Download Free Elasticsearch 70 Cookbook Book in PDF and EPUB Free Download. You can read online Elasticsearch 70 Cookbook and write the review.

If you are a developer who implements ElasticSearch in your web applications and want to sharpen your understanding of the core elements and applications, this is the book for you. It is assumed that you’ve got working knowledge of JSON and, if you want to extend ElasticSearch, of Java and related technologies.
Search, analyze, and manage data effectively with Elasticsearch 7 Key FeaturesExtend Elasticsearch functionalities and learn how to deploy on Elastic CloudDeploy and manage simple Elasticsearch nodes as well as complex cluster topologiesExplore the capabilities of Elasticsearch 7 with easy-to-follow recipesBook Description Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics. Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch, and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch. What you will learnCreate an efficient architecture with ElasticsearchOptimize search results by executing analytics aggregationsBuild complex queries by managing indices and documentsMonitor the performance of your cluster and nodesDesign advanced mapping to take full control of index stepsIntegrate Elasticsearch in Java, Scala, Python, and big data applicationsInstall Kibana to monitor clusters and extend it for pluginsWho this book is for If you’re a software engineer, big data infrastructure engineer, or Elasticsearch developer, you'll find this book useful. This Elasticsearch book will also help data professionals working in the e-commerce and FMCG industry who use Elastic for metrics evaluation and search analytics to get deeper insights for better business decisions. Prior experience with Elasticsearch will help you get the most out of this book.
Search, analyze, store and manage data effectively with Elasticsearch 8.x Key Features • Explore the capabilities of Elasticsearch 8.x with easy-to-follow recipes • Extend the Elasticsearch functionalities and learn how to deploy on Elastic Cloud • Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies Book Description Elasticsearch is a Lucene-based distributed search engine at the heart of the Elastic Stack that allows you to index and search unstructured content with petabytes of data. With this updated fifth edition, you'll cover comprehensive recipes relating to what's new in Elasticsearch 8.x and see how to create and run complex queries and analytics. The recipes will guide you through performing index mapping, aggregation, working with queries, and scripting using Elasticsearch. You'll focus on numerous solutions and quick techniques for performing both common and uncommon tasks such as deploying Elasticsearch nodes, using the ingest module, working with X-Pack, and creating different visualizations. As you advance, you'll learn how to manage various clusters, restore data, and install Kibana to monitor a cluster and extend it using a variety of plugins. Furthermore, you'll understand how to integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this Elasticsearch cookbook, you'll have gained in-depth knowledge of implementing the Elasticsearch architecture and be able to manage, search, and store data efficiently and effectively using Elasticsearch. What you will learn • Become well-versed with the capabilities of X-Pack • Optimize search results by executing analytics aggregations • Get to grips with using text and numeric queries as well as relationship and geo queries • Install Kibana to monitor clusters and extend it for plugins • Build complex queries by managing indices and documents • Monitor the performance of your cluster and nodes • Design advanced mapping to take full control of index steps • Integrate Elasticsearch in Java, Scala, Python, and big data applications Who this book is for If you're a software engineer, big data infrastructure engineer, or Elasticsearch developer, you'll find this Elasticsearch book useful. The book will also help data professionals working in e-commerce and FMCG industries who use Elastic for metrics evaluation and search analytics to gain deeper insights and make better business decisions. Prior experience with Elasticsearch will help you get the most out of this book.
Over 170 advanced recipes to search, analyze, deploy, manage, and monitor data effectively with Elasticsearch 5.x About This Book Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies Write native plugins to extend the functionalities of Elasticsearch 5.x to boost your business Packed with clear, step-by-step recipes to walk you through the capabilities of Elasticsearch 5.x Who This Book Is For If you are a developer who wants to get the most out of Elasticsearch for advanced search and analytics, this is the book for you. Some understanding of JSON is expected. If you want to extend Elasticsearch, understanding of Java and related technologies is also required. What You Will Learn Choose the best Elasticsearch cloud topology to deploy and power it up with external plugins Develop tailored mapping to take full control of index steps Build complex queries through managing indices and documents Optimize search results through executing analytics aggregations Monitor the performance of the cluster and nodes Install Kibana to monitor cluster and extend Kibana for plugins Integrate Elasticsearch in Java, Scala, Python and Big Data applications In Detail Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We'll guide you through comprehensive recipes on what's new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and scripting. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch. Style and approach This book follows a problem-solution approach to effectively use and manage Elasticsearch. Each recipe focuses on a particular task at hand, and is explained in a very simple, easy to understand manner.
