Apache Kafka Training in Maia

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 onsite) is aimed at intermediate-level engineers and administrators who wish to deploy, configure, and optimize 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.

Format of the Course

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

Course Customization Options

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

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

This instructor-led live training, available online or onsite, is tailored for intermediate-level system administrators and DevOps professionals aiming to install, configure, monitor, and troubleshoot Confluent Apache Kafka clusters.

Upon completion of this training, participants will be able to:

• Comprehend the components and architecture of Confluent Kafka.
• Deploy and manage Kafka brokers, Zookeeper quorums, and essential services.
• Configure advanced features, including security, replication, and performance tuning.
• Utilize management tools to monitor and maintain Kafka clusters.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Maia (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 Maia (online or onsite) is designed for intermediate system administrators aiming to effectively utilize Kafka's message queuing features.

By the end of the 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 Maia (online or onsite) is intended for system administrators at beginner to intermediate levels who aim to learn how to effectively manage Kafka topics for efficient data streaming and processing.

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

• Comprehend 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.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level developers who wish to learn the fundamentals of Kafka and 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.

This instructor-led, live training in Maia (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 Maia (online or onsite) is aimed at developers who wish to integrate Apache Kafka with existing databases and applications for processing, analysis, etc.

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

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

This instructor-led live training, available both online and onsite, targets engineers looking to leverage Confluent (a distribution of Kafka) to construct and manage a real-time data processing platform for their applications.

Upon completing this training, participants will be able to:

• Install and configure the Confluent Platform.
• Utilize Confluent’s management tools and services to simplify Kafka operations.
• Store and process incoming stream data.
• Optimize and manage Kafka clusters.
• Secure data streams.

Format of the Course

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

Course Customization Options

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

Apache Kafka serves as a distributed streaming platform and stands as the industry standard for developing data pipelines. It addresses a wide array of data processing use cases, functioning effectively as a message queue, distributed log, stream processor, and more.

The course begins by exploring the theoretical foundations of data pipelines before delving into Kafka’s core concepts. We will also examine key components such as Kafka Streams and Kafka Connect.

In this instructor-led, live training in Maia (onsite or remote), participants will learn how to set up and integrate different Stream Processing frameworks with existing big data storage systems and 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 job.
• Process of data continuously, concurrently, and in a record-by-record fashion.
• Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
• Integrate the most appropriate stream processing library with enterprise applications and microservices.

This course is designed for enterprise architects, developers, system administrators, and anyone interested in mastering high-throughput distributed messaging systems. If you have specific requirements (e.g., focusing solely on system administration), the course content can be customized to better align with your needs.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level / intermediate-level / 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 Maia (online or onsite) is designed for data engineers, data scientists, and programmers who wish to leverage Apache Kafka capabilities for data streaming with Python.

By the end of this training, participants will be able to use Apache Kafka to monitor and manage conditions in continuous data streams using Python programming.

This instructor-led, live training in Maia (online or onsite) is designed for software testers who wish to integrate network security measures into an Apache Kafka application.

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

• Deploy Apache Kafka on a cloud-based server.
• Implement SSL encryption to mitigate attacks.
• Add ACL authentication to monitor and manage user access.
• Ensure that authorized clients can access Kafka clusters using SSL and SASL authentication.

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

In this instructor-led live training, participants will learn how to integrate Kafka Streams into sample Java applications that send and receive data via Apache Kafka for stream processing.

Upon completion of this training, participants will be able to:

• Grasp Kafka Streams features and its advantages compared to 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

Format of the course

• A mix of lectures, discussions, exercises, and extensive hands-on practice

Notes

• To request a customized training for this course, please contact us to make arrangements.

This instructor-led, live training in Maia (online or onsite) is designed for data scientists who wish to employ the SMACK stack to construct data processing platforms for big data solutions.

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

• Implement a data pipeline architecture for processing big data.
• Develop cluster infrastructure with Apache Mesos and Docker.
• Analyze data with Spark and Scala.
• Manage unstructured data with Apache Cassandra.

This instructor-led live training in Maia (online or onsite) is designed for developers aiming to shift traditional architectures to highly concurrent microservice-based systems using Spring Cloud, Kafka, Docker, Kubernetes, and Redis.

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

• Establish the required development environment for constructing microservices.
• Design and implement a highly concurrent microservices ecosystem leveraging Spring Cloud, Kafka, Redis, Docker, and Kubernetes.
• Converting monolithic and SOA services into a microservice-based architecture.
• Embrace a DevOps methodology for software development, testing, and deployment.
• Maintain high concurrency among microservices in production environments.
• Monitor microservices and execute recovery strategies.
• Perform performance tuning.
• Explore future trends in microservices architecture.