Apache Mesos Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1785880934
Total Pages : 141 pages
Book Rating : 4.7/5 (858 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 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.

Apache Mesos Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1785880934
Total Pages : 141 pages
Book Rating : 4.7/5 (858 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 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.

Learn Apache Mesos

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Publisher : Packt Publishing Ltd
ISBN 13 : 1789133785
Total Pages : 248 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 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.

Docker Cookbook

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491919779
Total Pages : 359 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Docker Cookbook by : Sébastien Goasguen

Download or read book Docker Cookbook written by Sébastien Goasguen and published by "O'Reilly Media, Inc.". This book was released on 2015-11-04 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you're deploying applications on-premise or in the cloud, this cookbook is for developers, operators, and IT professionals who need practical solutions for using Docker. The recipes in this book will help developers go from zero knowledge to distributed applications packaged and deployed within a couple of chapters. IT professionals will be able to use this cookbook to solve everyday problems, as well as create, run, share, and deploy Docker images quickly. Operators will learn and understand what developers are excited about and start to adopt the tools that will change the way they work.--

Apache Spark 2.x Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1787127516
Total Pages : 288 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Apache Spark 2.x Cookbook by : Rishi Yadav

Download or read book Apache Spark 2.x Cookbook written by Rishi Yadav and published by Packt Publishing Ltd. This book was released on 2017-05-31 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 70 recipes to help you use Apache Spark as your single big data computing platform and master its libraries About This Book This book contains recipes on how to use Apache Spark as a unified compute engine Cover how to connect various source systems to Apache Spark Covers various parts of machine learning including supervised/unsupervised learning & recommendation engines Who This Book Is For This book is for data engineers, data scientists, and those who want to implement Spark for real-time data processing. Anyone who is using Spark (or is planning to) will benefit from this book. The book assumes you have a basic knowledge of Scala as a programming language. What You Will Learn Install and configure Apache Spark with various cluster managers & on AWS Set up a development environment for Apache Spark including Databricks Cloud notebook Find out how to operate on data in Spark with schemas Get to grips with real-time streaming analytics using Spark Streaming & Structured Streaming Master supervised learning and unsupervised learning using MLlib Build a recommendation engine using MLlib Graph processing using GraphX and GraphFrames libraries Develop a set of common applications or project types, and solutions that solve complex big data problems In Detail While Apache Spark 1.x gained a lot of traction and adoption in the early years, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building blocks to build better, faster, smarter, and more accessible big data applications. This book uncovers all these features in the form of structured recipes to analyze and mature large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will learn to set up development environments. Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark. Last but not least, the final few chapters delve deeper into the concepts of graph processing using GraphX, securing your implementations, cluster optimization, and troubleshooting. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand Spark 2.x's real-time processing capabilities and deploy scalable big data solutions. This is a valuable resource for data scientists and those working on large-scale data projects.

Apache Kafka 1.0 Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 178728218X
Total Pages : 243 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Apache Kafka 1.0 Cookbook by : Raúl Estrada

Download or read book Apache Kafka 1.0 Cookbook written by Raúl Estrada and published by Packt Publishing Ltd. This book was released on 2017-12-22 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplify real-time data processing by leveraging the power of Apache Kafka 1.0 About This Book Use Kafka 1.0 features such as Confluent platforms and Kafka streams to build efficient streaming data applications to handle and process your data Integrate Kafka with other Big Data tools such as Apache Hadoop, Apache Spark, and more Hands-on recipes to help you design, operate, maintain, and secure your Apache Kafka cluster with ease Who This Book Is For This book is for developers and Kafka administrators who are looking for quick, practical solutions to problems encountered while operating, managing or monitoring Apache Kafka. If you are a developer, some knowledge of Scala or Java will help, while for administrators, some working knowledge of Kafka will be useful. What You Will Learn Install and configure Apache Kafka 1.0 to get optimal performance Create and configure Kafka Producers and Consumers Operate your Kafka clusters efficiently by implementing the mirroring technique Work with the new Confluent platform and Kafka streams, and achieve high availability with Kafka Monitor Kafka using tools such as Graphite and Ganglia Integrate Kafka with third-party tools such as Elasticsearch, Logstash, Apache Hadoop, Apache Spark, and more In Detail Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite. If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have. Style and approach Following a cookbook recipe-based approach, we'll teach you how to solve everyday difficulties and struggles you encounter using Kafka through hands-on examples.

