Stream Processing With Apache Kafka Training Course: Real-time Data Pipelines

Introduction

Revolutionize your data handling with our Stream Processing with Apache Kafka Training Course. This program is designed to equip you with the essential skills to build real-time data pipelines with Kafka, enabling you to process and analyze streaming data efficiently. In today's fast-paced data landscape, mastering Apache Kafka is crucial for organizations seeking to derive immediate insights from their data streams. Our Apache Kafka training course offers hands-on experience and expert guidance, empowering you to leverage Kafka's capabilities for diverse real-time data processing tasks.

This real-time data pipelines training delves into the core concepts of Apache Kafka, covering topics such as message brokers, stream processing, and data partitioning. You'll gain expertise in using industry-standard techniques to build real-time data pipelines with Kafka, meeting the demands of modern data-driven organizations. Whether you're a data engineer, software developer, or data analyst, this Stream Processing with Apache Kafka course will empower you to design and implement robust and scalable real-time data solutions.

Target Audience:

• Data Engineers
• Software Developers
• Data Analysts
• System Administrators
• DevOps Engineers
• Backend Developers
• Anyone needing Apache Kafka skills

Course Objectives:

• Understand the fundamentals of stream processing with Apache Kafka.
• Master Kafka architecture and core concepts.
• Utilize Kafka producers and consumers for data ingestion and processing.
• Implement Kafka topics, partitions, and replication for data reliability.
• Design and build real-time data pipelines with Kafka.
• Optimize Kafka configurations for performance and scalability.
• Troubleshoot and address common issues in Kafka deployments.
• Implement data serialization and schema management in Kafka.
• Integrate Kafka with various data storage and processing systems.
• Understand how to handle large data volumes and high throughput with Kafka.
• Explore advanced Kafka features (e.g., Kafka Streams, Kafka Connect).
• Apply real world use cases for Apache Kafka in stream processing.
• Leverage Kafka's ecosystem for efficient real-time data handling.

Duration

10 Days

Course content

Module 1: Introduction to Apache Kafka

• Fundamentals of stream processing with Apache Kafka.
• Overview of Kafka architecture, topics, and partitions.
• Setting up a Kafka development environment.
• Introduction to Kafka producers and consumers.
• Best practices for Kafka.

Module 2: Kafka Architecture and Concepts

• Mastering Kafka architecture and core concepts.
• Understanding Kafka brokers, topics, and partitions.
• Designing and building Kafka clusters.
• Optimizing Kafka configurations for performance.
• Best practices for Kafka architecture.

Module 3: Kafka Producers and Consumers

• Utilizing Kafka producers and consumers for data ingestion and processing.
• Implementing data ingestion with Kafka producers.
• Designing and building consumer applications.
• Optimizing producers and consumers for data throughput.
• Best practices for producers and consumers.

Module 4: Topics, Partitions, and Replication

• Implementing Kafka topics, partitions, and replication for data reliability.
• Utilizing topic configuration and management.
• Designing and building replicated Kafka clusters.
• Optimizing partitions for data distribution.
• Best practices for topics.

Module 5: Real-Time Data Pipelines

• Designing and building real-time data pipelines with Kafka.
• Implementing data stream processing workflows.
• Utilizing Kafka for data ingestion, transformation, and delivery.
• Optimizing pipelines for real-time analytics.
• Best practices for data pipelines.

Module 6: Kafka Configuration Optimization

• Optimizing Kafka configurations for performance and scalability.
• Utilizing Kafka tuning parameters.
• Implementing resource management and scaling.
• Designing efficient Kafka deployments.
• Best practices for configuration optimization.

Module 7: Troubleshooting Kafka Deployments

• Debugging common issues in Kafka deployments.
• Analyzing Kafka logs and error messages.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common Kafka errors.
• Best practices for troubleshooting.

Module 8: Data Serialization and Schema Management

• Implementing data serialization and schema management in Kafka.
• Utilizing Avro, Protobuf, and JSON schema.
• Designing and building schema registries.
• Optimizing data serialization for performance.
• Best practices for data serialization.

Module 9: Integration with Data Systems

• Integrating Kafka with various data storage and processing systems.
• Utilizing Kafka Connect for data integration.
• Implementing data integration with external databases and APIs.
• Optimizing integration for data retrieval and processing.
• Best practices for integration.

Module 10: Large Data Volumes and High Throughput

• Understanding how to handle large data volumes and high throughput with Kafka.
• Utilizing Kafka for big data streaming.
• Implementing data partitioning and parallel processing.
• Designing scalable data processing workflows.
• Best practices for large data.

Module 11: Advanced Kafka Features

• Exploring advanced Kafka features (Kafka Streams, Kafka Connect).
• Utilizing Kafka Streams for real-time stream processing.
• Implementing Kafka Connect for data integration.
• Designing and building advanced Kafka solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced features.

Module 12: Real-World Use Cases

• Implementing Kafka for real-time analytics and monitoring.
• Utilizing Kafka for log aggregation and processing.
• Implementing Kafka for event-driven microservices.
• Utilizing Kafka for IoT data streaming.
• Best practices for real-world applications.

Module 13: Kafka Tools Implementation

• Utilizing Kafka tools and frameworks (Kafka CLI, Kafka Manager).
• Implementing Kafka applications with specific tools.
• Designing and building automated deployment workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Kafka Monitoring and Logging

• Implementing Kafka monitoring and logging.
• Utilizing Kafka monitoring tools and metrics.
• Designing and building performance dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 15: Future Trends in Kafka Streaming

• Emerging trends in Kafka streaming.
• Utilizing Kafka with cloud-native environments.
• Implementing Kafka for data mesh architectures.
• Best practices for future applications.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.