Mule Meets Kafka: Best Practices For Data Consumption 
Published 3/2024 
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz 
Language: English

| Size: 4.16 GB[/align]
| Duration: 7h 3m 
Discover MuleSoft's capabilities for Kafka and Confluent to consume data performant, fault-tolerant and reusable

[b]What you'll learn[/b]

How to implement a performant, fault-tolerant and reusable Kafka data consumption solution using MuleSoft

Gaining significantly better performance results by using batch messages and parallel processing

Filtering and logging problematic messages without using a dead-letter queue

Ensuring consistency when dealing with messages that have to be consumed following the "all or nothing" principle

Populating a target system using the example of a database

Extract recurrent parts of your implementation to reusable components

Take special actions such as stopping the consumption flow in case of a critical error

Populating a Kafka topic with large and customized mocking data using DataWeave capabilities

[b]Requirements[/b]

Basic understanding of Apache Kafka, Mule API implementation concepts and relational databases

For the hands-on part: A recent Windows or Mac machine with at least 8GB RAM (16GB recommended), approximately 20 GB of disk space, a REST client such as Postman, a Docker Desktop and a Maven installation

Description

Are you looking for a way to consume data from Kafka topics quick, reliable and efficient?Maybe you have already tried to use MuleSoft for consuming Kafka topic data and struggled with performance issues, unrecoverable errors or implementation efforts?If so this course is for you.You will learn about MuleSoft's capabilities that will allow you toconsume your data in a performant way by using parallelism and data segmentation at multiple levelshandle errors effectively by classifying an error based on several criteria such as reproducibility and triggering appropriate actionsspeed up implementation by creating reusable components that are available across your appsensure data consistency in case of an incomplete or aborted consumptionAfter this course, you will have a better understanding of which tasks you should pay attention to when implementing a Kafka topic data integration solution and how MuleSoft can help you solving them.This is a hands-on course that guides you in implementing and testing a complete sample application from scratch on your computer for consuming data from a Kafka topic and populating the data to a target system. This also includes the hosting and population of a sample Confluent Kafka topic with mocking data.The capabilities you will learn about are also potentially useful for integrating data from other sources than a Kafka topic.

Overview

Section 1: Introduction

Lecture 1 Why I made this course

Lecture 2 The overall picture

Lecture 3 A personal message from your instructor

Section 2: Setting up your environment

Lecture 4 Apache Kafka

Lecture 5 MySQL

Lecture 6 MuleSoft

Section 3: Consuming the data

Lecture 7 Implementing the basic consumption process

Lecture 8 Preparing the payload

Lecture 9 Populating the target system

Lecture 10 Handling tombstone messages

Section 4: Error handling

Lecture 11 Overview

Lecture 12 Populating the error log table

Lecture 13 Handling deserialization errors

Lecture 14 Handling System API call errors

Lecture 15 Logging the Correlation ID

Lecture 16 Stopping the consumption flow

Section 5: Reusability

Lecture 17 Overview

Lecture 18 Extracting message deserialization and payload preparation

Lecture 19 Extracting message consumption and error handling

Lecture 20 Congratulations

Developers and architects who want to get to know MuleSoft's capabilities for performant, fault-tolerant and reusable data consumption,Developers who want to geo to know which tasks you should pay attention to when implementing a Kafka topic data integration solution and how MuleSoft can help you solving them

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