Event-Driven Architecture for the Cloud
Creating modern, efficient, and delightful digital experiences with an event-driven architecture.
Event-driven architecture (EDA) is a software architecture paradigm promoting the production, detection, consumption of, and reaction to events. But EDA is evolving in the era of polyglot development and the hybrid cloud.
CDC can play a critical role in application modernization efforts ensuring the tight messaging and passing of events that exists in monolithic applications are carried over to today’s loosely coupled cloud-native environments.
EDA is a software development method for building applications that asynchronously communicate or integrate with other applications and systems via events.
The financial services industry is under great pressure to modernize the services they offer. They face increased competition from nimbler FinTechs, the growing risk from cyber threats and fraud, evolving regulatory requirements, and ever-rising customer demands for highly responsive innovative digital services.
We are living in a cloud-native world. For many organizations, scale-out, distributed, microservices-based environments – which can deliver greater scalability, reliability, and efficiency – have become the default approach to software design and deployment.
With open banking, developers can integrate financial data from multiple institutions within the same application or share financial data between applications more easily.
To be competitive, banks and insurance companies must invest in architectures and tools that deliver more flexible, scalable, and resilient software services.
An event-driven architecture provides a foundation upon which financial services organizations can move from batch to real-time applications and modernize their offerings.
A cloud-native approach to application development based on an EDA, containers, and microservices allows businesses to offer innovative real-time products and services.
Developers and businesses need a scalable platform to host event-driven Kafka applications.
CDC minimizes the resources required for processes because it only deals with data changes. Such capabilities allow streaming projects to scale more easily.
Organizations that opt to build their own EDA will face numerous challenges related to integration, deployment, performance, scalability, security, and more.
As businesses strive to be more responsive and react in real-time, they must incorporate events data and develop and deploy applications based on microservices and cloud-native architectures.
The decoupled and asynchronous nature of an event-driven architecture enables the development of flexible, extensible, modern cloud-based serverless applications.
Event-streaming technologies are essential for building and maintaining real-time links with internal partners, business partners, suppliers, and customers.
Event-driven architectures and event meshes enable today’s modern distributed, cloud-native applications that are responsive to state changes.
An event-driven architecture provides a number of advantages over REST APIs for modern applications deployed across hybrid cloud environments.
It has never been more important for organizations to be able to react to change in the market, and IT systems must deliver this ability to launch new services or update existing ones quickly. Rethinking IT infrastructure is crucial, as it is the foundation of digital services.
Event Driven Architecture (EDA) is a way of designing applications (microservices) to respond to real-time business events at edge.
Using a microservices-based architecture offers the flexibility to add new data sources and use new analysis engines without rewriting entire applications.
An event-driven architecture supports the analysis of event notifications to make decisions based on situational awareness.
Thanks to the rise of the digital enterprise, IoT and real-time analytics, event-driven architecture has moved from the shadows to the business mainstream.
In preparation for the upcoming Kafka Summit, this article discusses the journey Kafka users have taken to get on the API bandwagon.