Kafka for Application Modernization Training

About the Training

The Kafka for Application Modernization Training teaches the use of Apache Kafka in application modernization processes. This training covers the essential topics required for the effective use of Kafka in modernizing applications.

The training focuses on the fundamental structures of Apache Kafka, including data stream processing, fault tolerance, messaging, and other core concepts. Participants develop Kafka usage skills through examples and projects.

The training also teaches how Kafka can be utilized during the application modernization process. Participants learn about Kafka’s capabilities in big data processing, real-time analytics, fault tolerance, and other features. Additionally, they understand how Kafka can be used as a distributed publishing platform.

The Kafka for Application Modernization Training covers the entire application modernization process. Participants gain the foundational skills needed before beginning to develop modern applications. The training provides learning through examples, practical applications, and projects, helping participants start their application modernization journey.

The program begins with the fundamentals of Apache Kafka. Participants learn key concepts such as processing data streams with Kafka, managing messaging systems, and fault tolerance. They also gain an understanding of Kafka’s role in the development and management of modern applications, forming the basic building blocks needed for the application modernization process.

The training emphasizes Kafka’s core features and components, equipping participants with capabilities such as real-time data processing, handling large data streams, and fault tolerance. Topics such as topic streams, data flow, and the management of distributed systems are covered.

Finally, the training provides insights into how to modernize an application using Kafka. This process includes final testing of the application, managing data streams with Kafka, and ultimately, completing the application modernization. These insights help participants successfully modernize their applications with Kafka.

What Will You Learn?

 
  • Apache Kafka: Understanding the Apache Kafka system and its features.
  • Data Flow: Concepts of data flow design, publisher-subscriber systems, and how Apache Kafka can be utilized in this context.
  • Application Architecture: Modern application architecture design and how Apache Kafka can be integrated into this architecture.
  • Data Mapping: Data mapping and analytics, and how Apache Kafka supports data mapping and analytical processes.
  • Performance: Techniques to enhance the performance and scalability of Apache Kafka.
  • Application Development: Topics and practical applications of developing applications using Apache Kafka.

Prerequisites

The prerequisites for the Kafka for Application Modernization Training include having an operating system and a Java Development Environment (IDE) installed on your personal computer. Additionally, you are expected to have a good understanding of the following topics:
  • Programming Languages: Java or a similar programming language.
  • Data Structures and Algorithms: Basic knowledge of data structures and algorithms.
  • Application Architecture and Design: Basic knowledge of application architecture and design.
  • Data Mapping and Analytics: Basic knowledge of data mapping and analytics.

Who Should Attend?

The Kafka for Application Modernization Training is suitable for the following professional categories:
  • Software Developers: Application developers who want to learn how to perform data mapping and distribution.
  • DevOps and System Administrators: DevOps and system administrators who want to learn how to design and deploy modern application architectures.
  • Data Analysts and Data Scientists: Data analysts and data scientists who want to learn how to use Apache Kafka in data mapping and analytical applications.
  • IT Project Managers and Project Managers: IT project managers and project managers who want to learn how to design and deploy modern application architectures.

