Microservices help build big applications by dividing them into small, independent parts. Each part does one job and communicates with others through APIs.
Companies like Netflix, Amazon, and Uber use microservices to handle millions of users. To build a good microservices system, follow these best practices.
Each microservice should have its own database. This makes it independent and avoids data conflicts.
β No data mixing between services
β Easier to manage and scale
πΉ Example: Amazonβs payment and order systems have separate databases to work smoothly.
All microservices should be updated and maintained regularly. This avoids problems when they communicate with each other.
β Prevents compatibility issues
β Keeps the system stable
πΉ Example: Netflix updates all its services together to avoid errors.
Each microservice should have its own build and deployment process. This allows you to update one service without affecting others.
β Faster updates
β Fewer system failures
πΉ Example: Uber updates its ride-matching service without stopping payments or navigation.
Each microservice should do only one job. This makes it easy to manage, fix, and improve.
β Simple and clear structure
β Easy to test and update
πΉ Example: Spotify has different services for playlists, streaming, and user accounts.
Deploy each microservice inside a container like Docker. Containers keep services separate and easy to manage.
β Easy to move and scale
β Works the same on any server
πΉ Example: Netflix runs thousands of containers to manage streaming services.
Microservices should not store user data on the server. Use a database or cache instead.
β Makes scaling easy
β No data loss when restarting servers
πΉ Example: Facebook stores user sessions in Redis instead of saving them on servers.
Each microservice should match a real-world business function. This makes the system more useful and organized.
β Clear roles for each service
β Easier to scale and improve
πΉ Example: In an online store, there are separate services for orders, payments, and deliveries.
Just like backend services, the frontend should also be divided into smaller parts. Each part should match its microservice.
β Faster updates
β Better performance
πΉ Example: Amazonβs product page, cart, and recommendations all have different frontend services.
Managing microservices manually is difficult. Use tools like Kubernetes to automate tasks.
β Auto-scaling when needed
β Handles failures automatically
πΉ Example: Google uses Kubernetes to manage millions of search requests smoothly.
β Scalable: Grow each service separately
β Flexible: Use different technologies for different services
β Fast Development: Teams work on different services at the same time
β Reliable: If one service fails, others keep working
β Complex: Managing many services is harder than one big system
β Data Issues: Keeping data consistent across services is tricky
β Higher Costs: More services mean more resources are needed
Tool | Purpose | Used By |
---|---|---|
Docker | Run services in containers | Netflix, PayPal |
Kubernetes | Manage microservices | Google, Airbnb |
Redis | Store session data | Facebook, Twitter |
API Gateway | Manage service communication | Amazon, Uber |
Grafana | Monitor system health | LinkedIn, eBay |
β Mixing Responsibilities: Each service should do only one job
β Sharing Databases: Each service should have its own database
β Skipping API Gateway: Use an API gateway to control communication
β Ignoring Security: Protect services with authentication and authorization
β Not Using Automation: Automate deployments with CI/CD tools
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