Security for Apache Kafka Training Course

Confluent Apache Kafka is a distributed event streaming platform built for high-throughput, fault-tolerant data pipelines and real-time analytics.

This instructor-led, live training (delivered online or on-site) is designed for intermediate-level system administrators and DevOps professionals who want to install, configure, monitor, and troubleshoot Confluent Apache Kafka clusters.

By the end of this training, participants will be able to:

• Grasp the core components and architecture of Confluent Kafka.
• Deploy and manage Kafka brokers, Zookeeper quorums, and essential services.
• Configure advanced features such as security, replication, and performance tuning.
• Utilise management tools to monitor and maintain Kafka clusters.

Course Format

• Interactive lectures and group discussions.
• Abundant exercises and hands-on practice.
• Practical implementation in a live-lab environment.

Course Customisation Options

• To request a customised version of this course, please get in touch with us to arrange.

This instructor-led, live training in New Zealand (available online or on-site) is tailored for developers who wish to integrate Apache Kafka with existing databases and applications for processing, analysis, and more.

By the end of this training, participants will be able to:

• Use Kafka Connect to ingest large amounts of data from databases into Kafka topics.
• Ingest log data generated by application servers into Kafka topics.
• Make all collected data available for stream processing.
• Export data from Kafka topics into secondary systems for storage and analysis.

Confluent Apache Kafka is an enterprise-grade distributed event streaming platform built on Apache Kafka. It supports high-throughput, fault-tolerant data pipelines and real-time streaming applications.

This instructor-led, live training (online or on-site) is aimed at intermediate-level engineers and administrators who wish to deploy, configure, and optimise Confluent Kafka clusters in production environments.

By the end of this training, participants will be able to:

• Install, configure, and operate Confluent Kafka clusters with multiple brokers.
• Design high-availability setups using Zookeeper and replication techniques.
• Tune performance, monitor metrics, and apply recovery strategies.
• Secure, scale, and integrate Kafka with enterprise environments.

Course Format

• Interactive lecture and discussion.
• Plenty of exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

This instructor-led, live training (delivered online or on-site) is designed for engineers who wish to leverage Confluent (a distribution of Kafka) to build and manage a real-time data processing platform for their applications.

By the end of this training, participants will be able to:

• Install and configure the Confluent Platform.
• Utilise Confluent's management tools and services to streamline Kafka operations.
• Store and process incoming stream data.
• Optimise and manage Kafka clusters.
• Secure data streams.

Course Format

• Interactive lectures and discussions.
• Abundant exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Course Customisation Options

• This course is based on the open-source version of Confluent: Confluent Open Source.
• To request a customised training arrangement for this course, please contact us.

Apache Kafka is a distributed streaming platform. It is the de facto standard for building data pipelines and addresses a wide range of data processing use cases: it can be used as a message queue, distributed log, stream processor, and more.

We'll begin with an overview of the theory behind data pipelines in general, then move on to the core concepts underpinning Kafka. We'll also explore key components such as Kafka Streams and Kafka Connect.

In this instructor-led, live training in New Zealand (delivered onsite or remotely), participants will learn how to set up and integrate various Stream Processing frameworks with existing big data storage systems, related software applications, and microservices.

By the end of this training, participants will be able to:

• Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
• Understand and select the most appropriate framework for the task at hand.
• Process data continuously, concurrently, and on a record-by-record basis.
• Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, and other storage systems.
• Integrate the most suitable stream processing library with enterprise applications and microservices.

This course is designed for enterprise architects, developers, system administrators, and anyone seeking to understand and utilise a high-throughput distributed messaging system. If you have more specific requirements (for example, focusing solely on system administration), this course can be tailored to better suit your needs.

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner-level, intermediate-level, or advanced-level system administrators and operations engineers who wish to use Apache Kafka to deploy, secure, monitor, and troubleshoot Kafka clusters.

By the end of this training, participants will be able to: explain Kafka architecture and KRaft mode, operate and secure Kafka clusters, monitor performance and reliability, and resolve common production issues.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level developers who wish to develop big data applications with Apache Kafka.

By the end of this training, participants will be able to:

• Develop Kafka producers and consumers to send and read data from Kafka.
• Integrate Kafka with external systems using Kafka Connect.
• Write streaming applications with Kafka Streams & ksqlDB.
• Integrate a Kafka client application with Confluent Cloud for cloud-based Kafka deployments.
• Gain practical experience through hands-on exercises and real-world use cases.

This instructor-led, live training in New Zealand (online or on-site) is designed for data engineers, data scientists, and programmers who aim to leverage Apache Kafka capabilities for data streaming using Python.

By the end of this training, participants will be equipped to utilise Apache Kafka to monitor and manage conditions within continuous data streams through Python programming.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level Java developers who wish to integrate Apache Kafka into their applications for reliable, scalable, and high-throughput messaging.

By the end of this training, participants will be able to:

• Understand the architecture and core components of Kafka.
• Set up and configure a Kafka cluster.
• Produce and consume messages using Java.
• Implement Kafka Streams for real-time data processing.
• Ensure fault tolerance and scalability in Kafka applications.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level system administrators who wish to effectively leverage Kafka's message queuing features.

By the end of this training, participants will be able to:

• Understand Kafka's message queuing capabilities and architecture.
• Configure Kafka topics for message queuing scenarios.
• Produce and consume messages using Kafka.
• Monitor and manage Kafka as a message queue.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level developers who wish to master the fundamentals of Kafka and learn how to integrate it with Spring Boot.

By the end of this training, participants will be able to:

• Understand Kafka and its architecture.
• Learn how to install, configure, and set up a basic Kafka environment.
• Integrate Kafka with Spring Boot.

Kafka Streams is a client-side library designed for building applications and microservices that exchange data with an Apache Kafka messaging system. Historically, Apache Kafka has depended on Apache Spark or Apache Storm to process data between message producers and consumers. By invoking the Kafka Streams API directly from within an application, data can be processed inside Kafka itself, eliminating the need to send it to a separate cluster for processing.

In this instructor-led, live training, participants will learn how to integrate Kafka Streams into a set of sample Java applications that exchange data with Apache Kafka for stream processing.

By the end of this training, participants will be able to:

• Understand the features of Kafka Streams and its advantages over other stream processing frameworks
• Process stream data directly within a Kafka cluster
• Develop a Java or Scala application or microservice that integrates with Kafka and Kafka Streams
• Write concise code to transform input Kafka topics into output Kafka topics
• Build, package, and deploy the application

Audience

• Developers

Course Format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Notes

• To request customised training for this course, please contact us to make arrangements

This instructor-led, live training in New Zealand (delivered online or on-site) is designed for beginner to intermediate-level system administrators who wish to learn how to effectively manage Kafka topics to ensure efficient data streaming and processing.

By the end of this training, participants will be able to:

• Understand the fundamentals and architecture of Kafka topics.
• Create, configure, and manage Kafka topics.
• Monitor Kafka topics for health, performance, and availability.
• Implement security measures for Kafka topics.