Apache Kafka Training in Natal

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 built for high-throughput, fault-tolerant data pipelines and real-time analytics.

This instructor-led live training (available 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:

• Understand the components and architecture of Confluent Kafka.
• Deploy and manage Kafka brokers, Zookeeper quorums, and key services.
• Configure advanced features including security, replication, and performance tuning.
• Use 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 a customized training for this course, please contact us to arrange.

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

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

• Grasp the architecture and fundamental 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 within Kafka applications.

This instructor-led live training in Natal (online or on-site) targets intermediate-level system administrators seeking to effectively utilize Kafka's message queuing capabilities.

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

• Comprehend 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 guided, live training in Natal (online or in person) targets beginner to intermediate system administrators aiming to learn how to effectively manage Kafka topics for optimal data streaming and processing.

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

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

This instructor-led, live training in Natal (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 Natal (online or onsite) targets intermediate-level developers who want 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 and 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 course is designed for enterprise architects, developers, system administrators, and anyone seeking to understand and leverage a high-throughput distributed messaging system. If you have more specific requirements (e.g., focusing solely on system administration), this course can be customized to better suit your needs.

This instructor-led, live training in Natal (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 Natal (online or onsite) targets developers aiming to shift from traditional architectures to a highly concurrent microservices-based model using Spring Cloud, Kafka, Docker, Kubernetes, and Redis.

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

• Set up the necessary development environment for building microservices.
• Design and implement a highly concurrent microservices ecosystem using Spring Cloud, Kafka, Redis, Docker and Kubernetes.
• Transform monolithic and SOA services to microservice based architecture.
• Adopt a DevOps approach to developing, testing and releasing software.
• Ensure high concurrency among microservices in production.
• Monitor microservices and implement recovery strategies.
• Carry out performance tuning.
• Learn about future trends in microservices architecture.