Mastering Mesos

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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.

Apache Spark for Data Science Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1785288806
Total Pages : 388 pages
Book Rating : 4.7/5 (852 download)

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Book Synopsis Apache Spark for Data Science Cookbook by : Padma Priya Chitturi

Download or read book Apache Spark for Data Science Cookbook written by Padma Priya Chitturi and published by Packt Publishing Ltd. This book was released on 2016-12-22 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over insightful 90 recipes to get lightning-fast analytics with Apache Spark About This Book Use Apache Spark for data processing with these hands-on recipes Implement end-to-end, large-scale data analysis better than ever before Work with powerful libraries such as MLLib, SciPy, NumPy, and Pandas to gain insights from your data Who This Book Is For This book is for novice and intermediate level data science professionals and data analysts who want to solve data science problems with a distributed computing framework. Basic experience with data science implementation tasks is expected. Data science professionals looking to skill up and gain an edge in the field will find this book helpful. What You Will Learn Explore the topics of data mining, text mining, Natural Language Processing, information retrieval, and machine learning. Solve real-world analytical problems with large data sets. Address data science challenges with analytical tools on a distributed system like Spark (apt for iterative algorithms), which offers in-memory processing and more flexibility for data analysis at scale. Get hands-on experience with algorithms like Classification, regression, and recommendation on real datasets using Spark MLLib package. Learn about numerical and scientific computing using NumPy and SciPy on Spark. Use Predictive Model Markup Language (PMML) in Spark for statistical data mining models. In Detail Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark's selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark's data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work. Style and approach This book contains a comprehensive range of recipes designed to help you learn the fundamentals and tackle the difficulties of data science. This book outlines practical steps to produce powerful insights into Big Data through a recipe-based approach.

Vagrant Virtual Development Environment Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1784391085
Total Pages : 250 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis Vagrant Virtual Development Environment Cookbook by : Chad Thompson

Download or read book Vagrant Virtual Development Environment Cookbook written by Chad Thompson and published by Packt Publishing Ltd. This book was released on 2015-02-26 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a software developer or administrator who wishes to create simple, reusable environments using Vagrant, this book is the perfect choice for you. Whether you are a system administrator with extensive experience in virtualization or a developer wishing to create development scripts for cloud deployment, you will find easy-to-follow recipes and techniques in this book that will allow you to create robust and reproducible virtual environments.

Docker Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1788625986
Total Pages : 344 pages
Book Rating : 4.7/5 (886 download)

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Book Synopsis Docker Cookbook by : Ken Cochrane

Download or read book Docker Cookbook written by Ken Cochrane and published by Packt Publishing Ltd. This book was released on 2018-08-31 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage Docker to deploying software at scale Key Features Leverage practical examples to manage containers efficiently Integrate with orchestration tools such as Kubernetes for controlled deployments Learn to implement best practices on improving efficiency and security of containers Book Description Docker is an open source platform for building, shipping, managing, and securing containers. Docker has become the tool of choice for people willing to work with containers. Since the market is moving toward containerization, Docker will definitely have a big role to play in the future tech market. This book starts with setting up Docker in different environment, and helps you learn how to work with Docker images. Then, you will take a deep dive into network and data management for containers. The book explores the RESTful APIs provided by Docker to perform different actions, such as image/container operations. The book then explores logs and troubleshooting Docker to solve issues and bottlenecks. You will gain an understanding of Docker use cases, orchestration, security, ecosystems, and hosting platforms to make your applications easy to deploy, build, and collaborate on. The book covers the new features of Docker 18.xx (or later), such as working with AWS and Azure, Docker Engine, Docker Swarm, Docker Compose, and so on. By the end of this book, you will have gained hands-on experience of finding quick solutions to different problems encountered while working with Docker. What you will learn Install Docker on various platforms Work with Docker images and containers Container networking and data sharing Docker APIs and language bindings Various PaaS solutions for Docker Implement container orchestration using Docker Swarm and Kubernetes Container security Docker on various clouds Who this book is for Book is targeted towards developers, system administrators, and DevOps engineers who want to use Docker in his/her development, QA, or production environments. It is expected that the reader has basic Linux/Unix skills such as installing packages, editing files, managing services, and so on. Any experience in virtualization technologies such as KVM, XEN, and VMware will be an added advantage

