Apache Kafka Training in Patras

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

By the conclusion of this course, participants will be capable of:

• Gaining a comprehensive understanding of Confluent Kafka’s components and architecture.
• Deploying and managing Kafka brokers, Zookeeper quorums, and essential services.
• Configuring advanced features such as security protocols, replication mechanisms, and performance tuning.
• Utilizing management tools to effectively monitor and maintain Kafka clusters.

Course Format

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

Customization Options

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

This instructor-led, live training in Patras (online or on-site) is designed for 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 capable of:

• Gaining a solid understanding of Kafka's architecture and core components.
• Setting up and configuring a Kafka cluster.
• Producing and consuming messages using Java.
• Implementing Kafka Streams for real-time data processing.
• Ensuring fault tolerance and scalability within Kafka applications.

This instructor-led, live training in Patras (online or onsite) is designed for 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 retrieve data from Kafka.
• Integrate Kafka with external systems using Kafka Connect.
• Build streaming applications with Kafka Streams & ksqlDB.
• Connect a Kafka client application with Confluent Cloud for cloud-based Kafka deployments.
• Acquire 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 comprehend and leverage a high-throughput distributed messaging system. Should you have specific needs, such as a focus solely on system administration, the course content can be customized to better align with your requirements.

This instructor-led, live training in Patras (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.