Download or read book Learn Apache Mesos written by Manuj Aggarwal and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scale applications with high availability and optimized resource management across data centers Key FeaturesCreate clusters and perform scheduling, logging, and resource administration with MesosExplore practical examples of managing complex clusters at scale with real-world dataWrite native Mesos frameworks with PythonBook Description Apache Mesos is an open source cluster manager that provides efficient resource isolation and sharing across distributed applications or frameworks. This book will help you build a strong foundation of Mesos' capabilities along with practical examples to support the concepts explained throughout the book. Learn Apache Mesos dives straight into how Mesos works. You will be introduced to the distributed system and its challenges and then learn how you can use Mesos and its framework to solve data problems. You will also gain a full understanding of Mesos' internal mechanisms and get equipped to use Mesos and develop applications. Furthermore, this book lets you explore all the steps required to create highly available clusters and build your own Mesos frameworks. You will also cover application deployment and monitoring. By the end of this book, you will have learned how to use Mesos to make full use of machines and how to simplify data center maintenance. What you will learnDeploy and monitor a Mesos clusterSet up servers on AWS to deploy Mesos componentsExplore Mesos resource scheduling and the allocation moduleDeploy Docker-based services and applications using Mesos MarathonConfigure and use SSL to protect crucial endpoints of your Mesos clusterDebug and troubleshoot services and workloads on a Mesos clusterWho this book is for This book is for DevOps and data engineers and administrators who work with large data clusters. You’ll also find this book useful if you have experience working with virtualization, databases, and platforms such as Hadoop and Spark. Some experience in database administration and design will help you get the most out of this book.

Download or read book Mesos in Action written by Roger Ignazio and published by Simon and Schuster. This book was released on 2016-05-02 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Mesos in Action introduces readers to the Apache Mesos cluster manager and the concept of application-centric infrastructure. Filled with helpful figures and hands-on instructions, this book guides you from your first steps creating a highly-available Mesos cluster through deploying applications in production and writing native Mesos frameworks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Modern datacenters are complex environments, and when you throw Docker and other container-based systems into the mix, there’s a great need to simplify. Mesos is an open source cluster management platform that transforms the whole datacenter into a single pool of compute, memory, and storage resources that you can allocate, automate, and scale as if you’re working with a single supercomputer. About the Book Mesos in Action introduces readers to the Apache Mesos cluster manager and the concept of application-centric infrastructure. Filled with helpful figures and hands-on instructions, this book guides you from your first steps creating a highly-available Mesos cluster through deploying applications in production and writing native Mesos frameworks. You’ll learn how to scale to thousands of nodes, while providing resource isolation between processes using Linux and Docker containers. You’ll also learn practical techniques for deploying applications using popular key frameworks. What’s Inside Spinning up your first Mesos cluster Scheduling, resource administration, and logging Deploying containerized applications with Marathon, Chronos, and Aurora Writing Mesos frameworks using Python About the Reader Readers need to be familiar with the core ideas of datacenter administration and need a basic knowledge of Python or a similar programming language. About the Author Roger Ignazio is an experienced systems engineer with a focus on distributed, fault-tolerant, and scalable infrastructure. He is currently a technical lead at Mesosphere. Table of Contents PART 1 HELLO, MESOS Introducing Mesos Managing datacenter resources with Mesos PART 2 CORE MESOS Setting up Mesos Mesos fundamentals Logging and debugging Mesos in production PART 3 RUNNING ON MESOS Deploying applications with MarathoN Managing scheduled tasks with Chronos Deploying applications and managing scheduled tasks with Aurora Developing a framework

Download or read book Building Applications on Mesos written by David Greenberg and published by "O'Reilly Media, Inc.". This book was released on 2015-12-07 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can Apache Mesos make a difference in your organization? With this practical guide, you’ll learn how this cluster manager directs your datacenter’s resources, and provides real time APIs for interacting with (and developing for) the entire cluster. You’ll learn how to use Mesos as a deployment system, like Ansible or Chef, and as an execution platform for building and hosting higher-level applications, like Hadoop. Author David Greenberg shows you how Mesos manages your entire datacenter as a single logical entity, eliminating the need to assign fixed sets of machines to applications. You’ll quickly discover why Mesos is the ultimate DevOps tool. Understand Mesos architecture, and learn how it manages CPU, memory, and other resources across a cluster Build an application on top of Mesos with Marathon, a platform for hosting services on Mesos Create new, production-ready frameworks for Mesos Write a custom executor to provide richer interaction between the Mesos scheduler and workers Dive into advanced topics, including the reconciliation process, Docker integration, dynamic reservations, and persistent volumes Learn about today’s Mesos initiatives that will likely become tomorrow’s features

