Booking options
Price on Enquiry
Price on Enquiry
Delivered Online
Two days
All levels
Duration
2 Days
12 CPD hours
This course is intended for
This in an Introductory and beyond level course is geared for experienced Java developers seeking to be proficient in Apache Kafka. Attendees should be experienced developers who are comfortable with Java, and have reasonable experience working with databases.
Overview
Working in a hands-on learning environment, students will explore
Overview of Streaming technologies
Kafka concepts and architecture
Programming using Kafka API
Kafka Streams
Monitoring Kafka
Tuning / Troubleshooting Kafka
Apache Kafka is a real-time data pipeline processor. It high-scalability, fault tolerance, execution speed, and fluid integrations are some of the key hallmarks that make it an integral part of many Enterprise Data architectures. In this lab intensive two day course, students will learn how to use Kafka to build streaming solutions.
Introduction to Streaming Systems
Fast data
Streaming architecture
Lambda architecture
Message queues
Streaming processors
Introduction to Kafka
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
Programming With Kafka
Configuration parameters
Producer API (Sending messages to Kafka)
Consumer API (consuming messages from Kafka)
Commits , Offsets, Seeking
Schema with Avro
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)
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
Trouble shooting : failure scenarios and recovery
Monitoring and Instrumenting Kafka
Monitoring Kafka
Instrumenting with Metrics library
Instrument Kafka applications and monitor their performance
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