📄️ Introduction to Kafka
Apache Kafka: distributed streaming platform, real-time messaging, pub/sub, data processing, scalable architecture, and Kubernetes integration.
📄️ Initial Concepts
Understanding Apache Kafka core concepts: event streaming, advantages, architecture, message production and consumption, development and DevOps practices for distributed systems.
📄️ Architecture
Deep dive into Apache Kafka architecture: brokers, clients, events, topics, partitions, producers, consumers, and security in distributed systems with high availability.
📄️ Development
Apache Kafka development nuances beyond core concepts: serialization, delivery guarantees, idempotence, consumer groups, security mechanisms, authentication, authorization, and Schema Registry integration.
📄️ Ecosystem
Exploring the Apache Kafka ecosystem with external tools and integrations: Kafka Connect for data integration, REST Proxy for HTTP access, Kafka Streams for real-time processing, KSQL for SQL queries, and Cruise Control for intelligent partition balancing.
📄️ Approaches
Apache Kafka installation strategies in Kubernetes and when to use Confluent Cloud SaaS: comparing Strimzi vs CFK operators, Zookeeper vs KRaft consensus, self-managed vs cloud-managed solutions, and vendor lock-in considerations.
📄️ Installation
Deploying Apache Kafka on Kubernetes using Strimzi: operator installation, node pool configuration, custom resources, JBOD storage architecture, Cruise Control setup, and cluster management best practices.
📄️ Tools
Essential tools for working with Apache Kafka: Schema Registry deployment with Confluent for Kubernetes, KsqlDB configuration, graphical interfaces, RBAC management, and topic administration using custom resources.