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We're here to help you find itThe "Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams" course provides an in-depth understanding of building and maintaining event-driven systems. It caters to developers and architects seeking expertise in leveraging Apache Kafka and Red Hat AMQ for real-time data processing.
In Module 1, learners explore the core principles that underpin Event-driven architectures, setting the stage for more advanced concepts.
Module 2 introduces Kafka and AMQ Streams concepts, teaching students to develop basic Messaging functionalities in applications.
Module 3 delves into the Streams API, guiding participants through the creation of sophisticated data streaming applications.
Module 4 focuses on Asynchronous services and the Event collaboration pattern, essential for modern, scalable systems.
Module 5 covers Kafka Connect and Debezium, tools for integrating and reacting to changes in data systems.
Finally, Module 6 equips learners with troubleshooting skills for Kafka and AMQ Streams applications, ensuring they can maintain performance and reliability.
By the end of the course, participants will have a robust skill set for designing and implementing event-driven systems using Apache Kafka and Red Hat AMQ technologies.
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Before enrolling in the "Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams" course, participants should have a solid understanding of the following concepts and skills to ensure they can fully benefit from the training:
While these prerequisites are intended to set a foundation for the course, the training is designed to accommodate learners from various backgrounds and levels of expertise. If you are new to some of these concepts, additional preparatory resources may be available to help you get up to speed before the course begins.
This course equips participants with the skills to design, build, and troubleshoot event-driven applications using Apache Kafka and Red Hat AMQ Streams.
Target Audience and Job Roles for the Course:
Gain expertise in building scalable, high-performance event-driven applications using Apache Kafka and Red Hat AMQ Streams, covering everything from fundamental concepts to advanced data streaming and integration techniques.
The Streams API, particularly in the context of Red Hat AMQ Streams, is a toolset for managing Apache Kafka, which is used for building real-time data pipelines and streaming apps. It simplifies the deployment, scaling, and management of Kafka clusters within Kubernetes environments. Red Hat AMQ Streams enhances Kafka’s capabilities with additional features for monitoring and security, all of which are crucial for efficient, robust application development. This integration allows businesses to handle large amounts of data efficiently, ensuring data consistency and high availability.
Apache Kafka is a powerful tool for handling real-time data feeds. It's designed as a distributed event streaming platform, allowing you to efficiently process large amounts of data in real-time. Kafka works by receiving messages from various data sources and organizing them into categories or "topics." Services can then read and process these messages at their leisure. This system is crucial for businesses that depend on prompt data analysis and decision-making. Red Hat AMQ Streams enhances Kafka with additional capabilities like easier configuration and management, particularly in cloud environments, ensuring reliable and scalable data handling.
Red Hat AMQ Streams, part of the Red Hat AMQ portfolio, is a scalable, distributed streaming platform based on Apache Kafka. It enables enterprises to manage and integrate data with high-throughput and real-time data streaming capabilities. Primarily designed for efficiently handling large volumes of data, AMQ Streams facilitates seamless data exchange between applications and microservices, enhancing the reliability and speed of data processing. Ideal for building data pipelines and streaming applications, it supports a variety of use cases from real-time analytics to event-driven architectures.
Event-driven architectures are a design pattern where the flow of a program is determined by events, such as user actions, sensor outputs, or messages from other programs. Instead of a traditional, linear workflow, components in this architecture react to events and manage them accordingly. This approach enhances flexibility and responsiveness, making it suitable for systems where real-time updates and scalability are necessary. Tools like Red Hat AMQ Streams, part of the broader Red Hat AMQ offerings, help manage data streams efficiently in such architectures, facilitating real-time data processing and communication between different services.
Red Hat AMQ, including Red Hat AMQ Streams, is a messaging platform built for high-performance and reliability. AMQ streams, a part of Red Hat AMQ, specifically handle real-time data processing by leveraging Apache Kafka, a distributed data streaming technology. This enables efficient communication through streaming large volumes of messages across distributed systems. Red Hat AMQ ensures secure and scalable messaging functionalities essential for modern application integration and microservices architectures. The course AD482 particularly focuses on building reactive microservices using these technologies, allowing professionals to implement robust message-driven applications in enterprise environments.
Asynchronous services allow operations within a system to run independently without waiting for other tasks to complete, enhancing efficiency and responsiveness. They're crucial in environments where tasks vary in priority and execution time, enabling systems to handle multiple requests simultaneously without delay. This is particularly important in distributed computing, where services like Red Hat AMQ or AMQ Streams manage data flow and messaging asynchronously across different applications and services, ensuring robust, scalable communication for complex, real-time applications. Asynchronous architecture underpins modern, high-performing applications by reducing bottlenecks and improving user experience.
Event collaboration pattern in technology refers to a design where systems communicate by exchanging events or messages about changes rather than through direct requests. This approach allows different components or services to work together without being tightly coupled, meaning they can operate independently and only interact through these events. This method improves flexibility, scalability, and resilience, as each part can evolve without heavily impacting others. It is particularly useful in complex systems where maintaining direct links between components would be challenging and inefficient.
Kafka Connect is a tool used to stream data between Apache Kafka and other systems like databases, key-value stores, search indexes, and file systems. It simplifies adding new data sources to your Kafka environment, allowing seamless data ingestion and export. This ensures efficient data flow between Kafka and external systems without needing to write custom code, making data integration and real-time processing simpler. Kafka Connect fits flexibly into data architectures, enhancing scalability and reliability in data management and analytics.
Debezium is an open-source distributed platform for change data capture (CDC). It monitors databases and records each row-level change as streams of events, ensuring real-time data synchronization and making the data available for various applications. Debezium is integrated with Kafka, facilitated by Red Hat AMQ Streams, enhancing its scalability and management capabilities. This setup allows organizations to react quickly to data changes, enrich decision-making, and maintain accurate, real-time data across systems.
This course equips participants with the skills to design, build, and troubleshoot event-driven applications using Apache Kafka and Red Hat AMQ Streams.
Target Audience and Job Roles for the Course:
Gain expertise in building scalable, high-performance event-driven applications using Apache Kafka and Red Hat AMQ Streams, covering everything from fundamental concepts to advanced data streaming and integration techniques.