Microservices Deployment Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1786461315
Total Pages : 374 pages
Book Rating : 4.7/5 (864 download)

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Book Synopsis Microservices Deployment Cookbook by : Vikram Murugesan

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.

Node Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1785881248
Total Pages : 654 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Node Cookbook by : David Mark Clements

Download or read book Node Cookbook written by David Mark Clements and published by Packt Publishing Ltd. This book was released on 2017-07-31 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 60 high-quality recipes covering debugging, security, performance, microservices, web frameworks, databases, deployment and more; rewritten for Node 4, 6, and 8. About This Book Actionable recipes across the full spectrum of Node.js development Cutting edge techniques and tools for measuring and improving performance Best practices for creating readily-scalable production systems Who This Book Is For If you have good knowledge of JavaScript and want to build fast, efficient, scalable client-server solutions, then this book is for you. Some experience with Node.js is assumed to get the most out of this book. If working from a beginner level Node Cookbook 2nd Edition is recommended as a primer for Node Cookbook 3rd Edition. What You Will Learn Debug Node.js programs Write and publish your own Node.js modules Detailed coverage of Node.js core API's Use web frameworks such as Express, Hapi and Koa for accelerated web application development Apply Node.js streams for low-footprint data processing Fast-track performance knowledge and optimization abilities Persistence strategies, including database integrations with MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB Apply critical, essential security concepts Use Node with best-of-breed deployment technologies: Docker, Kubernetes and AWS In Detail Today's web demands efficient real-time applications and scalability. Asynchronous event-driven programming is ideal for this, and this is where Node.js comes in. Server-side JavaScript has been here since the 90s, but Node got it right. With Node for tooling and server-side logic, and a browser-based client-side UI, everything is JavaScript. This leads to rapid, fluid development cycles. The full-stack, single language experience means less context-switching between languages for developers, architects and whole teams. This book shows you how to build fast, efficient, and scalable client-server solutions using the latest versions of Node. The book begins with debugging tips and tricks of the trade, and how to write your own modules. Then you'll learn the fundamentals of streams in Node.js, discover I/O control, and how to implement the different web protocols. You'll find recipes for integrating databases such as MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB. We also cover the options for building web application with Express, Hapi and Koa. You will then learn about security essentials in Node.js and advanced optimization tools and techniques. By the end of the book you will have acquired the level of expertise to build production-ready and scalable Node.js systems. The techniques and skills you will learn in this book are based on the best practices developed by nearForm, one of the leaders in Node implementations, who supported the work of the authors on this book. Style and approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient server side applications using the latest features and capabilities in Node 8 whilst also supporting usage with Node 4 and 6.

