Apache Flink for all: Making Flink consumable across all areas of your business

In an era of rapid technological advancements, responding quickly to changes is crucial. Event-driven businesses across all industries thrive on real-time data, enabling companies to act on events as they happen rather than after the fact. These agile businesses recognize needs, fulfill them and secure a leading market position by delighting customers.

This is where Apache Flink shines, offering a powerful solution to harness the full potential of an event-driven business model through efficient computing and processing capabilities. Flink jobs, designed to process continuous data streams, are key to making this possible.

Imagine a retail company that can instantly adjust its inventory based on real-time sales data pipelines. They are able to adapt to changing demands quickly to seize new opportunities. Or consider a FinTech organization that can detect and prevent fraudulent transactions as they occur. By countering threats, the organization prevents both financial losses and customer dissatisfaction. These real-time capabilities are no longer optional but essential for any companies that are looking to be leaders in today’s market.

Apache Flink takes raw events and processes them, making them more relevant in the broader business context. During event processing, events are combined, aggregated and enriched, providing deeper insights and enabling many types of use cases, such as:

1. Data analytics: Helps perform analytics on data processing on streams by monitoring user activities, financial transactions, or IoT device data.
2. Pattern detection: Enables identifying and extracting complex event patterns from continuous data streams.
3. Anomaly detection: Identifies unusual patterns or outliers in streaming data to pinpoint irregular behaviors quickly.
4. Data aggregation: Ensures efficient summarization and processing of continuous data flows for timely insights and decision-making.
5. Stream joins: Combines data from multiple streaming platforms and data sources for further event correlation and analysis.
6. Data filtering: Extracts relevant data by applying specific conditions to streaming data.
7. Data manipulation: Transforms and modifies data streams with data mapping, filtering and aggregation.

Apache Flink augments event streaming technologies like Apache Kafka to enable businesses to respond to events more effectively in real time. While both Flink and Kafka are powerful tools, Flink provides additional unique advantages:

• Data stream processing: Enables stateful, time-based processing of data streams to power use cases such as transaction analysis, customer personalization and predictive maintenance through optimized computing. 
• Integration: Integrates seamlessly with other data systems and platforms, including Apache Kafka, Spark, Hadoop and various databases. 
• Scalability: Handles large datasets across distributed systems, ensuring performance at scale, even in the most demanding Flink jobs.
• Fault tolerance: Recovers from failures without data loss, ensuring reliability.

It comes as no surprise that Apache Kafka is the de-facto standard for real-time event streaming. But that’s just the beginning. Most applications require more than just a single raw stream and different applications can use the same stream in different ways.

Apache Flink provides a means of distilling events so they can do more for your business. With this combination, the value of each event stream can grow exponentially. Enrich your event analytics, leverage advanced ETL operations and respond to increasing business needs more quickly and efficiently. You can harness the ability to generate real-time automation and insights at your fingertips.

IBM® is at the forefront of event streaming and stream processing providers, adding more value to Apache Flink’s capabilities. Our approach to event streaming and streaming applications is to provide an open and composable solution to address these large-scale industry concerns. Apache Flink will work with any Kafka topic, making it consumable for all.

The IBM technology builds on what customers already have, avoiding vendor lock-in. With its easy-to-use and no-code format, users without deep skills in SQL, Java, or Python can leverage events, enriching their data streams with real-time context, irrespective of their role. Users can reduce dependencies on highly skilled technicians and free up developers’ time to accelerate the number of projects that can be delivered. The goal is to empower them to focus on business logic, build highly responsive Flink applications and lower their application workloads.

IBM Event Automation, a fully composable event-driven service, enables businesses to drive their efforts wherever they are on their journey. The event streams, event endpoint management and event processing capabilities help lay the foundation of an event-driven architecture for unlocking the value of events. You can also manage your events like APIs, driving seamless integration and control.

Take a step towards an agile, responsive and competitive IT ecosystem with Apache Flink and IBM Event Automation.