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Kafka Up and Running for Network DevOps

Author : Eric Chou

Publisher : Network Automation Nerds, LLC.

Page : 186 pages

File Size : 11,86 MB

Release : 2021-11-11

Category : Computers

ISBN : 1957046015

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Book Description

Today's network is about agility, automation, and continuous improvement. In Kafka Up and Running for Network DevOps, we will be on a journey to learn and set up the hugely popular Apache Kafka data messaging system. Kafka is unique in its principle to treat network data as a continuous flow of information that can adapt to the ever-changing business requirements. Whether you need a system to aggregate log messages, collect metrics, or something else, Kafka can be the reliable, highly redundant system you want. We will begin by learning about the core concepts of Kafka, followed by detailed steps of setting up a Kafka system in a lab environment. For the production environment, we will take advantage of the various public cloud provider offerings. Next, we will set up our Kafka cluster in Amazon Managed Kafka Service to host our Kafka cluster in the AWS cloud. We will also learn about AWS Kinesis, Azure Event Hub, and Google Cloud Put/Sub. Finally, the book will illustrate several use cases of how to integrate Kafka with our network from data enhancement, monitoring, to an event-driven architecture. The Network DevOps Series is a series of books targeted for the next generation of Network Engineers who wants to take advantage of the powerful tools and projects in modern software development and the open-source communities.



Kafka: The Definitive Guide

Author : Gwen Shapira

Publisher : "O'Reilly Media, Inc."

Page : 499 pages

File Size : 40,67 MB

Release : 2021-11-05

Category : Computers

ISBN : 1492043036

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Book Description

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



Kafka: The Definitive Guide

Author : Neha Narkhede

Publisher : "O'Reilly Media, Inc."

Page : 374 pages

File Size : 41,78 MB

Release : 2017-08-31

Category : Computers

ISBN : 1491936118

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Book Description

Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are 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. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems



Effective Kafka

Author : Emil Koutanov

Publisher :

Page : 466 pages

File Size : 12,73 MB

Release : 2020-03-17

Category :

ISBN :

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Book Description

The software architecture landscape has evolved dramatically over the past decade. Microservices have displaced monoliths. Data and applications are increasingly becoming distributed and decentralised. But composing disparate systems is a hard problem. More recently, software practitioners have been rapidly converging on event-driven architecture as a sustainable way of dealing with complexity - integrating systems without increasing their coupling.In Effective Kafka, Emil Koutanov explores the fundamentals of Event-Driven Architecture - using Apache Kafka - the world's most popular and supported open-source event streaming platform.You'll learn: - The fundamentals of event-driven architecture and event streaming platforms- The background and rationale behind Apache Kafka, its numerous potential uses and applications- The architecture and core concepts - the underlying software components, partitioning and parallelism, load-balancing, record ordering and consistency modes- Installation of Kafka and related tooling - using standalone deployments, clusters, and containerised deployments with Docker- Using CLI tools to interact with and administer Kafka classes, as well as publishing data and browsing topics- Using third-party web-based tools for monitoring a cluster and gaining insights into the event streams- Building stream processing applications in Java 11 using off-the-shelf client libraries- Patterns and best-practice for organising the application architecture, with emphasis on maintainability and testability of the resulting code- The numerous gotchas that lurk in Kafka's client and broker configuration, and how to counter them- Theoretical background on distributed and concurrent computing, exploring factors affecting their liveness and safety- Best-practices for running multi-tenanted clusters across diverse engineering teams, how teams collaborate to build complex systems at scale and equitably share the cluster with the aid of quotas- Operational aspects of running Kafka clusters at scale, performance tuning and methods for optimising network and storage utilisation- All aspects of Kafka security -including network segregation, encryption, certificates, authentication and authorization.The coverage is progressively delivered and carefully aimed at giving you a journey-like experience into becoming proficient with Apache Kafka and Event-Driven Architecture. The goal is to get you designing and building applications. And by the conclusion of this book, you will be a confident practitioner and a Kafka evangelist within your organisation - wielding the knowledge necessary to teach others.



