Event Sourcing Design Architecture

Event Sourcing

Event sourcing is an architectural pattern used in software engineering that stores all changes to an application's state as a sequence of events. This approach to designing software systems provides a number of advantages for developers, including improved scalability, simplified debugging, and enhanced data integrity. 

Event sourcing architecture is based on the idea of recording all user interactions, or events, and storing them in a log or journal. This log serves as the single source of truth for the system and allows developers to reconstruct the state of the application at any point in time. As new events are added to the log, they are used to update the state of the system in a consistent, deterministic manner. The primary benefit of event sourcing is that it makes the application easier to scale. Since all events are recorded, the system can be easily broken up into smaller components that can be scaled independently. This makes it much simpler to increase the capacity of the system, as developers don't have to worry about the state of the system at any given time. Another advantage of event sourcing is that it simplifies debugging. Since all events are logged, it's easy to trace the source of any errors that occur. This makes it easier to find and fix issues quickly, which is particularly useful for applications with high availability requirements. Finally, event sourcing provides improved data integrity. All events are stored in an immutable log, which means that changes to the system can only be made by processing valid events. This makes it impossible for malicious actors to tamper with the system, as any attempts to manipulate the data will be easily detected. 

Event sourcing is a powerful architecture that can provide significant benefits for software developers. It simplifies scalability, simplifies debugging, and provides enhanced data integrity, making it an attractive option for any application that requires high performance and reliability. In conclusion, event sourcing is an architectural pattern that allows developers to store changes to an application's state as a sequence of events. This approach provides many benefits, including improved scalability, simplified debugging, and enhanced data integrity. Event sourcing is a powerful architecture that can provide significant benefits for software developers, and is worth considering for any application that requires high performance and reliability.

The pros of event sourcing include increased scalability and resilience, faster restoration after a failure, and powerful real-time analytics capabilities. The cons of event sourcing include the need for extra development effort to implement the pattern, difficulty in maintaining the event log, and the potential for events to be lost or corrupted.

Command Query Responsibility Segregation (CQRS) 

Event sourcing can be combined with a Command Query Responsibility Segregation (CQRS) pattern to create a powerful and scalable architecture. In this architecture, the events stored in the event log are used to update the read model, which is then used to answer queries. This allows the application to scale horizontally, as the query layer can be scaled independently from the command layer. Event sourcing and CQRS can be used together to provide a robust and resilient architecture with powerful event-driven capabilities.

Event sourcing can also be used to improve the performance of an application. By replaying events from the event log, an application can be quickly brought up to date with the current state of the system. This can be used to rapidly restore a system after a failure, or to quickly scale up a system when the workload increases. Event sourcing can also be used to provide powerful real-time analytics, as the event log can be used to track and analyze changes to the system.

The CQRS pattern has a number of benefits when used in combination with event sourcing. It allows applications to scale horizontally, as the query layer can be scaled independently from the command layer. It also allows for the rapid restoration of a system after a failure, as the event log can be used to quickly bring the system up to date with the current state. Finally, it provides powerful real-time analytics capabilities, as the event log can be used to track and analyze changes to the system.

A common use case for CQRS and event sourcing is in e-commerce applications. By using CQRS, the query layer can be scaled independently from the command layer, allowing the application to handle large amounts of traffic. The events stored in the event log can be used to quickly restore the system after a failure, or to rapidly scale up the system when the workload increases. Finally, the event log can be used to provide powerful real-time analytics, such as tracking customer behavior or analyzing product performance.

The pros of CQRS include increased scalability, faster restoration after a failure, and powerful real-time analytics capabilities. The cons of CQRS include the need for extra development effort to implement the pattern, difficulty in maintaining the read and write models, and potential for data inconsistency between the two models.

Event Sourcing Technologies

• Apache Kafka: https://kafka.apache.org/

• Apache Pulsar: https://pulsar.apache.org/

• Apache Flink: https://flink.apache.org/

• Apache Samza: https://samza.apache.org/

• Apache Storm: https://storm.apache.org/

• Amazon Kinesis: https://aws.amazon.com/kinesis/

• Microsoft Azure Event Hubs: https://azure.microsoft.com/en-us/services/event-hubs/

• Google Cloud Pub/Sub: https://cloud.google.com/pubsub

• Red Hat AMQ Streams: https://developers.redhat.com/products/amq-streams/overview/

• RabbitMQ Streams: https://www.rabbitmq.com/streams.html

• NATS Streaming: https://docs.nats.io/nats-concepts/jetstream

• Akka Streams: https://doc.akka.io/docs/akka/current/stream/index.html

• Event Store: https://www.eventstore.com/

References

[1] Event Sourcing. (n.d.). Retrieved March 25, 2021, from https://martinfowler.com/eaaDev/EventSourcing.html

[2] What is Command Query Responsibility Segregation (CQRS)?. (2020, December 15). Retrieved March 25, 2021, from https://www.red-gate.com/simple-talk/dotnet/net-development/what-is-command-query-responsibility-segregation-cqrs/

[3] Event Sourcing vs CQRS. (n.d.). Retrieved March 25, 2021, from https://microservices.io/patterns/data/cqrs.html

[4] CQRS Pros & Cons. (n.d.). Retrieved March 25, 2021, from https://www.cqrs.nu/faq/cqrs-pros-cons