Event-driven architecture for microservices

Event-Driven Architecture (EDA) is a way of designing applications and services to respond to real-time information based on the sending and receiving of information about individual event notifications.

What is event-driven architecture?

EDA is based on asynchronous non-blocking communication between event producers and event consumers that are able to release the resource consumption while waiting for the response to return. Events enhance the decoupling of now well-defined bounded context (DDD) services technically and at runtime becoming the first architectural consideration for cloud and container-native distributed systems. Because more communication patterns are available, multiple consumers can receive events, simultaneously lowering the latency and increasing the throughput.

You can use event-driven architecture with Quarkus, Kafka, and OpenShift. Learn about it from the experts.

Create your first Apache Kafka cluster on OpenShift

Red Hat AMQ Streams is a massively scalable, distributed, and high-performance data streaming platform based on the Apache Kafka project. AMQ Streams provides an event streaming backbone that allows microservices and other application components to exchange data with extremely high throughput and low latency.

Run Kafka on OpenShift with AMQ Streams Learn about Apache Kafka Integration Connectors

Why event-driven architecture?

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Reduced coupling

Traditional RPC-style service architecture results in tightly bound services. Changes to the application flow typically require service code changes. EDA allows new functionality to be added by adding services that consume existing event streams.

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Mirrors real world

The real world is event-driven. Systems generate and respond to events in everyday life (for example, the human central nervous system).

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Encapsulation

Microservices concepts have grown in popularity due to the ability for service teams to develop services in isolation. EDA means that service designers need not be aware of how events are consumed.

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Near real-time latency

Customers increasingly expect a near real-time experience. Polling on APIs is a delicate trade-off between responsiveness and load. EDA allow apps to react in near real-time without compromise.

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Fine-grained scaling

Services can be independently scaled up and down to meet the event volume.

Cloud-native nature

Cloud-native nature

EDA are designed to work perfectly in the distributed world, and cloud-native services are running separately on nodes/servers in the cloud.

What is an event?

In its basic form, when we are talking about events in an Event-driven Architecture (EDA), we are referring to unusual or important actions or incidents that occur in the system generated by the systems software or hardware components.

Here are some common communication types that should also be taken into consideration when designing a proper cloud native EDA.

Learn more about events

Event

Event

Immutable state and value of a particular entity, which occurred during operation among services.

Command

Command

Asynchronized form of Remote Procedure Call, where it contains instructions of telling the recipient what to do, which may cause a change of state in the system.

Query

Query

Similar to commands, queries expect a response returning the results, but does not cause any change in state

3 types of events

As events are generated in one of the Event-driven Architecture components and the notifications placed in the channel, the communication pattern used to share then defines also the nature of the messages.

Learn more about event types

Volatile

The event needs to be disseminated to all consumers online at time of publication. Not persisted.

Durable

Events stored durably until read by all registered consumers. Traditional pub/sub.

Replayable

Events stored durably for specific period of time or storage capacity. Consumers can move back and forth of the stream.

Choose the right solution to implement your EDA patterns

AMQ Broker

About

  • Traditional messaging broker with queuing & Pub/Sub
  • Rich feature set inc. JMS 2.0
  • Best-in-class performance
  • Based on Apache ActiveMQ Artemis

Possible patterns

  • Durable events (recommended)
  • Volatile events
  • Command
  • Query

Unsuitable patterns

  • Replayable events

AMQ Interconnect

About

  • Message router
  • 1:1 (anycast) and 1:many (multicast)
  • Secure messaging backbone for hybrid cloud
  • Based on Apache Qpid Dispatch Router

Possible patterns

  • Command
  • Query
  • Volatile events

Unsuitable patterns

  • Durable events
  • Replayable events

AMQ Streams

About

  • Enterprise distribution of Apache Kafka
  • Simplified deployment on OpenShift
  • Based on Kafka and Strimzi

Possible patterns

  • Replayable events (recommended)
  • Durable events (recommended)
  • Command
  • Query

Unsuitable patterns

  • Volatile events
  • Transacted/filtered events

 

AMQ Online

About

  • Scalable, "self-service" on OpenShift
  • Available self-managed and Red Hat-managed
  • Based on EnMasse, Artemis & Qpid Dispatch Router

Possible patterns

  • Command
  • Query
  • Volatile events
  • Durable events

Unsuitable patterns

  • Replayable events
Learn more about Red Hat AMQ

Running Kafka on Kubernetes

Share data between microservices and other applications with high throughput and low latency. The AMQ streams component makes Apache Kafka "OpenShift native" through the use of powerful operators that simplify the deployment, configuration, management, and use of Apache Kafka on OpenShift.

Explore Kafka on Kubernetes
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