Apache Kafka Training and Certification

Apache Kafka is an open-source messaging infrastructure designed by LinkedIn and used by several major SaaS (Software as a Service) applications that we use on a daily basis. Kafka was designed to work with large scale data movements and offer seamless performance and reliability.

Today when most IT professionals are dealing with a data deluge in the form of hundreds of billions of message, Kafka is the big data solution that you need! Apache Kafka training will take you through the architectural design of Kafka that enables it to process large strings of data in real-time.

Kafka stores, processes, and publishes streams of data records seamlessly as they occur and in a durable manner. The speed and performance of Kafka can be attributed to the fact that it runs as a cluster on multiple servers, enabling it to span across several data centers.

IT professionals can use Kafka certification to dive into the intrinsic architecture of Apache Kafka. Moreover, it helps to understand Kafka API streams, learn how it is developed on Java, and eventually develop cutting-edge big data solutions using Kafka.

Course Content

Introduction to Apache Kafka

• Overview of event streaming and its importance.

• Introduction to Apache Kafka and its key features.

• Understanding Kafka architecture: topics, partitions, brokers, producers, and consumers.

Kafka Installation and Configuration

• Installing and setting up Apache Kafka on different platforms.

• Configuration of Kafka brokers, topics, and partitions.

• Understanding Kafkas storage and retention policies.

Producing and Consuming Data

• Writing Kafka producers to publish data to topics.

• Developing Kafka consumers to subscribe to topics and process data.

• Managing offsets and ensuring data consistency.

Kafka Messaging Patterns

• Understanding different messaging patterns: publish-subscribe and point-to-point.

• Implementing message ordering, data replay, and idempotence.

Kafka Connect

• Introduction to Kafka Connect for integrating Kafka with external data sources and sinks.

• Configuring and using connectors for various use cases.

Kafka Streams and Cluster Management

• Overview of Kafka Streams for building real-time applications and stream processing.

• Developing stream processing applications using the Kafka Streams API.

• Scaling Kafka clusters to handle increased load.

• Replication, failover, and fault tolerance strategies.

Advanced Topics

• Introduction to Kafka ecosystem components like Kafka MirrorMaker and Kafka Connectors.

• Integrating Kafka with other tools like Apache Spark and Elasticsearch.

Troubleshooting and Debugging

• Common issues and challenges in Kafka environments.

• Strategies for diagnosing and resolving problems.