Tutorials Microservices with .NET
Rate Limiting in Services — Complete Guide
Rate Limiting in Services — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of Microservices with .NET on Toolliyo Academy.
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Microservices with .NET · Lesson 73 of 120
Docker Compose
Beginner ✓ → Intermediate ✓ → Advanced → Professional
Advanced · 3 — Production skills · ~10 min · Module 8: DevOps and Cloud-Native
What is this?
Docker Compose is a key part of ShopNest Cloud-Native — your .NET microservices learning project. In plain terms: it helps Identity Service work correctly in a distributed system where each app deploys and scales on its own.
Why should you care?
You care about this when services leave your laptop and run on servers, Kubernetes, or Azure where restarts and scaling happen automatically.
See it live — copy this example
Create a Web API project (dotnet new webapi), paste the code, then run dotnet run.
services:
order-api:
build: ./src/Order.Api
depends_on: [rabbitmq, order-db]
payment-api:
build: ./src/Payment.Api
rabbitmq:
image: rabbitmq:3-management
Run Example »
This lesson uses terminal or setup steps. Run commands on your computer — the live editor appears on coding lessons.
What happened?
- The example shows Docker Compose wired into Identity Service.
- Read each line, run it locally, then change one setting and observe what breaks or improves.
- That is how teams learn in production too — small experiments, not big bang rewrites.
Try it yourself
- Ensure Docker Desktop is running.
- Open or create the ShopNest project area for Identity Service.
- Apply the Docker Compose pattern from the lesson example.
- Change a string or number in the example and run again — predict the output first.
- Break the code on purpose (remove a semicolon), read the compiler error, then fix it.
Remember
Docker Compose connects to Identity Service in ShopNest Cloud-Native. Practice by editing the example yourself — do not only read. Move on when you can explain this topic in your own words without looking.
Real-world: Swiggy order → restaurant → rider flow
When a customer confirms food order, events notify restaurant prep and rider dispatch. No single 30-second HTTP chain.
Outcome: Restaurant promos deploy without taking down payment processing.