Event-driven architecture (EDA) allows businesses to be more aware of everything that is happening in real time.

In modern enterprises, where operations leave a massive digital footprint, business events enable companies to be more adaptive, recognizing and responding to opportunities or threats as they arise. You can optimize your supply chain, create enjoyable, personalized experiences for your customers, and proactively identify quality issues or block customer churn before they occur.

As a result, more event-driven organizations can more effectively differentiate themselves from competitors, ultimately impacting top and bottom lines.

Become a real-time company

When companies deploy EDA, they often embark on a journey that takes them through several stages of maturity.

Phase 1—Tactical and Project-Based

First of all, the potential is demonstrated in the tactical projects delivered by individual teams. They often use Apache Kafka as an open technology and de facto standard for accessing events from a variety of core systems and applications. You can then use this approach to build new responsive applications.

Stage 2 – Widespread Adoption

Increasing awareness across the IT organization will lead to a standardized approach to creating an event backbone that caters to both existing and new event-driven projects across multiple teams. This approach provides operational efficiencies and the ability to create solutions that are resilient and scalable enough to support critical operations.

Stage 3 – Socialization and Management

As adoption increases, better management of event socialization and exposure becomes necessary. Teams want more visibility and access to events so they can reuse and innovate on the work of others. Events have become equally important as application programming interfaces (APIs) with the ability to describe, advertise, and discover events. Self-service access is provided to avoid authorization bottlenecks, along with facilities to maintain appropriate controls over usage.

Step 4 – Innovative Business Strategy

A wider range of users can access and process event streams to understand their relevance in a business context. Event topics can be combined to identify patterns or aggregated to analyze trends and detect anomalies. Event triggers are used to automate workflows or decisions, allowing businesses to create alerts so they can take appropriate action as soon as a situation is detected.

IBM® has created a configurable set of capabilities to support you wherever you are on this event-driven adoption journey. Built on the best of open source technology, each feature emphasizes scalability and is designed for flexibility and compatibility with the entire ecosystem for connectivity, analytics, processing, and more. Whether you’re starting from scratch or looking to take the next step, IBM can help you expand and add value to what you already have.

Building an event backbone

An event backbone is the core of any event-driven enterprise, efficiently delivering business events where they are needed. IBM offers an Event Streams feature build on Apache Kafka that enables event management across the entire enterprise. If you already have a Kafka-based infrastructure in place, Event Streams can seamlessly interoperate with events as part of a hybrid brokering environment.

As part of a Kubernetes-based container orchestration platform, you can use operators to deploy infrastructure as code by building and operating the many components of an Apache Kafka deployment in a consistent and repeatable manner. Kafka clusters can automatically scale on demand with full encryption and access control. Flexible and customizable Kafka configuration can be automated using a simple user interface.

It includes a built-in schema registry that validates your application’s event data as expected, improving data quality and reducing errors. Event schemas help reduce integration complexity by establishing an agreed-upon format across collaborating teams, and Event Streams enable schema evolution and adaptability as event-based adoption accelerates.

Event Streams establishes a highly resilient and highly available event backbone by supporting replication of event data between clusters across multiple zones so that the infrastructure can tolerate zone failures without loss of service availability. For disaster recovery, geo-replication allows you to create copies of event data to be sent to a backup cluster, and can be configured with just a few clicks through the user interface.

An event backbone is only as good as the event data it can access, and Event Streams supports a wide range of connectors to the major applications, systems, and platforms where event data is generated or consumed. The Connector Catalog contains an extensive list of key connectors supported by IBM and the community.

Rounding out all these features is a comprehensive management interface that enables seamless monitoring and operation of your Kafka environment and connected applications. This includes the ability to drill down into details of individual event payloads, schemas, publishing, and consumption rates, as well as overall system health, and helps identify and resolve problematic event data.

Event-based extension management

Many organizations have reached a point where their use of events is rapidly expanding. New event streams are being created every day by multiple teams that don’t necessarily see each other’s activities. This begins with concerns about duplication and how to improve visibility and promote greater efficiency and reuse. Of course, reuse can come with its own challenges. How is access controlled? How do you manage your workload to avoid crowding your backend systems? How can you avoid breaking changes that impact many teams?