Apache Kafka Quick Start Guide

Author : Raúl Estrada

Publisher : Packt Publishing Ltd

Page : 180 pages

File Size : 36,8 MB

Release : 2018-12-27

Category : Computers

ISBN : 1788992253

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Book Description

Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.0 Key FeaturesSolve practical large data and processing challenges with KafkaTackle data processing challenges like late events, windowing, and watermarkingUnderstand real-time streaming applications processing using Schema registry, Kafka connect, Kafka streams, and KSQLBook Description Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the fly. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines. This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment. Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows. What you will learnHow to validate data with KafkaAdd information to existing data flowsGenerate new information through message compositionPerform data validation and versioning with the Schema RegistryHow to perform message Serialization and DeserializationHow to perform message Serialization and DeserializationProcess data streams with Kafka StreamsUnderstand the duality between tables and streams with KSQLWho this book is for This book is for developers who want to quickly master the practical concepts behind Apache Kafka. The audience need not have come across Apache Kafka previously; however, a familiarity of Java or any JVM language will be helpful in understanding the code in this book.



Kafka in Action

Author : Dylan Scott

Publisher : Simon and Schuster

Page : 270 pages

File Size : 15,54 MB

Release : 2022-02-15

Category : Computers

ISBN : 161729523X

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Book Description

Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more. In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.



Kafka Streams in Action

Author : Bill Bejeck

Publisher : Simon and Schuster

Page : 410 pages

File Size : 14,74 MB

Release : 2018-08-29

Category : Computers

ISBN : 1638356025

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Book Description

Summary Kafka Streams in Action teaches you everything you need to know to implement stream processing on data flowing into your Kafka platform, allowing you to focus on getting more from your data without sacrificing time or effort. Foreword by Neha Narkhede, Cocreator of Apache Kafka Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Not all stream-based applications require a dedicated processing cluster. The lightweight Kafka Streams library provides exactly the power and simplicity you need for message handling in microservices and real-time event processing. With the Kafka Streams API, you filter and transform data streams with just Kafka and your application. About the Book Kafka Streams in Action teaches you to implement stream processing within the Kafka platform. In this easy-to-follow book, you'll explore real-world examples to collect, transform, and aggregate data, work with multiple processors, and handle real-time events. You'll even dive into streaming SQL with KSQL! Practical to the very end, it finishes with testing and operational aspects, such as monitoring and debugging. What's inside Using the KStreams API Filtering, transforming, and splitting data Working with the Processor API Integrating with external systems About the Reader Assumes some experience with distributed systems. No knowledge of Kafka or streaming applications required. About the Author Bill Bejeck is a Kafka Streams contributor and Confluent engineer with over 15 years of software development experience. Table of Contents PART 1 - GETTING STARTED WITH KAFKA STREAMS Welcome to Kafka Streams Kafka quicklyPART 2 - KAFKA STREAMS DEVELOPMENT Developing Kafka Streams Streams and state The KTable API The Processor APIPART 3 - ADMINISTERING KAFKA STREAMS Monitoring and performance Testing a Kafka Streams applicationPART 4 - ADVANCED CONCEPTS WITH KAFKA STREAMS Advanced applications with Kafka StreamsAPPENDIXES Appendix A - Additional configuration information Appendix B - Exactly once semantics



Streaming Architecture

Author : Ted Dunning

Publisher : "O'Reilly Media, Inc."

Page : 119 pages

File Size : 22,44 MB

Release : 2016-05-10

Category : Computers

ISBN : 149195390X

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Book Description

More and more data-driven companies are looking to adopt stream processing and streaming analytics. With this concise ebook, you’ll learn best practices for designing a reliable architecture that supports this emerging big-data paradigm. Authors Ted Dunning and Ellen Friedman (Real World Hadoop) help you explore some of the best technologies to handle stream processing and analytics, with a focus on the upstream queuing or message-passing layer. To illustrate the effectiveness of these technologies, this book also includes specific use cases. Ideal for developers and non-technical people alike, this book describes: Key elements in good design for streaming analytics, focusing on the essential characteristics of the messaging layer New messaging technologies, including Apache Kafka and MapR Streams, with links to sample code Technology choices for streaming analytics: Apache Spark Streaming, Apache Flink, Apache Storm, and Apache Apex How stream-based architectures are helpful to support microservices Specific use cases such as fraud detection and geo-distributed data streams Ted Dunning is Chief Applications Architect at MapR Technologies, and active in the open source community. He currently serves as VP for Incubator at the Apache Foundation, as a champion and mentor for a large number of projects, and as committer and PMC member of the Apache ZooKeeper and Drill projects. Ted is on Twitter as @ted_dunning. Ellen Friedman, a committer for the Apache Drill and Apache Mahout projects, is a solutions consultant and well-known speaker and author, currently writing mainly about big data topics. With a PhD in Biochemistry, she has years of experience as a research scientist and has written about a variety of technical topics. Ellen is on Twitter as @Ellen_Friedman.