Download or read book Big Data SMACK written by Raul Estrada and published by Apress. This book was released on 2016-09-29 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to integrate full-stack open source big data architecture and to choose the correct technology—Scala/Spark, Mesos, Akka, Cassandra, and Kafka—in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large data sets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explains each of the full-stack technologies and, more importantly, how to best integrate them. It provides detailed coverage of the practical benefits of these technologies and incorporates real-world examples in every situation. This book focuses on the problems and scenarios solved by the architecture, as well as the solutions provided by every technology. It covers the six main concepts of big data architecture and how integrate, replace, and reinforce every layer: The language: Scala The engine: Spark (SQL, MLib, Streaming, GraphX) The container: Mesos, Docker The view: Akka The storage: Cassandra The message broker: Kafka What You Will Learn: Make big data architecture without using complex Greek letter architectures Build a cheap but effective cluster infrastructure Make queries, reports, and graphs that business demands Manage and exploit unstructured and No-SQL data sources Use tools to monitor the performance of your architecture Integrate all technologies and decide which ones replace and which ones reinforce Who This Book Is For: Developers, data architects, and data scientists looking to integrate the most successful big data open stack architecture and to choose the correct technology in every layer

Download or read book Apache Mesos Basics written by Edward Campbell and published by Createspace Independent Publishing Platform. This book was released on 2017-06-28 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an exploration of Apache Mesos. The author aims to help you learn how to use Apache Mesos. The first part of the book helps you learn what Apache Mesos is. The various components of Apache Mesos are discussed, along with their different purposes. You will also learn how to setup the Mesos environment before you can begin to use it. Authentication and Authorization are very important aspects in Mesos. Authentication determines the users who are able to access Mesos while Authorization determines the resources one can use when using it. This book helps you understand how these processes happen and how you can modify them to suit your needs. Apache Mesos supports the concept of use of containers. This book helps you understand how this is done. Under normal circumstances, tasks will misbehave or fail. This means that we should come up with a way of checking the health of various tasks. This book helps you understand how to do this in Apache Mesos. The concept of framework rate limiting is also explored in this book, thus, you will learn how it works. You are also guided on how to write your own Apache Mesos frameworks by the use of Java programming language. The following topics are discussed in this book: - Getting Started with Apache Mesos - Authentication and Authorization - Container Image Support in Mesos Containerizer - Task Health Checking - Framework Rate Limiting - Building an Apache Mesos Framework - Maintenance Primitives

Download or read book Mastering Mesos written by Dipa Dubhashi and published by Packt Publishing Ltd. This book was released on 2016-05-26 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ultimate guide to managing, building, and deploying large-scale clusters with Apache Mesos About This Book Master the architecture of Mesos and intelligently distribute your task across clusters of machines Explore a wide range of tools and platforms that Mesos works with This real-world comprehensive and robust tutorial will help you become an expert Who This Book Is For The book aims to serve DevOps engineers and system administrators who are familiar with the basics of managing a Linux system and its tools What You Will Learn Understand the Mesos architecture Manually spin up a Mesos cluster on a distributed infrastructure Deploy a multi-node Mesos cluster using your favorite DevOps See the nuts and bolts of scheduling, service discovery, failure handling, security, monitoring, and debugging in an enterprise-grade, production cluster deployment Use Mesos to deploy big data frameworks, containerized applications, or even custom build your own applications effortlessly In Detail Apache Mesos is open source cluster management software that provides efficient resource isolations and resource sharing distributed applications or frameworks. This book will take you on a journey to enhance your knowledge from amateur to master level, showing you how to improve the efficiency, management, and development of Mesos clusters. The architecture is quite complex and this book will explore the difficulties and complexities of working with Mesos. We begin by introducing Mesos, explaining its architecture and functionality. Next, we provide a comprehensive overview of Mesos features and advanced topics such as high availability, fault tolerance, scaling, and efficiency. Furthermore, you will learn to set up multi-node Mesos clusters on private and public clouds. We will also introduce several Mesos-based scheduling and management frameworks or applications to enable the easy deployment, discovery, load balancing, and failure handling of long-running services. Next, you will find out how a Mesos cluster can be easily set up and monitored using the standard deployment and configuration management tools. This advanced guide will show you how to deploy important big data processing frameworks such as Hadoop, Spark, and Storm on Mesos and big data storage frameworks such as Cassandra, Elasticsearch, and Kafka. Style and approach This advanced guide provides a detailed step-by-step account of deploying a Mesos cluster. It will demystify the concepts behind Mesos.

