How do you ensure data consistency in Microservices?

Consistency: all data in the database is consistent at the end of transaction. Isolation: only one transaction can touch the data in the same time, other transactions wait until completion of the working transaction. Durability: data is persisted in the database at the end of the transaction.

How do you achieve data consistency in Microservices?

For transactions, use patterns such as Scheduler Agent Supervisor and Compensating Transaction to keep data consistent across several services. You may need to store an additional piece of data that captures the state of a unit of work that spans multiple services, to avoid partial failure among multiple services.

How are microservices used to manage shared data?

In this approach rather than allowing microservices to access the database directly, a new microservice is developed. This microservice manages all access to the shared data by the two services. By having a common entry point it is easier to reason about changes in various places.

When do you need strong consistency guarantees for microservices?

When you need strong consistency guarantees, one service may represent the source of truth for a given entity, which is exposed through an API. Other services might hold their own copy of the data, or a subset of the data, that is eventually consistent with the master data but not considered the source of truth.

What is the problem of dependencies in microservices?

The problem of dependencies. As we have discussed in previous posts, one of the biggest enemies of distributed architectures are dependencies. In a microservice-based architecture, services are modeled as isolated units that manage a reduced set of problems.

How are services modeled in a microservice architecture?

However, fully functional systems rely on the cooperation and integration of its parts, and microservice architectures are not an exception. “In a microservice architecture, services are modeled as isolated units that manage a reduced set of problems.”

How do you ensure data consistency in microservices?

For transactions, use patterns such as Scheduler Agent Supervisor and Compensating Transaction to keep data consistent across several services. You may need to store an additional piece of data that captures the state of a unit of work that spans multiple services, to avoid partial failure among multiple services.

How do you manage multiple microservices?

Microservices and containers: 6 management tips for the long haul

1. Keep “KISS” top of mind.
2. Put your management plan into place – early.
3. Tap into an orchestration platform.
4. Develop a minimum set of operational capabilities.
5. Implement continuous integration and continuous delivery.

How do I share data between microservices?

Another way to share data is to share a data store. Services can share a relational database, NoSQL store, or another data storage service. One or more services publish the data to the database, and other services consume it when required. Most databases and data stores provide data via request/response mechanisms.

How do you maintain data consistency?

Ensuring data consistency

1. Using referential integrity for data consistency. Referential integrity ensures that data is consistent across tables.
2. Using locks for data consistency. Locks can ensure that data remains consistent even when multiple users try to access the same data at the same time.
3. Checking data consistency.

How do you ensure data consistency in distributed system?

1 Answer

1. First is to take the lock before writing anything to the database or caching system. This ensures read and write lock. This includes master server as well.
2. Secondly, if replication fails then there is the added complex layer of rollovers. This ensures that data is consistent if not then it is not applied.

How do you sync two microservices?

How to keep DB in sync when using microservices architecture?

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.

What makes data consistent?

A database can be said to be data consistent when the content under question does not give us the chance to infer a contradiction directly or indirectly. These conclusions are derived by keeping the database constraints specified in the database schema and any other inference rules in mind.

Why do we need data consistency across microservices?

They enable organizations to achieve agility and be able to improve the time it takes to get working enhancements to production. On the downside, there are quite a number of challenges—each service has its own database and wherever business transactions span multiple services you need a mechanism to ensure data consistency across services.

How can CDC be used in microservices design?

CDC, although well rooted and practiced extensively in Data Warehousing, can well be adopted to Microservices design effectively to ensure that the transactions span services with consistency. The basic principle remains same at the core.

Why are microservice applications built as modular components?

When microservice applications are built as a set of modular components, they are easier to understand, simpler to test and effortless to maintain over the life of the application. They enable organizations to achieve agility and be able to improve the time it takes to get working enhancements to production.

When do we need to take care of consistency?

As long as we have multiple places where the data is stored (which are not in a single database), consistency is not solved automatically and engineers need to take care of consistency while designing the system.