Scala Data Analysis Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1784394998
Total Pages : 254 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis Scala Data Analysis Cookbook by : Arun Manivannan

Download or read book Scala Data Analysis Cookbook written by Arun Manivannan and published by Packt Publishing Ltd. This book was released on 2015-10-30 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes About This Book Implement Scala in your data analysis using features from Spark, Breeze, and Zeppelin Scale up your data anlytics infrastructure with practical recipes for Scala machine learning Recipes for every stage of the data analysis process, from reading and collecting data to distributed analytics Who This Book Is For This book shows data scientists and analysts how to leverage their existing knowledge of Scala for quality and scalable data analysis. What You Will Learn Familiarize and set up the Breeze and Spark libraries and use data structures Import data from a host of possible sources and create dataframes from CSV Clean, validate and transform data using Scala to pre-process numerical and string data Integrate quintessential machine learning algorithms using Scala stack Bundle and scale up Spark jobs by deploying them into a variety of cluster managers Run streaming and graph analytics in Spark to visualize data, enabling exploratory analysis In Detail This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you'll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX. Style and approach This book contains a rich set of recipes that covers the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala and Spark.

Amazon EC2 Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1785282255
Total Pages : 194 pages
Book Rating : 4.7/5 (852 download)

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Book Synopsis Amazon EC2 Cookbook by : Sekhar Reddy

Download or read book Amazon EC2 Cookbook written by Sekhar Reddy and published by Packt Publishing Ltd. This book was released on 2015-11-27 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 40 hands-on recipes to develop and deploy real-world applications using Amazon EC2 About This Book Design and build applications using Amazon EC2 and a range of supporting AWS tools Find highly effective solutions to your AWS Cloud-based application development, deployment, and infrastructural issues A comprehensive set of recipes to implement your product's functional and non-functional requirements Who This Book Is For This book is targeted at Cloud-based developers who have prior exposure to AWS concepts and features. Some experience in building small applications and creating some proof-of-concept applications is required. What You Will Learn Select and configure the right EC2 instances Create, configure, and secure a Virtual Private Cloud Create an AWS CloudFormation template Use AWS Identity and Access Management to secure access to EC2 instances Configure auto-scaling groups using CloudWatch Choose and use the right data service such as SimpleDB and DynamoDB for your cloud applications Access key AWS services using client tools and AWS SDKs Deploy AWS applications using Docker containers In Detail Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides flexible and resizable compute capacity in the cloud. The main purpose of Amazon EC2 is to make web-scale cloud computing easier for the developers. It offers developers and companies the raw building blocks like load balancers, object stores and virtual machines running on general hardware (that is, Amazon runs a multitude of hardware components but presents them as a generic utility to its users) with accessible APIs in order to create scalable software products This book covers designing, developing, and deploying scalable, highly available, and secure applications on the AWS platform. By following the steps in the recipes, you will be able to effectively and systematically resolve issues related to development, deployment, and infrastructure for enterprise-grade cloud applications or products. This book starts with helping you choose and configure the right EC2 instances to meet your application-specific requirements. The book then moves on to creating a CloudFormation template and will teach you how to work with stacks. You will then be introduced to using IAM services to configure users, groups, roles, and multi-factor authentication. You will also learn how to connect AD to AWS IAM. Next, you will be using AWS data services and accessing other AWS services including Route 53, Amazon S3, and AWS SES (Amazon Simple Email Service). Finally, you will be deploying AWS applications using Docker containers. Style and approach This book contains a rich set of recipes that cover not only the full spectrum of real-world cloud application development using Amazon EC2, but also the services and security of the applications. The book contains easy-to-follow recipes with step-by-step instructions to leverage EC2 within your applications.

Java Deep Learning Cookbook

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1788999479
Total Pages : 294 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Java Deep Learning Cookbook by : Rahul Raj