Download or read book Apache Mesos Essentials written by Dharmesh Kakadia and published by . This book was released on 2015-06-29 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for developers and operators who want to build and run scalable and fault-tolerant applications leveraging Apache Mesos. A basic knowledge of programming with some fundamentals of Linux is a prerequisite.

Download or read book Apache Mesos Cookbook written by David Blomquist and published by . This book was released on 2017-04-28 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 50 recipes on the core features of Apache Mesos and running big data frameworks in MesosAbout This Book* Learn to install and configure Mesos to suit the needs of your organization* Follow step-by-step instructions to deploy application frameworks on top of Mesos, saving you many hours of research and trial and error* Use this practical guide packed with powerful recipes to implement Mesos and easily integrate it with other application frameworksWho This Book Is ForThis book is for system administrators, engineers, and big data programmers. Basic experience with big data technologies such as Hadoop or Spark would be useful but is not essential. A working knowledge of Apache Mesos is expected.What you will learn* Set up Mesos on different operating systems* Use the Marathon and Chronos frameworks to manage multiple applications* Work with Mesos and Docker* Integrate Mesos with Spark and other big data frameworks* Use networking features in Mesos for effective communication between containers* Configure Mesos for high availability using Zookeeper* Secure your Mesos clusters with SASL and Authorization ACLs* Solve everyday problems and discover the best practicesIn DetailApache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks.The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper.Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We'll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs.You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch.Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos.

Download or read book Apache Mesos Cookbook written by David Blomquist and published by Packt Publishing Ltd. This book was released on 2017-08-02 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos About This Book Learn to install and configure Mesos to suit the needs of your organization Follow step-by-step instructions to deploy application frameworks on top of Mesos, saving you many hours of research and trial and error Use this practical guide packed with powerful recipes to implement Mesos and easily integrate it with other application frameworks Who This Book Is For This book is for system administrators, engineers, and big data programmers. Basic experience with big data technologies such as Hadoop or Spark would be useful but is not essential. A working knowledge of Apache Mesos is expected. What You Will Learn Set up Mesos on different operating systems Use the Marathon and Chronos frameworks to manage multiple applications Work with Mesos and Docker Integrate Mesos with Spark and other big data frameworks Use networking features in Mesos for effective communication between containers Configure Mesos for high availability using Zookeeper Secure your Mesos clusters with SASL and Authorization ACLs Solve everyday problems and discover the best practices In Detail Apache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks. The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper. Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We'll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs. You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch. Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos. Style and approach This step-by-step guide is packed with powerful recipes on using Apache Mesos and shows its integration with containers and big data frameworks.

Download or read book Complete Guide to Open Source Big Data Stack written by Michael Frampton and published by Apress. This book was released on 2018-01-18 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You’ll Learn Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing Who This Book Is For Developers, architects, IT project managers, database administrators, and others charged with developing or supporting a big data system. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.

