Apache Kafka Training Course – Master Real-Time Data Streaming
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Description of the Apache Kafka Training Course – Master Real-Time Data Streaming
In a permanently connected world, modern architectures must be able to process data streams in real time, at scale, and without interruption. Apache Kafka has established itself as the reference standard for building robust, distributed event streaming systems. This training course gives you the solid foundations needed to design, deploy and operate a Kafka architecture in a professional environment.
Also discover our Kubernetes Training Course – From Code to Cluster in Complete Autonomy, our Spring Microservices and Kubernetes Training Course, our Docker to Kubernetes Training Course, our Docker Training Course, our Advanced Kubernetes and CI/CD Training Course and our Kubernetes Training Course.
Format
Remote (recorded sessions).
GOOD TO KNOW
This training course includes numerous exercises (60% practical) for better learning. Sessions are guaranteed from 1 registered participant (except in cases of force majeure).
This training course is part of our DevOps Training Courses. Discover our complete DevOps offer to go further in automation, CI/CD and infrastructure industrialisation.
Objectives of this Apache Kafka Training Course
By the end of this training course, each participant will be able to:
- Understand the distributed architecture of Kafka.
- Install and configure a local or remote Kafka cluster.
- Create producers and consumers in Java or Python.
- Use Kafka Streams and Kafka Connect to process and integrate data.
- Monitor, scale and secure a Kafka cluster in production.
Prerequisites
Good foundations in software development (Java, Python or equivalent). Knowledge of messaging systems or distributed architecture (a plus). Comfortable with command line and local deployment (Linux/Windows).
TARGET AUDIENCE
Ideal for developers, architects, DevOps/DataOps engineers, or integration managers wishing to master real-time data streaming with Apache Kafka.
Programme of this Apache Kafka Training Course
Introduction to Terraform and IaC
Principes d’Infrastructure as Code, avantages, architecture de Terraform, providers, ressources et blocs HCL.
Writing and executing Terraform code
Creation of.tf files, init, plan, apply, controlled deletion, resource lifecycle management.
Advanced structuring
Variables, outputs,.tfvars files, custom modules, code factorisation, dynamic resource creation.
State, backends, and workspaces
State, backends, and workspaces.
Safety and best practices
Securing secrets, integration with Vault, versioning management, team conventions, linters, and validation.S3, Azure Blob, etc.), locking, organisation by environment.
Multi-cloud case study
Deployment of resources on AWS or Azure, reusable modules, environment logic (dev/stage/prod).
The advantages of this training course
This training course :
- Provides a rigorous and professional approach to Terraform
- Prepares you for secure production deployment with CI/CD and remote backendsmphasises code structuring and team collaboration
- Includes concrete multi-cloud case studies that can be adapted to any real-world project
FAQ – Apache Kafka Training
What is Apache Kafka?
Apache Kafka is a distributed, high-throughput data streaming and messaging platform. It enables systems to publish, store and consume event streams in real time, with strong fault tolerance. It is used for event-driven architectures, log aggregation, CDC and real-time analytics. MFE-IT trains developers and architects.
What is the difference between Kafka and RabbitMQ?
Kafka is a distributed log designed for high throughput and long-term event retention, with a pull-based consumer model. RabbitMQ is an AMQP broker built around message queues, optimised for fine-grained routing and push-based delivery. Kafka excels at streaming and event sourcing; RabbitMQ at transactional exchanges.
What are the typical use cases for Kafka?
Centralised log aggregation, real-time pipelines (Kafka Streams, Flink), event sourcing, CDC with Debezium, asynchronous microservices, metrics and IoT telemetry. MFE-IT illustrates these use cases with concrete examples and explains architectural choices (partitions, keys, consumers, failure recovery).
How long does the Apache Kafka training at MFE-IT last?
The training lasts 3 days (21 hours), either remotely or in-person, with a maximum of 3 participants per session and 30 days of post-training support included.