Learn Apache Mesos

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Learn Apache Mesos

Author : Manuj Aggarwal
Publisher : Packt Publishing Ltd
ISBN 13 : 1789133785
Total Pages : 240 pages
Book Rating : 4.7/5 (891 download)

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Book Synopsis Learn Apache Mesos by : Manuj Aggarwal

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 240 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.

Building Applications on Mesos

Author : David Greenberg
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491926570
Total Pages : 155 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Building Applications on Mesos by : David Greenberg

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 155 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

Big Data SMACK

Author : Raul Estrada
Publisher : Apress
ISBN 13 : 1484221753
Total Pages : 277 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Big Data SMACK by : Raul Estrada

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

Mesos in Action

Author : Roger Ignazio
Publisher : Manning
ISBN 13 : 9781617292927
Total Pages : 0 pages
Book Rating : 4.2/5 (929 download)

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Book Synopsis Mesos in Action by : Roger Ignazio

Download or read book Mesos in Action written by Roger Ignazio and published by Manning. This book was released on 2016-05-23 with total page 0 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

Apache Mesos Cookbook

Author : David Blomquist
Publisher :
ISBN 13 : 9781785884627
Total Pages : 247 pages
Book Rating : 4.8/5 (846 download)

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Book Synopsis Apache Mesos Cookbook by : David Blomquist

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.

Mastering Spark with R

Author : Javier Luraschi
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492046329
Total Pages : 296 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Mastering Spark with R by : Javier Luraschi

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

Learning Apache Spark 2

Author : Muhammad Asif Abbasi
Publisher : Packt Publishing Ltd
ISBN 13 : 1785889583
Total Pages : 349 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Learning Apache Spark 2 by : Muhammad Asif Abbasi

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.

Fast Data Processing Systems with SMACK Stack

Author : Raul Estrada
Publisher : Packt Publishing Ltd
ISBN 13 : 1786468069
Total Pages : 371 pages
Book Rating : 4.7/5 (864 download)

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Book Synopsis Fast Data Processing Systems with SMACK Stack by : Raul Estrada

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

Mastering Mesos

Author : Dipa Dubhashi
Publisher : Packt Publishing Ltd
ISBN 13 : 1785885375
Total Pages : 352 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Mastering Mesos by : Dipa Dubhashi

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.

Learning Spark

Author : Jules S. Damji
Publisher : O'Reilly Media
ISBN 13 : 1492050016
Total Pages : 400 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Learning Spark by : Jules S. Damji

Download or read book Learning Spark written by Jules S. Damji and published by O'Reilly Media. This book was released on 2020-07-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow

Spark: The Definitive Guide

Author : Bill Chambers
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491912294
Total Pages : 594 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Spark: The Definitive Guide by : Bill Chambers

Download or read book Spark: The Definitive Guide written by Bill Chambers and published by "O'Reilly Media, Inc.". This book was released on 2018-02-08 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

Learning Spark

Author : Holden Karau
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449359051
Total Pages : 289 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Learning Spark by : Holden Karau

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

Apache Mesos Essentials

Author : Dharmesh Kakadia
Publisher :
ISBN 13 : 9781783288762
Total Pages : 230 pages
Book Rating : 4.2/5 (887 download)

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Book Synopsis Apache Mesos Essentials by : Dharmesh Kakadia

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.

Learning Apache Apex

Author : Thomas Weise
Publisher : Packt Publishing Ltd
ISBN 13 : 1788294114
Total Pages : 282 pages
Book Rating : 4.7/5 (882 download)

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Book Synopsis Learning Apache Apex by : Thomas Weise