To address these issues, many companies are starting to handle event interfaces more formally and apply best practices developed as part of API management to ensure that event interfaces are well described and versioned, that access is separated and isolated, and that usage is properly handled. Protect and manage.

IBM provides event endpoint management capabilities that enable everyone to discover and consume existing events and manage event sources, such as APIs, to securely reuse them across the enterprise. This capability not only allows you to manage IBM’s Event Streams, but it can also do this for any Kafka-based event-driven applications and backbones you already have, following the open approach already described.

This allows event interfaces to be described in a consistent framework based on the AsyncAPI open standard. This means that it is understandable to people, supported by code generation tools, and consistent with the API definition. Event Endpoint Management generates valid AsyncAPI documents based on the event schema or sample messages.

Provides a catalog for publishing event interfaces for others to discover. This includes defining lifecycle management, versioning, and policy-based controls. For example, it integrates with identity access management solutions to require users to provide valid credentials and provides role-based access.

Catalog users can then search for available events, understand those events, and easily register for self-service access. Usage analytics allows event owners to monitor subscribers and revoke access when necessary. Teams providing topics for reuse can place them directly in the catalog and consumers can self-manage access, significantly reducing the burden on Kafka administrators.

Event Endpoint Management provides an event gateway that ensures that consumers are decoupled from event producers and brokers, isolated from each other, and any changes to the data format are managed. It also enforces policy-based controls, applying them directly to the Kafka protocol itself. This means that you can manage Kafka-compatible implementations that are part of the ecosystem.

Detect and act on business situations

As events are reused in different ways and use cases become more sophisticated, events often need to be further refined or combined with other events to identify the most interesting business situations that require action. Events can become more actionable when strengthened by external data or when they occur in conjunction with other events in a specific time period.

IBM provides event processing capabilities to help you work with events to understand business context. It includes a low-code user interface and a powerful open source event processing engine designed to enable a wide range of users to work with events. If you already have a Kafka-based infrastructure deployed, event processing can work with events pulled from any Apache Kafka implementation in your environment.

The event processing runtime is built on Apache Flink, an open, reliable, extensible and secure way to run event processing flows. The IBM event processing runtime is fully supported, deployed, and managed using Kubernetes operators. This simplifies deployment and management when deploying as a shared execution environment or as part of an app.

Low-code tools allow users to connect event sources to a series of operations that define how to handle the event. Combine events from multiple sources to identify situations derived from different events that occur, filter events to remove unrelated events from the stream, aggregate events to count occurrences across different time windows, and fields within events You can get new information and lots of information by doing calculations using . more. Traditionally, handling these types of events required highly skilled programmers. This tool allows users to prototype a wide range of potentially useful scenarios in a safe and non-destructive environment.

It’s designed to let you drag and drop event sources, destinations, and processing actions to connect them together and process events in an intuitive and visual way with productivity support and validation at each step. The ability to click Run, immediately see the output director in the editor, and then pause processing to edit it before running it again allows rapid iteration of solutions. Results can be exported or sent to Kafka as a continuous stream.

Event processing enables collaboration by enabling the creation and deployment of many solutions, allowing multiple team members to share and collaborate within a workspace. The event processing logic generated by the tool can be exported to a tool such as GitHub, allowing it to be shared with others within the organization. Tutorials and context-sensitive help make it easy for new team members to get up to speed and start contributing.

Once a solution is configured in event processing, output can be sent to multiple locations for observability and drive actions, including cloud-based applications, automation platforms, or business dashboards that can use Kafka inputs.

Are you ready to take the next step?

IBM Event Automation, a fully configurable, event-driven service, allows companies to take their efforts wherever they are along the journey. Event streams, event endpoint management, and event processing capabilities help lay the foundation for an event-driven architecture to unlock the value of events.

Visit our website to request a demo and learn more.