Kafka Fundamentals
An intro training on Apache Kafka, the open-source distributed event streaming platform. We’ll look at the architectural features of Kafka that enable high-performance data delivery.
24 hours
Kafka Fundamentals
Sign Up
24 hours
Schedule and prices
€ 410
Training for 7-8 or more people? Customize trainings for your specific needs
Kafka Fundamentals
Sign Up
24 hours
Schedule and prices
€ 410
Training for 7-8 or more people? Customize trainings for your specific needs


This training will help you get a proper understanding of the architecture and functioning of Apache Kafka, an open-source distributed event streaming platform. We will implement Java-based and REST-based clients for Kafka cluster access, discuss cluster and client configuration to achieve tradeoffs between latency, throughput, durability, and availability. We’ll also consider a multi-cluster setting as it is vital to achieve fault-tolerance and promote scalability.

Kafka Connect allows us to resolve common tasks such as moving data between Kafka and external systems (DBMS, file system, etc.). Using Kafka Streams is the recommended way to build fast and resilient streaming processing solutions.
After completing the course, a certificate
is issued on the Luxoft Training form


  • Understand Kafka architecture
  • Understand the deployment and configuration of Kafka
  • Use REST-based access to Kafka
  • Create Kafka Java API clients
  • Design multi-cluster architectures
  • Use Kafka Connect tools
  • Create Kafka Streams programs

Target Audience

  • Software Developers
  • Software Architects
  • Data Engineers


  • Development experience in Java over 3 months


  • Overview

    • What is Kafka?
    • Kafka Use Cases and Anti Use Cases
    • Kafka vs Database
    • Kafka vs Message Queue
    • Kafka Storage Architecture: Brokers, Topics, Partitions, Segments, Replicas
    • Kafka Cluster Architecture: Zookeeper, Partition Assignment, Replica Leaders and Followers, In-Sync Replicas
    • Kafka Clients and APIs
  • Cluster Setup

    • Practice: Setting up Kafka Cluster using Docker
    • Zookeeper Ensemble Installation
    • Kafka Brokers Installation
  • Applications Development in Java

    • Kafka Producer API: Basics
    • Practice: Single Message Producer
    • Practice: Group Message Producer
    • Practice: Group Producer with Explicit Partitioning
    • Practice: No-key Message Producer
    • Kafka Consumer API: Basics, Consumer Groups
    • Practice: Single Consumer
    • Practice: Multiple Consumers in Same Group
    • Advanced Producing and Consuming: Batching, Retries, Idempotence, Transactions, Consumer Group Rebalance
    • Practice: Producer with no batching and retries
    • Practice: Idempotent Producer
    • Practice: Transactional Producer
    • Practice: Transactional Producer and Consumer
    • Practice: Transactional Consume-Copy-Produce
  • External Access to Kafka Cluster

    • Security: SSL, SASL, Kerberos
    • Confluent REST Proxy: Producing and consuming JSON, Binary and Avro files
    • Practice: Access via REST Proxy
    • Confluent Schema Registry
    • Practice: Use REST Proxy with Schema Registry
  • Operations and Monitoring

    • Performance Goals and Modes of Execution
    • Zookeeper: Configuration, Standalone and Quorum Modes, CLI
    • Cluster Management and Monitoring
    • Practice: Monitoring Kafka using Prometheus
  • Multi Clusters

    • Why Multi Clusters in Kafka?
    • MirrorMakerAccess
    • Practice: Using MirrorMaker to Synchronize Clusters
    • Confluence Replicator
  • Kafka Connect

    • Kafka Connect Architecture
    • Kafka Connect Sinks
    • Practice: FileStream Sink Connector
    • Practice: JDBC Sink Connector
    • Kafka Connect Sources
    • Practice: FileStream Source Connector
    • Practice: JDBC Source Connector
  • Kafka Streams Basics

    • Kafka Streams: Streams DSL, Processor API, StreamBuilder, Topology Creating and Implementing
    • Demo: Implementing Streams Topology
    • Demo: Create Streams application using StreamBuilder
    • Kafka Streams Internals: Multihreading, Multiple Instances and Tasks
    • Schemata in Kafka: Serialization, JSON Schema, Avro Schema, Schema Registry, Schema Evolution
    • Demo: Using JSON Schema
    • Stateful Processing: State Store, Fault Tolerance for State Stores
    • KTable: Update Streams, Caching, Emit Rate, Aggregation
    • Windowing in Streams: Timestamp Extractors, Tumbling, Hopping and Session Windows
    • Streaming Joins: Stream with Stream, KTable with KTable, Stream with KTable
  • Show Entire Program
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