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Kafka is definitely one of the leading distributed messaging queues, found in use everywhere. More correctly termed “a distributed messaging platform,” it provides three key capabilities: publish-and-subscribe, store streams, process streams. This course introduces the students to using Kafka and architecting systems with it.


Use Kafka to build streaming solutions

What You Will Learn

  • Overview of Streaming technologies
  • Kafka concepts and architecture
  • Programming using Kafka API
  • Kafka Streams
  • Monitoring Kafka
  • Tuning / Troubleshooting Kafka


Developers, architects


Two days
(three- and four-day format goes into architecture, performance, and administration)


Lectures and hands-on labs. (50%   50%)


  • comfortable with Java programming language (programming exercises are in Java)
  • comfortable in Linux environment (be able to navigate Linux command line, run commands)

Lab environment

Zero Install: There is no need to install any software on students’ machines! A lab environment in the cloud will be provided for students.

Students will need the following

  • An SSH client (Linux and Mac already have ssh clients, for Windows Putty is recommended)
  • A browser to access the cluster. We recommend Chrome browser


Detailed outline

  • Section 1: Introduction to Streaming Systems
    • Fast data
    • Streaming architecture
    • Lambda architecture
    • Message queues
    • Streaming processors
  • Section 2: Introduction 
    •  Architecture
    • Comparing Kafka with other queue systems (JMS / MQ)
    • Kaka concepts: Messages, Topics, Partitions, Brokers, Producers, commit logs
    • Kafka & Zookeeper
    • Producing messages
    • Consuming messages (Consumers, Consumer Groups)
    • Message retention
    • Scaling Kafka
    • Labs :
      • Getting Kafka up and running
      • Using Kafka utilities
  • Section 3: Programming With Kafka
    • Configuration parameters
    • Producer API (Sending messages to Kafka)
    • Consumer API (consuming messages from Kafka)
    • Commits, Offsets, Seeking
    • Schema with Avro
    • Lab :
      • Writing Kafka clients in Java
      • Benchmarking Producer APIs
  • Section 4: Kafka Streams
    • Streams overview and architecture
    • Streams use cases and comparison with other platforms
    • Learning Kafka Streaming concepts (KStream, KTable, KStore)
    • KStreaming operations (transformations, filters, joins, aggregations)
    • Labs:
      • Kafka Streaming labs
  • Section 5: Administering Kafka
    • Hardware / Software requirements
    • Deploying Kafka
    • Configuration of brokers / topics / partitions / producers / consumers
    • Security: How secure Kafka cluster, and secure client communications (SASL, Kerberos)
    • Monitoring: monitoring tools
    • Capacity Planning: estimating usage and demand
    • Troubleshooting: failure scenarios and recovery
  • Section 6: Monitoring and Instrumenting Kafka
    • Monitoring Kafka
    • Instrumenting with Metrics library
    • Labs
      • Monitor Kafka cluster
      • Instrument Kafka applications and monitor their performance
  • Final workshop (time permitting)
    • students will build an end-to-end application simulating web traffic and send metrics to Grafana.
      See screenshot and video below!