Top 12 Microservices Communication Patterns Explained

A complete guide to 12 microservices communication patterns that help developers design scalable, secure, and efficient microservices architectures.

Table of Contents

• Introduction
• REST API
  • Benefits & Drawbacks
• RPC-based communication
  • Benefits & Drawbacks
• Asynchronous messaging
  • Benefits & Drawbacks
• Publish-Subscribe
  • Benefits & Drawbacks
• Events Sourcing
  • Benefits & Drawbacks
• CQRS
  • Benefits & Drawbacks
• Shared Database
  • Problem
• Saga Pattern
  • Benefits & Drawbacks
• Outbox Pattern
  • Benefits & Drawbacks
• API Gateway Pattern
  • Benefits
• Service Mesh Communication
  • Benefits
• BFF
  • Benefits
• Conclusion

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Introduction

The architecture of microservices has revolutionized the development of modern applications. Applications are separated into smaller, autonomous services that interact with one another rather than existing as a single, massive monolithic system.

The problem lies in how these services can communicate effectively, consistently, and scalably.

Microservices communication patterns can help with that.

The top 12 microservices communication patterns that are frequently employed in modern distributed systems will be examined in this blog.

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REST API (synchronous)

Synchronous communication via REST APIs is the most popular communication pattern in microservices. Using HTTP, one service makes a direct call to another and watches for a response.

Benefits:

• Easy to understand and apply
• Broadly endorsed
• Simple debugging

Drawbacks:

• Raises latency
• Close relationship between services
• For straightforward request-response communication, this pattern works best.

RPC-based communication (gRPC):

Protocol buffers are used by the high-performance Remote Procedure Call (RPC) framework  to facilitate effective binary communication. Internal service-to-service communication is one of its frequent uses

Benefits:

• Lightweight and incredibly quick
• Support streaming
• Strong typing contracts

Drawbacks

• Not as readable by humans as REST
• A little complicated to set up
• gRPC is perfect for high-performance, low-latency systems.

Asynchronous messaging (queue-based):

Instead of using direct calls, services in this pattern exchange messages via message queues like Kafka or RabbitMQ.
A message is published to a queue by the sender, and it is processed independently by the recipient

Benefits:

• A loose coupling
• Enhanced scalability
• Tolerance for faults

Drawbacks:

• Increased system complexity is a drawback.
• More challenging debugging
• This pattern is perfect for systems that need to be scalable and reliable.

Publish-Subscribe (Pub/Sub):

In Pub/Sub, an event is published by a service, and it is received and processed by several subscribers.
In event-driven architectures, this pattern is common.

Benefits:

Extremely scalable
Events can elicit reactions from multiple consumers.
A loose coupling

Drawbacks:

Tracking events can be difficult.
Distributed event debugging is challenging.
This pattern is extensively utilized in reactive and real-time systems.

Events Sourcing

In event sourcing, all state changes are stored as a series of events rather than just the most recent data state.
Events are replayed in order to reconstruct the current state.

Benefits:

Full audit trail
Debugging historical data is simple.
Compatible with CQRS

Drawbacks:

Complicated execution
demands meticulous design. Event sourcing is ideal for complex business domains such as order systems or finance.

CQRS (Command Query Responsibility Segregation)

Write operations (commands) and read operations (queries) are separated by CQRS. This enables distinct optimization for read and write models, which enhances scalability and performance.

Benefits:
Improved performance
architecture that is cleaner

Drawbacks:
Enhanced intricacy
Problems with data synchronisation
This pattern is mostly used with Event sourcing

Shared Database (Anti-Pattern)

This method uses a single database that is shared by several microservices. Despite its initial simplicity, as it looks, it results in tight coupling between services.

Problems:

• High dependency between services
• Independent deployment is challenging
• Scaling problems

In a true microservices architecture, this pattern is typically discouraged because of its complexity and tight coupling

Saga Pattern (Distributed Transactions):

Traditional distributed transactions, such as 2PC, are challenging in microservices. The Saga pattern uses a series of local transactions to handle transactions across services.

In this pattern, two categories exist:

1) Choreography (Event-based)
2) Orchestration (Central coordinator)

Benefits:
preserves the consistency of data
Steer clear of distributed transaction locks

Drawbacks:
complex error-handling
Scaling problem

It is mostly utilised in e-commerce platforms (e.g., order, payment, shipping)

Outbox Pattern

Reliable message publishing is ensured by the Outbox pattern. A service adds an event and database modifications to the same transaction. The event is later safely published.

Benefits:
Avoids inconsistent data
dependable delivery of events

Drawbacks:
needs more processing
High processing time

This pattern is very beneficial for architectures that rely on events

API Gateway Pattern

An API gateway serves as a single point of entry for requests from clients.

It can manage the following and route requests to the relevant microservices:

Verification
Rate limiting
Logging

Transformation:

Benefits:
Centralised management
Enhanced safety
Streamlined client correspondence

It is vital for large systems that use microservices.

Service Mesh Communication

A service mesh uses sidecar proxies like Istio or Linkerd to manage communication between services.

It manages:

Routing of traffic
Observability
Safety
Retries

Benefits:

No modifications to the code are necessary.
Advanced surveillance           
Enhanced dependability and reliability

It is perfect for complex cloud-native settings

BFF (Backend For Frontend)

For various client types (web, mobile, etc.), Backend for Frontend generates distinct backend services.
This prevents data from being fetched too much or too little.

Benefits:

Improved client optimisation
Better results
independent frontend evolution
It is frequently found in applications that support several client platforms.

Concluding Note:

In microservices, selecting an appropriate communication pattern depends on:

1) Complexity of the system
2) Needs for scalability
3) Performance requirements
4) requirements for consistency

Multiple patterns are frequently combined in real-world systems. For instance:

1) REST for basic calls
2) Asynchronous task messaging
3) Distributed Transaction Saga
4) Centralised access via an API gateway

Architects and developers can create scalable, dependable, and maintainable microservices systems by having a solid understanding of these 12 communication patterns.

Reference links:
For more coding series:
Power of Microservices Observability
No-Code & Low-Code
Learning to Code: How to Think Like a Programmer

Written By Reeshaiel Shah