Download or read book Learning Apache Spark 2 written by Muhammad Asif Abbasi and published by Packt Publishing Ltd. This book was released on 2017-03-28 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics About This Book Exclusive guide that covers how to get up and running with fast data processing using Apache Spark Explore and exploit various possibilities with Apache Spark using real-world use cases in this book Want to perform efficient data processing at real time? This book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. Basic familiarity with Java or Scala will be helpful. The assumption is that readers will be from a mixed background, but would be typically people with background in engineering/data science with no prior Spark experience and want to understand how Spark can help them on their analytics journey. What You Will Learn Get an overview of big data analytics and its importance for organizations and data professionals Delve into Spark to see how it is different from existing processing platforms Understand the intricacies of various file formats, and how to process them with Apache Spark. Realize how to deploy Spark with YARN, MESOS or a Stand-alone cluster manager. Learn the concepts of Spark SQL, SchemaRDD, Caching and working with Hive and Parquet file formats Understand the architecture of Spark MLLib while discussing some of the off-the-shelf algorithms that come with Spark. Introduce yourself to the deployment and usage of SparkR. Walk through the importance of Graph computation and the graph processing systems available in the market Check the real world example of Spark by building a recommendation engine with Spark using ALS. Use a Telco data set, to predict customer churn using Random Forests. In Detail Spark juggernaut keeps on rolling and getting more and more momentum each day. Spark provides key capabilities in the form of Spark SQL, Spark Streaming, Spark ML and Graph X all accessible via Java, Scala, Python and R. Deploying the key capabilities is crucial whether it is on a Standalone framework or as a part of existing Hadoop installation and configuring with Yarn and Mesos. The next part of the journey after installation is using key components, APIs, Clustering, machine learning APIs, data pipelines, parallel programming. It is important to understand why each framework component is key, how widely it is being used, its stability and pertinent use cases. Once we understand the individual components, we will take a couple of real life advanced analytics examples such as 'Building a Recommendation system', 'Predicting customer churn' and so on. The objective of these real life examples is to give the reader confidence of using Spark for real-world problems. Style and approach With the help of practical examples and real-world use cases, this guide will take you from scratch to building efficient data applications using Apache Spark. You will learn all about this excellent data processing engine in a step-by-step manner, taking one aspect of it at a time. This highly practical guide will include how to work with data pipelines, dataframes, clustering, SparkSQL, parallel programming, and such insightful topics with the help of real-world use cases.

Download or read book Mastering Spark with R written by Javier Luraschi and published by "O'Reilly Media, Inc.". This book was released on 2019-10-07 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions

Download or read book Apache Mesos The Ultimate Step By Step Guide written by Gerardus Blokdyk and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apache Mesos The Ultimate Step-By-Step Guide.

Download or read book Learning Spark written by Holden Karau and published by "O'Reilly Media, Inc.". This book was released on 2015-01-28 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm Learn how to deploy interactive, batch, and streaming applications Connect to data sources including HDFS, Hive, JSON, and S3 Master advanced topics like data partitioning and shared variables

Download or read book Fast Data Processing Systems with SMACK Stack written by Raul Estrada and published by Packt Publishing Ltd. This book was released on 2016-12-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles! About This Book This highly practical guide shows you how to use the best of the big data technologies to solve your response-critical problems Learn the art of making cheap-yet-effective big data architecture without using complex Greek-letter architectures Use this easy-to-follow guide to build fast data processing systems for your organization Who This Book Is For If you are a developer, data architect, or a data scientist looking for information on how to integrate the Big Data stack architecture and how to choose the correct technology in every layer, this book is what you are looking for. What You Will Learn Design and implement a fast data Pipeline architecture Think and solve programming challenges in a functional way with Scala Learn to use Akka, the actors model implementation for the JVM Make on memory processing and data analysis with Spark to solve modern business demands Build a powerful and effective cluster infrastructure with Mesos and Docker Manage and consume unstructured and No-SQL data sources with Cassandra Consume and produce messages in a massive way with Kafka In Detail SMACK is an open source full stack for big data architecture. It is a combination of Spark, Mesos, Akka, Cassandra, and Kafka. This stack is the newest technique developers have begun to use to tackle critical real-time analytics for big data. This highly practical guide will teach you how to integrate these technologies to create a highly efficient data analysis system for fast data processing. We'll start off with an introduction to SMACK and show you when to use it. First you'll get to grips with functional thinking and problem solving using Scala. Next you'll come to understand the Akka architecture. Then you'll get to know how to improve the data structure architecture and optimize resources using Apache Spark. Moving forward, you'll learn how to perform linear scalability in databases with Apache Cassandra. You'll grasp the high throughput distributed messaging systems using Apache Kafka. We'll show you how to build a cheap but effective cluster infrastructure with Apache Mesos. Finally, you will deep dive into the different aspect of SMACK using a few case studies. By the end of the book, you will be able to integrate all the components of the SMACK stack and use them together to achieve highly effective and fast data processing. Style and approach With the help of various industry examples, you will learn about the full stack of big data architecture, taking the important aspects in every technology. You will learn how to integrate the technologies to build effective systems rather than getting incomplete information on single technologies. You will learn how various open source technologies can be used to build cheap and fast data processing systems with the help of various industry examples