Data Pipelines with Apache Airflow

Author : Julian de Ruiter

Publisher : Simon and Schuster

Page : 480 pages

File Size : 22,78 MB

Release : 2021-04-05

Category : Computers

ISBN : 1638356831

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Book Description

"An Airflow bible. Useful for all kinds of users, from novice to expert." - Rambabu Posa, Sai Aashika Consultancy Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines. A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, keeping every process along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. Its easy-to-use UI, plug-and-play options, and flexible Python scripting make Airflow perfect for any data management task. About the book Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines. You’ll explore the most common usage patterns, including aggregating multiple data sources, connecting to and from data lakes, and cloud deployment. Part reference and part tutorial, this practical guide covers every aspect of the directed acyclic graphs (DAGs) that power Airflow, and how to customize them for your pipeline’s needs. What's inside Build, test, and deploy Airflow pipelines as DAGs Automate moving and transforming data Analyze historical datasets using backfilling Develop custom components Set up Airflow in production environments About the reader For DevOps, data engineers, machine learning engineers, and sysadmins with intermediate Python skills. About the author Bas Harenslak and Julian de Ruiter are data engineers with extensive experience using Airflow to develop pipelines for major companies. Bas is also an Airflow committer. Table of Contents PART 1 - GETTING STARTED 1 Meet Apache Airflow 2 Anatomy of an Airflow DAG 3 Scheduling in Airflow 4 Templating tasks using the Airflow context 5 Defining dependencies between tasks PART 2 - BEYOND THE BASICS 6 Triggering workflows 7 Communicating with external systems 8 Building custom components 9 Testing 10 Running tasks in containers PART 3 - AIRFLOW IN PRACTICE 11 Best practices 12 Operating Airflow in production 13 Securing Airflow 14 Project: Finding the fastest way to get around NYC PART 4 - IN THE CLOUDS 15 Airflow in the clouds 16 Airflow on AWS 17 Airflow on Azure 18 Airflow in GCP



Python and Terraform Infrastructure as code, standards and practices

Author :

Publisher : jideon francisco marques

Page : 448 pages

File Size : 12,56 MB

Release : 2024-02-23

Category : Computers

ISBN :

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Book Description

How this book is organized: A roadmap I organized this book into three sections with 13 chapters. Part 1 introduces IaC and how you, as an individual, write it. • Chapter 1 defines IaC and its benefits and principles. The chapter explains that the book has examples in Python, run by HashiCorp Terraform, and deployed to Google Cloud Platform (GCP). I also discuss the tools and use cases you’ll encounter in your IaC journey. • Chapter 2 dives into the principle of immutability and how you can migrate existing infrastructure resources to IaC. It also covers the practices of writing clean IaC. • Chapter 3 offers a few patterns for dividing and grouping infrastructure resources into modules. Each pattern includes an example and a list of use cases. • Chapter 4 covers how to manage dependencies among infrastructure resources and modules and decouple them with dependency injection and some common patterns. Part 2 describes how to write and collaborate on IaC as a team. • Chapter 5 organizes the practices and considerations for expressing IaC in different repository structures and sharing it across your team. • Chapter 6 provides an infrastructure testing strategy. It describes each type of test and how to write them for IaC. • Chapter 7 applies continuous delivery to IaC. It covers a high-level view of branching models and how your team can use them to change infrastructure. • Chapter 8 provides techniques to build secure and compliant IaC, including testing and tagging. Part 3 covers how to manage IaC across your company. • Chapter 9 applies immutability to infrastructure changes, including an example for blue-green deployments. • Chapter 10 refactors a large body of IaC to improve its maintainability and mitigate the blast radius of failed changes to one codebase. • Chapter 11 describes reverting IaC and rolling forward changes to the system. • Chapter 12 addresses the use of IaC to manage cloud computing costs. It includes an example for cost estimation of IaC. • Chapter 13 completes the book with practices to manage and update IaC tools. You will find that many concepts build on each other throughout the book, and it may help to read the chapters in order if you have not previously practiced IaC. Otherwise, you can choose the sections that best apply to the challenges you face in your IaC practice.