Interest in online banking is skyrocketing. In this context, more and more banking providers are building digital products (especially mobile offerings) and improving their core capabilities to meet user expectations of the instantaneous, always-on, realtime world. In this blog post, we will look at Kafka’s characteristics and explore why it’s such a popular choice for architecting event-driven realtime banking ecosystems.

Getting data from a database into Kafka is one of the most frequent use cases we see. For data integration between enterprise data sources when migrating from monolith to microservices, what better than CDC? We talked about breaking up a monolith and the importance of data observability previously. Now we’re showing you how to do it with a typical microservices architecture pattern including PostgreSQL, Debezium and Apache Kafka.

As a developer, you're no stranger to your vast and varied data environment… Or are you? The tremendous amount of data your organization collects is stored in various sources and formats. You need a way to understand where and what data is, to be able to do what you need to do: build amazing event-driven applications.

In an event-driven architecture, event routers are the components that connect event consumers to event producers. Not all implementations of event routers are the same, nor do any of them offer an all-purpose solution, so deciding which one to use depends on your use case and project's needs. Understanding their capabilities and limitations provides key insights that empower you to confidently decide which one to use and prepare you to navigate its shortcomings.

When you’re one of many developers commanding streaming applications running in Apache Kafka, you want enough data observability to fly your own data product to the moon. But you also want to boldly go where no developer has gone before to discover new applications. At the same time, you don’t want to be exposed to sensitive data that summons you to your compliance team, crashing you back down to earth.

You’ve been handed the not-so-easy task of scoping a managed Kafka for your team. How do you start the shortlist? Post something on Reddit? Skim read a gazillion review blogs? Crash Google Chrome opening a thousand tabs to compare feature lists? If you’re going to run a Kafka POC with two or three vendors, or you’re trying to find the best Kafka for your business, how can you narrow down your selection? Let’s get to it.