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Kafka - The Definitive Guide

Real-Time Data and Stream Processing at Scale

Paperback Engels 2021 2e druk 9781492043089
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Samenvatting

Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes.

Engineers from Confluent and LinkedIn responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer.

You'll examine:
- Best practices for deploying and configuring Kafka
- Kafka producers and consumers for writing and reading messages
- Patterns and use-case requirements to ensure reliable data delivery
- Best practices for building data pipelines and applications with Kafka
- How to perform monitoring, tuning, and maintenance tasks with Kafka in production
- The most critical metrics among Kafka's operational measurements
- Kafka's delivery capabilities for stream processing systems

Specificaties

ISBN13:9781492043089
Taal:Engels
Bindwijze:paperback
Aantal pagina's:425
Uitgever:O'Reilly
Druk:2
Verschijningsdatum:30-11-2021
Hoofdrubriek:IT-management / ICT

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Inhoudsopgave

Foreword to the Second Edition
Foreword to the First Edition
Preface
Who Should Read This Book
Conventions Used in This Book
Using Code Examples
O’Reilly Online Learning
How to Contact Us
Acknowledgments

1. Meet Kafka
Publish/Subscribe Messaging
How It Starts
Individual Queue Systems
Enter Kafka
Messages and Batches
Schemas
Topics and Partitions
Producers and Consumers
Brokers and Clusters
Multiple Clusters
Why Kafka?
Multiple Producers
Multiple Consumers
Disk-Based Retention
Scalable
High Performance
Platform Features
The Data Ecosystem
Use Cases
Kafka’s Origin
LinkedIn’s Problem
The Birth of Kafka
Open Source
Commercial Engagement
The Name
Getting Started with Kafka

2. Installing Kafka
Environment Setup
Choosing an Operating System
Installing Java
Installing ZooKeeper
Installing a Kafka Broker
Configuring the Broker
General Broker Parameters
Topic Defaults
Selecting Hardware
Disk Throughput
Disk Capacity
Memory
Networking
CPU
Kafka in the Cloud
Microsoft Azure
Amazon Web Services
Configuring Kafka Clusters
How Many Brokers?
Broker Configuration
OS Tuning
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