Dive into streaming data quality with Gilles Philippart! Learn to keep bad data out with Confluent's Data Quality Rules.

As you scale up the number of teams and apps on #apachekafka , using schemas managed in a Schema Registry will save you endless problems. In this #Kafka Live Stream, learn the fundamentals of schemas for your applications and how you can best manage them.

The dual write problem occurs when you try to write to two separate systems and need them to be atomic. If one write fails, and the other succeeds, you can end up with inconsistent state. This is an easy trap to fall into, and it can be difficult to avoid. We'll explore what causes the dual-write problem and explore both valid and invalid solutions to it.

How to monitor your #kafka connectors, and automatically restart them when they fail.

Building scalable and resilient microservices requires an approach that eliminates the need to treat them as special. They should be treated as easily replaceable building blocks. This means eliminating bottlenecks and single points of failure but it can also mean changing from a pull-based approach to a push-based approach. CHAPTERS.

Transform your ability to understand your streaming landscape, troubleshoot when things go wrong, and keep compliant.

How to adopt data mesh practices into your event-driven application development, allowing the freedom for innovation while meeting diverse data compliance needs.

Communication between microservices can be broadly categorized as either point-to-point or publish/subscribe. Point-to-point is often used synchronously, while publish/subscribe tends to be asynchronous. Each of these techniques can have a place in a modern microservices platform, but it is important to understand the role each one plays so that they can be used effectively. CHAPTERS.