Outline

Introduction to KAFKA
  • Messaging Architectures – What is Messaging?
  • Messaging Architectures – Steps to Messaging
  • Messaging Architectures – Messaging Models
  • What is Kafka?
  • What is Kafka? (Contd.)
  • Kafka Overview
  • Need for Kafka
  • When to Use Kafka?
  • Kafka Architecture
  • Core concepts in Kafka
  • Kafka Topic
  • Kafka Partitions
  • Kafka Producer
  • Kafka Consumer
  • Kafka Broker
  • Kafka Cluster
  • Why Kafka Cluster?
  • Sample Multi-Broker Cluster
  • Overview of ZooKeeper
  • Kafka Cluster & ZooKeeper
  • Who Uses Kafka?
  • Summary
Using Apache Kafka
  • Installing Apache Kafka
  • Configuration Files
  • Starting Kafka
  • Using Kafka Command Line Client Tools
  • Setting up a Multi-Broker Cluster
  • Using Multi-Broker Cluster
  • Kafka Connect
  • Kafka Connect – Configuration Files
  • Using Kafka Connect to Import/Export Data
  • Creating a Spring Boot Producer
  • Adding Kafka dependency to pom.xml
  • Defining a Spring Boot Service to Send Message(s)
  • Defining a Spring Boot Controller
  • Testing the Spring Boot Producer
  • Creating a Nodejs Consumer
  • Summary
Building Data Pipelines
  • Building Data Pipelines
  • Considerations When Building Data Pipelines
  • Timeliness
  • Reliability
  • High and Varying Throughput
  • High and Varying Throughput (Contd.)
  • Data Formats
  • Data Formats (Contd.)
  • Transformations
  • Transformations (Contd.)
  • Security
  • Failure Handling
  • Coupling and Agility
  • Ad-hoc Pipelines
  • Loss of Metadata
  • Extreme Processing
  • Kafka Connect Versus Producer and Consumer
  • Kafka Connect Versus Producer and Consumer (Contd.)
  • Summary
Integrating Kafka with Other Systems
  • Introduction to Kafka Integration
  • Kafka Connect
  • Kafka Connect (Contd.)
  • Running Kafka Connect
  • Key Configurations for Connect workers:
  • Kafka Connect API
  • Kafka Connect Example – File Source
  • Kafka Connect Example – File Sink
  • Kafka Connector Example – MySQL to Elasticsearch
  • Kafka Connector Example – MySQL to Elasticsearch (Contd.)
  • Write the data to Elasticsearch
  • Building Custom Connectors
  • Kafka Connect – Connectors
  • Kafka Connect – Tasks
  • Kafka Connect – Workers
  • Kafka Connect – Workers (Contd.)
  • Kafka Connect – Converters and Connect’s data model
  • Kafka Connect – Offset management
  • Alternatives to Kafka Connect
  • Alternatives to Kafka Connect (Contd.)
  • Introduction to Storm
  • Other Components of Spark
  • Integrating Storm with Kafka
  • Integrating Storm with Kafka – Sample Code
  • Integrating Storm with Kafka
  • Introduction to Hadoop
  • Hadoop Components
  • Integrating Hadoop with Kafka
  • Hadoop Consumers
  • Hadoop Consumers (Contd.)
  • Hadoop Consumers (Contd.)
  • Hadoop Consumers – Produce Topic
  • Hadoop Consumers – Fetch Generated Topic
  • Summary
Kafka Security
  • Kafka Security
  • Encryption and Authentication using SSL
  • Encryption and Authentication using SSL (Contd.)
  • Configuring Kafka Brokers
  • Configuring Kafka Brokers – Optional Settings
  • Authenticating Using SASL
  • Authenticating Using SASL – Configuring Kafka Brokers
  • Authenticating Using SASL – Configuring Kafka Brokers (Contd.)
  • Authorization and ACLs
  • Authorization and ACLs (Contd.)
  • Securing a Running Cluster
  • Securing a Running Cluster (Contd.)
  • ZooKeeper Authentication
  • ZooKeeper Authentication (Contd.)
  • Summary
Monitoring Kafka
  • Introduction
  • Metrics Basics
  • JVM Monitoring
  • Garbage collection
  • Garbage Collection (Contd.)
  • Java OS monitoring
  • OS Monitoring
  • OS Monitoring (Contd.)
  • Kafka Broker Metrics
  • Under-Replicated Partitions
  • Active controller count
  • Request handler idle ratio
  • Intelligent Thread Usage
  • All topics bytes in
  • All topics bytes out
  • All topics messages in
  • Partition count
  • Leader count
  • Offline partitions
  • Request metrics
  • Request Metrics (Contd.)
  • Logging
  • Logging (Contd.)
  • Client Monitoring
  • Producer Metrics
  • Overall producer metrics
  • Overall producer metrics (Contd.)
  • Per-broker and per-topic metrics
  • Consumer Metrics
  • Fetch Manager Metrics
  • Per-broker and per-topic metrics
  • Consumer coordinator metrics
  • Quotas
  • Quotas (Contd.)
  • Lag Monitoring
  • Lag Monitoring (Contd.)
  • End-to-End Monitoring
  • Summary
Kafka Operational Aspects
  • Kafka Administration
  • Kafka Cluster Management
  • Kafka Replica Distribution
  • Partition Reassignment
  • Partition Reassignment (Contd.)
  • Kafka Topic Management
  • Kafka Topic Management (Contd.)
  • Kafka Cluster Mirroring
  • Kafka Cluster Mirroring (Contd.)
  • Integration with Other Tools
  • Summary

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