Download or read book Java Deep Learning Cookbook written by Rahul Raj and published by Packt Publishing Ltd. This book was released on 2019-11-08 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java and Deeplearning4j to build robust, scalable, and highly accurate AI models from scratch Key FeaturesInstall and configure Deeplearning4j to implement deep learning models from scratchExplore recipes for developing, training, and fine-tuning your neural network models in JavaModel neural networks using datasets containing images, text, and time-series dataBook Description Java is one of the most widely used programming languages in the world. With this book, you will see how to perform deep learning using Deeplearning4j (DL4J) – the most popular Java library for training neural networks efficiently. This book starts by showing you how to install and configure Java and DL4J on your system. You will then gain insights into deep learning basics and use your knowledge to create a deep neural network for binary classification from scratch. As you progress, you will discover how to build a convolutional neural network (CNN) in DL4J, and understand how to construct numeric vectors from text. This deep learning book will also guide you through performing anomaly detection on unsupervised data and help you set up neural networks in distributed systems effectively. In addition to this, you will learn how to import models from Keras and change the configuration in a pre-trained DL4J model. Finally, you will explore benchmarking in DL4J and optimize neural networks for optimal results. By the end of this book, you will have a clear understanding of how you can use DL4J to build robust deep learning applications in Java. What you will learnPerform data normalization and wrangling using DL4JBuild deep neural networks using DL4JImplement CNNs to solve image classification problemsTrain autoencoders to solve anomaly detection problems using DL4JPerform benchmarking and optimization to improve your model's performanceImplement reinforcement learning for real-world use cases using RL4JLeverage the capabilities of DL4J in distributed systemsWho this book is for If you are a data scientist, machine learning developer, or a deep learning enthusiast who wants to implement deep learning models in Java, this book is for you. Basic understanding of Java programming as well as some experience with machine learning and neural networks is required to get the most out of this book.

Apache Solr High Performance

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1782164839
Total Pages : 172 pages
Book Rating : 4.7/5 (821 download)

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Book Synopsis Apache Solr High Performance by : Surendra Mohan

Download or read book Apache Solr High Performance written by Surendra Mohan and published by Packt Publishing Ltd. This book was released on 2014-03-25 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an easy-to-follow guide, full of hands-on, real-world examples. Each topic is explained and demonstrated in a specific and user-friendly flow, from search optimization using Solr to Deployment of Zookeeper applications. This book is ideal for Apache Solr developers and want to learn different techniques to optimize Solr performance with utmost efficiency, along with effectively troubleshooting the problems that usually occur while trying to boost performance. Familiarity with search servers and database querying is expected.

Apache Spark for Data Science Cookbook

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Publisher : Packt Publishing Ltd
ISBN 13 : 1785288806
Total Pages : 388 pages
Book Rating : 4.7/5 (852 download)

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Book Synopsis Apache Spark for Data Science Cookbook by : Padma Priya Chitturi

Download or read book Apache Spark for Data Science Cookbook written by Padma Priya Chitturi and published by Packt Publishing Ltd. This book was released on 2016-12-22 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over insightful 90 recipes to get lightning-fast analytics with Apache Spark About This Book Use Apache Spark for data processing with these hands-on recipes Implement end-to-end, large-scale data analysis better than ever before Work with powerful libraries such as MLLib, SciPy, NumPy, and Pandas to gain insights from your data Who This Book Is For This book is for novice and intermediate level data science professionals and data analysts who want to solve data science problems with a distributed computing framework. Basic experience with data science implementation tasks is expected. Data science professionals looking to skill up and gain an edge in the field will find this book helpful. What You Will Learn Explore the topics of data mining, text mining, Natural Language Processing, information retrieval, and machine learning. Solve real-world analytical problems with large data sets. Address data science challenges with analytical tools on a distributed system like Spark (apt for iterative algorithms), which offers in-memory processing and more flexibility for data analysis at scale. Get hands-on experience with algorithms like Classification, regression, and recommendation on real datasets using Spark MLLib package. Learn about numerical and scientific computing using NumPy and SciPy on Spark. Use Predictive Model Markup Language (PMML) in Spark for statistical data mining models. In Detail Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark's selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark's data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work. Style and approach This book contains a comprehensive range of recipes designed to help you learn the fundamentals and tackle the difficulties of data science. This book outlines practical steps to produce powerful insights into Big Data through a recipe-based approach.