---
title: Microservices Patterns
category: product
entity_type: skill
price: $15
canonical: https://forgehouse.ai/skills/microservices-patterns/
lang: en
hreflang_alt: https://forgehouse.ai/tr/skiller/microservices-patterns/
last_updated: 2026-06-20
---

# Microservices Patterns

> Design microservices architectures with service boundaries, event-driven communication, and…

A design guide for microservices architectures covering service boundaries, inter-service communication, distributed data, and resilience. It shows how to decompose monoliths, choose synchronous versus event-driven communication, and add circuit breakers, sagas, and bulkheads that keep distributed systems stable under failure.

## Use cases
- Decomposing a monolith into well-bounded services
- Designing service boundaries and API contracts
- Choosing between REST, gRPC, and event-driven communication
- Managing distributed transactions with saga compensation
- Adding resilience with circuit breakers and bulkheads
- Building an API gateway that aggregates services and handles partial failure

## Benefits
- Avoid the distributed-monolith trap with clear, business-aligned boundaries
- Keep failures contained so one slow service doesn't cascade across the system
- Maintain data consistency across services with proper saga compensation
- Migrate from monolith incrementally with no risky big-bang rewrite

## What’s included
- Service decomposition strategies by business capability and subdomain
- Synchronous REST with retries and asynchronous event-driven Kafka patterns
- A full saga orchestration implementation with compensating actions
- A production circuit breaker with closed, open, and half-open states
- An API gateway template with parallel aggregation and partial-failure handling
- Bounded context, bulkhead, and strangler-fig migration patterns

## Who it’s for
Backend architects and engineers building distributed systems or decomposing monoliths into microservices.

## How it runs
Most microservice failures are boundary failures. So this skill starts at the boundaries: one domain per service, one database per owner, and resilience wired in as a default before traffic arrives.
1. Draws bounded contexts before any code: each service owns one domain concept and its own database, no shared tables, shared models capped at 2-3 DTOs, and a context map marking who is upstream and who is downstream.
2. Decides the communication mode per interaction: synchronous REST/gRPC gets a hardened client with timeouts, connection limits and exponential-backoff retries; anything that can be async becomes an event on Kafka, partitioned by aggregate id so events for one order stay ordered.
3. Makes every event consumer idempotent and gives it a dead letter queue: the same event arriving twice produces the same result, and three failed retries route the message to DLQ for manual inspection instead of silent loss.
4. Wires distributed transactions as sagas: each step (create order, reserve inventory, process payment, confirm) carries a compensating action, and on failure the completed steps roll back in reverse order. Four or more steps means orchestration, two or three can stay choreography.
5. Installs resilience as a default, not an option: a circuit breaker on every service-to-service call (5 failures open the circuit for 30 seconds, then half-open probing) plus bulkhead isolation so one slow dependency cannot drain every pool.
6. Aggregates at the API gateway with partial-failure handling: parallel fan-out to services, and when one of them is down the response still ships what succeeded instead of failing the whole page.

## FAQ
### We're still on a monolith. Is this useful before we've split anything?
That is the starting point it assumes: decomposition strategies by business capability and subdomain, plus the strangler-fig pattern for migrating incrementally instead of a big-bang rewrite. You can do the boundary work while the monolith is still running.

### How does it keep data consistent without distributed transactions?
Through a full saga orchestration implementation with compensating actions: each step has a defined rollback, so a failure midway unwinds cleanly instead of leaving half-written state. Circuit breakers and bulkheads keep the failure itself from cascading.

### Does it choose my infrastructure, like Kubernetes or a message broker?
No. It is an architecture patterns guide covering boundaries, communication choices, and resilience, with Kafka shown as the event-driven example. Cluster setup, broker operations, and deployment tooling are outside its scope.

## Price
$15, one-time, no subscription. VAT included.

Related guide: [AI code review and developer workflow](https://forgehouse.ai/guides/ai-code-review/)