Download or read book Continuous Delivery with Docker and Jenkins written by Rafal Leszko and published by Packt Publishing Ltd. This book was released on 2017-08-24 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the combination of Docker and Jenkins in order to enhance the DevOps workflow About This Book Build reliable and secure applications using Docker containers. Create a complete Continuous Delivery pipeline using Docker, Jenkins, and Ansible. Deliver your applications directly on the Docker Swarm cluster. Create more complex solutions using multi-containers and database migrations. Who This Book Is For This book is indented to provide a full overview of deep learning. From the beginner in deep learning and artificial intelligence to the data scientist who wants to become familiar with Theano and its supporting libraries, or have an extended understanding of deep neural nets. Some basic skills in Python programming and computer science will help, as well as skills in elementary algebra and calculus. What You Will Learn Get to grips with docker fundamentals and how to dockerize an application for the Continuous Delivery process Configure Jenkins and scale it using Docker-based agents Understand the principles and the technical aspects of a successful Continuous Delivery pipeline Create a complete Continuous Delivery process using modern tools: Docker, Jenkins, and Ansible Write acceptance tests using Cucumber and run them in the Docker ecosystem using Jenkins Create multi-container applications using Docker Compose Managing database changes inside the Continuous Delivery process and understand effective frameworks such as Cucumber and Flyweight Build clustering applications with Jenkins using Docker Swarm Publish a built Docker image to a Docker Registry and deploy cycles of Jenkins pipelines using community best practices In Detail The combination of Docker and Jenkins improves your Continuous Delivery pipeline using fewer resources. It also helps you scale up your builds, automate tasks and speed up Jenkins performance with the benefits of Docker containerization. This book will explain the advantages of combining Jenkins and Docker to improve the continuous integration and delivery process of app development. It will start with setting up a Docker server and configuring Jenkins on it. It will then provide steps to build applications on Docker files and integrate them with Jenkins using continuous delivery processes such as continuous integration, automated acceptance testing, and configuration management. Moving on you will learn how to ensure quick application deployment with Docker containers along with scaling Jenkins using Docker Swarm. Next, you will get to know how to deploy applications using Docker images and testing them with Jenkins. By the end of the book, you will be enhancing the DevOps workflow by integrating the functionalities of Docker and Jenkins. Style and approach The book is aimed at DevOps Engineers, developers and IT Operations who want to enhance the DevOps culture using Docker and Jenkins.

Download or read book Microservices Deployment Cookbook written by Vikram Murugesan and published by Packt Publishing Ltd. This book was released on 2017-01-31 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master over 60 recipes to help you deliver complete, scalable, microservice-based solutions and see the improved business results immediately About This Book Adopt microservices-based architecture and deploy it at scale Build your complete microservice architecture using different recipes for different solutions Identify specific tools for specific scenarios and deliver immediate business results, correlate use cases, and adopt them in your team and organization Who This Book Is For This book is for developers, ops, and DevOps professionals who would like to put microservices to work and improve products, services, and operations. Those looking to build and deploy microservices will find this book useful, as well as managers and people at CXO level looking to adopt microservices in their organization. Prior knowledge of Java is expected. No prior knowledge of microservices is assumed. What You Will Learn Build microservices using Spring Boot, Wildfly Swarm, Dropwizard, and SparkJava Containerize your microservice using Docker Deploy microservices using Mesos/Marathon and Kubernetes Implement service discovery and load balancing using Zookeeper, Consul, and Nginx Monitor microservices using Graphite and Grafana Write stream programs with Kafka Streams and Spark Aggregate and manage logs using Kafka Get introduced to DC/OS, Docker Swarm, and YARN In Detail This book will help any team or organization understand, deploy, and manage microservices at scale. It is driven by a sample application, helping you gradually build a complete microservice-based ecosystem. Rather than just focusing on writing a microservice, this book addresses various other microservice-related solutions: deployments, clustering, load balancing, logging, streaming, and monitoring. The initial chapters offer insights into how web and enterprise apps can be migrated to scalable microservices. Moving on, you'll see how to Dockerize your application so that it is ready to be shipped and deployed. We will look at how to deploy microservices on Mesos and Marathon and will also deploy microservices on Kubernetes. Next, you will implement service discovery and load balancing for your microservices. We'll also show you how to build asynchronous streaming systems using Kafka Streams and Apache Spark. Finally, we wind up by aggregating your logs in Kafka, creating your own metrics, and monitoring the metrics for the microservice. Style and approach This book follows a recipe-driven approach and shows you how to plug and play with all the various pieces, putting them together to build a complete scalable microservice ecosystem. You do not need to study the chapters in order, as you can directly refer to the content you need for your situation.