This is the third blog in our series on Kafka, where we continue to explore the nuances of deploying Kafka for scale. In our previous blogs, Essential Metrics for Kafka Performance Monitoring and Auto-Instrumenting OpenTelemetry for Kafka, we laid the foundation for understanding Kafka’s performance and monitoring aspects. Now, as we explore further into the Kafka ecosystem, we’re here to tackle the common challenges that can arise during deployment and scaling.

Apache Kafka is an open-source distributed streaming system that has grown in popularity and usage across the technology industry. Originating from LinkedIn and now part of the Apache Software Foundation, Kafka provides a robust and scalable platform. It’s uniquely designed with an architecture that includes both a storage layer and a compute layer.