Download or read book Learning Apache Apex written by Thomas Weise and published by Packt Publishing Ltd. This book was released on 2017-11-30 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing and writing a real-time streaming publication with Apache Apex About This Book Get a clear, practical approach to real-time data processing Program Apache Apex streaming applications This book shows you Apex integration with the open source Big Data ecosystem Who This Book Is For This book assumes knowledge of application development with Java and familiarity with distributed systems. Familiarity with other real-time streaming frameworks is not required, but some practical experience with other big data processing utilities might be helpful. What You Will Learn Put together a functioning Apex application from scratch Scale an Apex application and configure it for optimal performance Understand how to deal with failures via the fault tolerance features of the platform Use Apex via other frameworks such as Beam Understand the DevOps implications of deploying Apex In Detail Apache Apex is a next-generation stream processing framework designed to operate on data at large scale, with minimum latency, maximum reliability, and strict correctness guarantees. Half of the book consists of Apex applications, showing you key aspects of data processing pipelines such as connectors for sources and sinks, and common data transformations. The other half of the book is evenly split into explaining the Apex framework, and tuning, testing, and scaling Apex applications. Much of our economic world depends on growing streams of data, such as social media feeds, financial records, data from mobile devices, sensors and machines (the Internet of Things - IoT). The projects in the book show how to process such streams to gain valuable, timely, and actionable insights. Traditional use cases, such as ETL, that currently consume a significant chunk of data engineering resources are also covered. The final chapter shows you future possibilities emerging in the streaming space, and how Apache Apex can contribute to it. Style and approach This book is divided into two major parts: first it explains what Apex is, what its relevant parts are, and how to write well-built Apex applications. The second part is entirely application-driven, walking you through Apex applications of increasing complexity.

Continuous Delivery with Docker and Jenkins

Author : Rafal Leszko
Publisher : Packt Publishing Ltd
ISBN 13 : 1787126145
Total Pages : 326 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Continuous Delivery with Docker and Jenkins by : Rafal Leszko

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.

Hands-On Deep Learning with Apache Spark

Author : Guglielmo Iozzia
Publisher : Packt Publishing Ltd
ISBN 13 : 1788999703
Total Pages : 310 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On Deep Learning with Apache Spark by : Guglielmo Iozzia

Download or read book Hands-On Deep Learning with Apache Spark written by Guglielmo Iozzia and published by Packt Publishing Ltd. This book was released on 2019-01-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speed up the design and implementation of deep learning solutions using Apache Spark Key FeaturesExplore the world of distributed deep learning with Apache SparkTrain neural networks with deep learning libraries such as BigDL and TensorFlowDevelop Spark deep learning applications to intelligently handle large and complex datasetsBook Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learnUnderstand the basics of deep learningSet up Apache Spark for deep learningUnderstand the principles of distribution modeling and different types of neural networksObtain an understanding of deep learning algorithmsDiscover textual analysis and deep learning with SparkUse popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and KerasExplore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

Learning Apache OpenWhisk

Author : Michele Sciabarrà
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492046124
Total Pages : 387 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Learning Apache OpenWhisk by : Michele Sciabarrà

Download or read book Learning Apache OpenWhisk written by Michele Sciabarrà and published by "O'Reilly Media, Inc.". This book was released on 2019-07-03 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serverless computing greatly simplifies software development. Your team can focus solely on your application while the cloud provider manages the servers you need. This practical guide shows you step-by-step how to build and deploy complex applications in a flexible multicloud, multilanguage environment using Apache OpenWhisk. You’ll learn how this platform enables you to pursue a vendor-independent approach using preconfigured containers, microservices, and Kubernetes as your cloud operating system. Michele Sciabarrà demonstrates how to build a serverless application using classical design patterns and the programming language or languages that best fit your task. You’ll start by building a simple serverless application hands-on before diving into the more complex aspects of the OpenWhisk platform. Examine how OpenWhisk’s serverless architecture works, including the use of packages, actions, sequences, triggers, rules, and feeds Learn how OpenWhisk compares to existing architectures, such as Java Enterprise Edition Manipulate OpenWhisk features using the command-line interface or a JavaScript API Design applications using common Gang of Four design patterns Use architectural design patterns such as model-view-controller to combine several OpenWhisk actions Learn how to test and debug your code in a serverless environment