Sure bro, I’ll explain it in a simple and clear way, like we're just talking casually.
Let’s go step-by-step.
⭐ How Microservices Communicate With Each Other (Detailed Explanation)
Microservices usually don’t run as one big system.
They are separate small services, running in different servers/containers, and they need to talk to each other.
Communication happens in two ways:
π΅ 1. Synchronous Communication
(Real-time, blocking — “I ask now, you answer now”)
Example:
Service A → waits → Service B responds → then A continues.
Common Protocols/Methods:
a) REST API (HTTP calls)
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Most common
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Simple
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Uses HTTP + JSON
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Example:
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Order Service calls Payment Service’s API:
POST /payment/process
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b) gRPC
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Faster than REST
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Uses binary protocol
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Uses HTTP/2
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Best for internal communication
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Requires
.protofiles
c) GraphQL
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Not very common between services, but possible
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One service queries another for custom data
✔ Advantages
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Simple and easy
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Widely supported
❌ Disadvantages
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Service A is dependent on Service B
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If B is slow/down → A also becomes slow/down
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High latency
π΅ 2. Asynchronous Communication
(Not real-time — “I send a message, you process whenever you want”)
Service A → sends message → doesn’t wait → continues
Service B → processes message later
This uses message brokers.
π₯ Common Messaging Systems
a) Apache Kafka
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Distributed message streaming platform
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High performance
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Used for large-scale event-driven systems
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Services publish events → others subscribe
b) RabbitMQ
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Message queue
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Uses AMQP protocol
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Reliable, supports acknowledgement
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Good for task queues
c) AWS SQS / SNS
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Cloud-based
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Serverless
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Very reliable and scalable
d) Azure Service Bus / Google Pub-Sub
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Cloud message brokers
✔ Where Asynchronous is usually used?
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Sending emails
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Notifications
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Payment confirmation
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Event-driven architectures
Example:
Order Service → sends event to Kafka → Payment Service receives → Inventory Service receives
All services remain loosely coupled.
⭐ Types of Communication Patterns
1. Request–Response (Sync)
A → B → Response → A continues
2. Fire-and-Forget (Async)
A → sends message → doesn't care about response
3. Event-Driven
A → publishes event
Many services → subscribe
4. Publish–Subscribe (Pub/Sub)
One message → multiple listeners
(Kafka, SNS, etc.)
5. Message Queue
Messages are stored in queue → consumers process them
(RabbitMQ, SQS)
⭐ Service Discovery
Since microservices run on multiple servers with dynamic IPs:
Systems used:
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Eureka (Netflix)
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Consul
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Zookeeper
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Kubernetes Service Discovery
They help one service find another automatically.
⭐ API Gateway
All external users talk to one entry point (API Gateway)
It handles:
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Routing
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Authentication
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Load balancing
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Rate limiting
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Logging
Examples:
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Kong
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NGINX
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AWS API Gateway
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Zuul
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Istio Ingress in Kubernetes
⭐ Circuit Breaker Pattern
If Service B is slow/failed:
Service A uses circuit breaker to:
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Stop calling B temporarily
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Return fallback response
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Avoid cascading failures
Libraries:
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Netflix Hystrix
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Resilience4j
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Istio retry policies
⭐ Diagram (Simple)
┌──────────────┐ Sync REST ┌──────────────┐
│ Order Service ├──────────────────────► Payment Serv. │
└───────▲──────┘ └──────▲──────┘
│ Async Event (Kafka) │
└──────────────────────────────────────┘
⭐ Summary (In Style You Prefer π)
Bro, microservices talk to each other mainly in two styles:
πΉ Sync (REST, gRPC)
Like calling your friend on phone and waiting for reply.
πΉ Async (Kafka, RabbitMQ)
Like sending a WhatsApp message — reply comes later.
Microservices also need:
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API Gateway
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Service Discovery
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Circuit Breakers
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Load Balancers
All of these ensure a scalable, fault-tolerant, loosely coupled system.
If you want, I can also explain:
✔ With real project example
✔ With code (Java + Spring Boot)
✔ With diagrams
✔ When to use sync vs async
Just tell me, bro!
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