Introduction to Kafka


Course Number: MSV-104

Duration: 3 days (19.5 hours)

Format: Live, hands-on

Kafka Training Overview

This Kafka training course teaches attendees how to use the Kafka messaging system for consuming data in their systems and to configure a distributed messaging broker.

Location and Pricing

Accelebrate offers instructor-led enterprise training for groups of 3 or more online or at your site. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for private corporate training on-site or online, please contact us.

Objectives

  • Understand the Apache Kafka architecture and data model
  • Decouple services and distributed systems
  • Build robust systems using distributed messaging brokers
  • Configure Kafka clusters in production
  • Write custom Kafka producers and consumers
  • Build an application that ingests data from a streaming API

Prerequisites

Students should have at least one programming language (preferably Python, Java, or Scala) and be able to work from the command line in a Linux VM or container.

Outline

Expand All | Collapse All

Introduction
Big Data and Distributed Systems Primer
  • Distributed systems
  • High availability
  • Latency and scalability
  • Message brokers and queues
  • Decoupling services
  • Lambda architecture
  • Data partitioning
Introduction to Apache Kafka
  • History
  • What is Kafka?
  • Why Kafka?
  • Features
  • Kafka in production
  • High-Level architecture
Core Concepts
  • Kafka guarantees/message ordering
  • Delivery semantics
  • Dumb broker vs. MOM
  • Kafka semantics
Kafka Cluster
  • Installing cluster
  • Brokers
  • Consumers
  • Producers
Apache Zookeeper
  • Cluster management
  • Roles
  • Basic operations
Kafka Producers
  • Role of producer
  • Records
  • Message durability
  • Batching and compression
  • Create console producer
  • Publishing data to topics
Kafka Consumers
  • Role of consumer
  • Offsets
  • Consumers and logs
  • Create console consumer
  • Performance tuning
  • Consumer groups
  • Consumer parallelism
  • Consumer rebalancing
Kafka Data Model
  • Kafka data model
  • Topics
  • Partitions
  • Distribution
  • Reliability
  • Leaders/followers
  • Replication factor
  • Persistence
Kafka API
  • Producer API
  • Consumer API
  • Java, Scala, Python APIs
  • Creating/modifying topics
  • Partitioning topics
  • Reading data from Kafka
  • Writing data to Kafka
Kafka in Production
  • Big Data Pipelines
  • Microservices
  • Case Study: Netflix
  • Apache Spark
  • Storm and Hadoop
Kafka Streams 
  • Stream processing
  • High-Level overview
  • Demo application
Conclusion

Training Materials:

All Kafka training students receive comprehensive courseware.

Software Requirements:

  • Upon request, Accelebrate can provide information for running the software for this class locally or for accessing it in our cloud environment.


Learn faster

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Satisfaction guarantee

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