How can you achieve data persistence in a microservices architecture?

How can you achieve data persistence in a microservices architecture?

The guide provides the following six patterns to enable data persistence among your microservices:

1. Database-per-service pattern.
2. API composition pattern.
3. CQRS pattern.
4. Event sourcing pattern.
5. Saga pattern.
6. Shared-database-per-service pattern.

How do you handle failure in microservices?

In this article

1. Use asynchronous communication (for example, message-based communication) across internal microservices.
2. Use retries with exponential backoff.
3. Work around network timeouts.
4. Use the Circuit Breaker pattern.
5. Provide fallbacks.
6. Limit the number of queued requests.

How do you sync data between microservices?

Here are some suggestions:

1. use a single database per microservice (not per instance) no matter how many instances are using it.
2. Use a shared cache layer on top of the DB (maybe redis cache)
3. Use a database cluster to deal with high load/availability of databases.

How do you secure a microservice?

Here are eight steps your teams can take to protect the integrity of your microservices architecture.

1. Make your microservices architecture secure by design.
2. Scan for dependencies.
3. Use HTTPS everywhere.
4. Use access and identity tokens.
5. Encrypt and protect secrets.
6. Slow down attackers.
7. Know your cloud and cluster security.

Is there eventual data consistency in microservices architecture?

By now, you might have already figured out that owing to the strong advocacy of decentralized data approach of the microservices architecture, it induces eventual data consistency in the systems. However, it would not be prudent to think that the monolithic software architecture deals with these issues seamlessly. They have their own perils.

What are the data considerations for microservices?

Because every microservice manages its own data, data integrity and data consistency are critical challenges. A basic principle of microservices is that each service manages its own data. Two services should not share a data store. Instead, each service is responsible for its own private data store, which other services cannot access directly.

Why are microservices architectures important to modern applications?

Microservices were born because monolithic architecture proved to be outdated to meet the demand of modern applications. While microservices solve a lot of issues, the architecture brings a new set of problems with it too. One of them is maintaining data consistency across microservices.

When to use shared database in microservices architecture?

Shared database is the easiest option to pick when you can’t deal anymore with complex data patterns like database-per-service. Shared database, as the name sounds, is shared commonly by the microservices for their respective domains of service.