Apache Kafka Training in Milan

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 onsite) targets intermediate-level system administrators and DevOps professionals looking to install, configure, monitor, and troubleshoot Confluent Apache Kafka clusters.

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

• Grasp the 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.
• Utilize management tools to monitor and maintain Kafka clusters.

Course Format

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

Customization Options

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

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

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

• Comprehend 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 within Kafka applications.

This instructor-led live session, available Milan (online or onsite), targets intermediate-level system administrators aiming to effectively utilize Kafka's message queuing features.

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

• Comprehend the architecture and capabilities of Kafka's message queuing.
• Configure Kafka topics tailored for message queuing scenarios.
• Produce and consume messages using Kafka.
• Monitor and manage Kafka when used as a message queue.

This instructor-led, live training in Milan (online or onsite) is designed for system administrators at the beginner to intermediate level who wish to learn how to effectively manage Kafka topics for efficient data streaming and processing.

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

• Understand Kafka topic fundamentals and architecture.
• 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 Milan (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 Milan (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.

Designed for enterprise architects, developers, and system administrators, this course enables participants to master the implementation and management of high-throughput distributed messaging systems. The curriculum can be customized to address specific professional needs, such as focusing exclusively on system administration tasks.

This instructor-led, live training in Milan (online or on-site) is aimed at beginner-level, intermediate-level, and 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 Milan (online or on-site) targets developers who aim to transform traditional architecture into a highly concurrent microservices-based architecture 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.