Microservice architecture

Microservice Architecture

 

Microservice architecture is a way of building software systems that consist of small, independent services. Each service is focused on a specific task and communicates with other services through well-defined interfaces, typically using a lightweight messaging protocol such as HTTP.

Here are two famous architectures that we leverage to implement microservices:

Command Query Responsibility Segregation (CQRS):

One common design pattern for implementing microservices is the Command Query Responsibility Segregation (CQRS) pattern. In this pattern, each service is responsible for either executing a command (performing an action) or handling a query (returning data). This separation of concerns can help to simplify the design of each service and make it easier to scale and maintain the system as a whole.


Command Query Responsibility Segregation (CQRS) is a design pattern that can be used when building software systems using a microservice architecture. In this pattern, each service is responsible for either executing a command (performing an action) or handling a query (returning data).

The goal of CQRS is to simplify the design of each service by separating the responsibility of handling commands (which cause a change in state) and queries (which request information), which can often be quite complex when combined. Separating commands and queries makes it easier to scale and maintain the system as a whole, as each service can be optimized for its specific purpose.

In a CQRS system, commands are typically sent to a service over a message bus, and queries are handled by a separate read model that is optimized for fast read access. This separation of concerns can help to improve the performance and scalability of the system.

Overall, CQRS can be a useful design pattern for building microservice systems that need to be scalable, maintainable, and easy to develop and deploy. By breaking a system down into small, independent services, it is easier to make changes and improvements without affecting the entire system.

Pros:

  1. Simplifies the design of each service by separating the concerns of executing commands and handling queries.
  2. It makes it easier to scale and maintain the system as a whole, as each service can be optimized for its specific purpose.
  3. It can improve the performance and scalability of the system by allowing the read model to be optimized for fast read access.

Cons:

  1. It can be more complex to implement, as it requires a message bus and a separate read model to handle queries.
  2. It may require more effort to test and debug the system, as the separation of commands and queries can make it more difficult to see the overall effect of a change.

Event source:

Event sourcing is a design pattern that can be used when building software systems using a microservice architecture. In this pattern, all changes to a service's data are recorded as a sequence of events. These events are persisted in an event store, which is a database that is specifically designed to store events.


The main advantage of using event sourcing is that it allows the current state of a service to be reconstructed by replaying its past events. This can be useful in a number of situations, such as when debugging the system, recovering from errors, or auditing the service's activity.

To implement event sourcing, a service typically exposes a set of commands that can be used to trigger events. When a command is received, the service performs the necessary actions and generates one or more events that describe the changes that were made. These events are then persisted in the event store.

To read the current state of the service, a separate projection component can be used to build a read model by replaying the events from the event store and applying them to a data model. This read model can then be queried by client applications to retrieve the current state of the service.

Pros:

  1. Allows the current state of service to be reconstructed by replaying its past events. This can be useful in a number of situations, such as when debugging the system, recovering from errors, or auditing the service's activity.
  2. It makes it easy to add new features or make changes to service by simply adding new events or changing how they are processed.
  3. It can help improve the system's performance and scalability by allowing the read model to be optimized for fast read access.

Cons:

  1. It can be more complex to implement, as it requires an event store and a projection component to build the read model.
  2. It may require more storage space, as the event store must be able to store all of the events for a service.






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