman)](https://samnewman.io/books/building_microservices/)
- [Microservices Patterns (Chris Richardson)](https://microservices.io/)Related Skills
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