Apache Kafka Training in Rennes

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 also allows for the evaluation of participants.

• 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 seeking to install, configure, monitor, and troubleshoot Confluent Apache Kafka clusters.

By the conclusion 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 such as security, replication, and performance tuning.
• Utilize management tools to monitor and maintain Kafka clusters.

Format of the Course also allows for the evaluation of participants.

• 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 Rennes (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 Rennes (online or onsite) is designed for intermediate-level developers who want to create big data applications using Apache Kafka.

Upon completing this training, participants will be able to:

• Create Kafka producers and consumers to send and receive data.
• Connect Kafka with external systems via Kafka Connect.
• Build streaming applications using Kafka Streams and ksqlDB.
• Link Kafka client applications to Confluent Cloud for cloud-based Kafka deployments.
• Acquire hands-on experience through practical exercises and real-world scenarios.

Designed for enterprise architects, developers, and system administrators, this course equips learners with the knowledge to understand and leverage high-throughput distributed messaging systems. While it caters to a broad audience, the content can be customized to address specific needs, such as a focus solely on system administration.

This instructor-led, live training in Rennes (online or onsite) is aimed at 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.