Microservice Communication - gRPC vs Kafka vs REST API: Which One Should You Choose?
A practical breakdown of REST, gRPC, and Kafka for microservices when to use each, with real-world examples from companies like Netflix, Instagram, and LinkedIn.
Introduction:
When people talk about microservices most of the conversation is around breaking the monolith and making small independent services. Sounds great in theory. But once that actually have multiple services running there’s a big question. how do these services talk to each other? That’s where communication patterns and protocols come into play.
This isn’t just a tech choice. Picking the wrong one can make your system slow, unreliable, or hard to scale. Let’s break it down with three popular ways to connect microservices: REST APIs, gRPC, and Kafka.
REST API — The Default Choice
When most developers think service-to-service communication they think HTTP REST. It’s familiar easy to implement and works with pretty much any programming language. One service exposes endpoints like or and another service calls them using HTTP.
It’s human readable because the data is usually JSON. You can open a browser or Postman and see exactly what’s coming back. Debugging is straightforward.
But it’s not perfect. HTTP 1.1 isn’t the fastest. JSON parsing is slower than binary formats. And REST is request response if Service A needs something from Service B it sends a request and waits for the answer. That means if Service B is slow Service A is also slow.
Real-world example: Instagram uses REST for many public facing APIs especially for its Graph API that developers can query for user posts comments and likes. It’s easy for third party apps and external partners to work with JSON over HTTP without special tooling.
gRPC — Faster and Strongly Typed
gRPC is like REST’s performance focused cousin. It’s built on top of HTTP 2, uses binary serialization with Protocol Buffers and supports streaming in addition to simple request response.
Instead of sending human readable JSON you define your API in a file with exact data types. gRPC then generates code for client and server in multiple languages. That means fewer mistakes due to mismatched request formats.
Speed wise gRPC wins in most cases. Binary data is smaller than JSON and HTTP 2 allows multiplexing multiple requests in a single connection so you avoid TCP connection overhead.
Real-world example: Netflix uses gRPC extensively for service-to-service communication inside its control plane. With hundreds of microservices needing high throughput and low latency gRPC’s strong typing and streaming support help them keep performance high at scale.
Kafka — Event-Driven Communication
REST and gRPC are direct communication methods Service A calls Service B directly. Kafka takes a different approach don’t call services directly send events to a shared log.
Think of Kafka as a distributed queue where services publish messages and others subscribe to them. If you have an Order Created event your payment notification and analytics services can all consume it independently. If a service is down Kafka stores the event until it’s back up.
Real-world example: LinkedIn uses Kafka to handle activity streams log data and asynchronous updates across its platform. Instagram also uses a Kafka like event pipeline to process billions of real time notifications without coupling services directly.
When to Choose What
Use REST if you want simplicity human readable data and easy integration.
Use gRPC if you need low latency high performance internal communication.
Use Kafka if you want to decouple services and handle high volume real time events.
Mixing Them in the Same System
Here’s the truth big companies rarely stick to one method. They mix them.
gRPC for internal microservice-to-microservice calls where speed matters.
REST for public APIs that external developers consume.
Kafka for async events and decoupling.
The key is understanding that these aren’t competing standards they solve different problems. The better you match the tool to the problem the less pain you’ll have scaling later.
The Trade-Off Mindset
Latency tolerance Can the request wait? If not you probably need gRPC or REST.
Coupling Do you want services to know each other’s addresses and APIs? If not go Kafka.
Human friendliness Will people debug this with cURL? REST wins here.
Throughput Millions of events per second? go for Kafka’s.
Operational cost Running Kafka isn’t like running a single REST server. You need infra and expertise.
conclusion:
Microservices are hard enough without overengineering communication. Don’t pick gRPC just because it’s modern or Kafka because it’s cool. Pick it because it actually solves the problem. And don’t be afraid to use more than one in the same architecture.