A practical book on real-world NGINX deployments to get you up and running quickly. About This Book Be the first to immerse yourself in the NGINX 1.9x web server and explore the plethora of advanced features. Master the skills of load balancing TCP-based applications and implementing HTTP/2. A recipe-based approach book that provides you with up-to-date information on NGINX, allowing you to implement specific use cases immediately. Who This Book Is For This book is aimed at smaller-to-medium developers, who are just getting started with NGINX. It assumes they already understand the basics of how a web server works and how basic networking works. What You Will Learn Practical, real-world examples and recipes on how to use NGINX Common CMS deployments such as WordPress, Joomla and more NGINX configurations for frameworks such as Ruby on Rails, Django and more Detailed SSL recipes, including HTTP/2 Real world rewrite examples Basic web and TCP load balancing configuration Bandwidth management and connection limiting Detailed NGINX deployment scenarios with Docker Performance tuning and monitoring of your NGINX deployments OpenResty deployment guides Advanced deployments with NGINX Plus features In Detail NGINX Cookbook covers the basics of configuring NGINX as a web server for use with common web frameworks such as WordPress and Ruby on Rails, through to utilization as a reverse proxy. Designed as a go-to reference guide, this book will give you practical answers based on real-world deployments to get you up and running quickly. Recipes have also been provided for multiple SSL configurations, different logging scenarios, practical rewrites, and multiple load balancing scenarios. Advanced topics include covering bandwidth management, Docker container usage, performance tuning, OpenResty, and the NGINX Plus commercial features. By the time you've read this book, you will be able to adapt and use a wide variety of NGINX implementations to solve any problems you have.
Incident response tools and techniques for effective cyber threat response Key Features Create a solid incident response framework and manage cyber incidents effectively Learn to apply digital forensics tools and techniques to investigate cyber threats Explore the real-world threat of ransomware and apply proper incident response techniques for investigation and recovery Book DescriptionAn understanding of how digital forensics integrates with the overall response to cybersecurity incidents is key to securing your organization’s infrastructure from attacks. This updated third edition will help you perform cutting-edge digital forensic activities and incident response with a new focus on responding to ransomware attacks. After covering the fundamentals of incident response that are critical to any information security team, you’ll explore incident response frameworks. From understanding their importance to creating a swift and effective response to security incidents, the book will guide you using examples. Later, you’ll cover digital forensic techniques, from acquiring evidence and examining volatile memory through to hard drive examination and network-based evidence. You’ll be able to apply these techniques to the current threat of ransomware. As you progress, you’ll discover the role that threat intelligence plays in the incident response process. You’ll also learn how to prepare an incident response report that documents the findings of your analysis. Finally, in addition to various incident response activities, the book will address malware analysis and demonstrate how you can proactively use your digital forensic skills in threat hunting. By the end of this book, you’ll be able to investigate and report unwanted security breaches and incidents in your organization.What you will learn Create and deploy an incident response capability within your own organization Perform proper evidence acquisition and handling Analyze the evidence collected and determine the root cause of a security incident Integrate digital forensic techniques and procedures into the overall incident response process Understand different techniques for threat hunting Write incident reports that document the key findings of your analysis Apply incident response practices to ransomware attacks Leverage cyber threat intelligence to augment digital forensics findings Who this book is for This book is for cybersecurity and information security professionals who want to implement digital forensics and incident response in their organizations. You’ll also find the book helpful if you’re new to the concept of digital forensics and looking to get started with the fundamentals. A basic understanding of operating systems and some knowledge of networking fundamentals are required to get started with this book.
If your organization is preparing to move toward a cloud-native computing architecture, this cookbook shows you how to successfully use Kubernetes, the de-facto standard for automating the deployment, scaling, and management of containerized applications. With more than 80 proven recipes, developers, system administrators, and architects will quickly learn how to get started with Kubernetes and understand its powerful API. Through the course of the book, authors Sébastien Goasguen and Michael Hausenblas provide several detailed solutions for installing, interacting with, and using Kubernetes in development and production. You'll learn how to adapt the system to your particular needs and become familiar with the wider Kubernetes ecosystem. Each standalone chapter features recipes written in O'Reilly's popular problem-solution-discussion format. Recipes in this cookbook focus on: Creating a Kubernetes cluster Using the Kubernetes command-line interface Managing fundamental workload types Working with services Exploring the Kubernetes API Managing stateful and non-cloud native apps Working with volumes and configuration data Cluster-level and application-level scaling Securing your applications Monitoring and logging Maintenance and troubleshooting.
Unlock the full potential of Elastic Stack for search, analytics, security, and observability and manage substantial data workloads in both on-premise and cloud environments Key Features Explore the diverse capabilities of the Elastic Stack through a comprehensive set of recipes Build search applications, analyze your data, and observe cloud-native applications Harness powerful machine learning and AI features to create data science and search applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionLearn how to make the most of the Elastic Stack (ELK Stack) products—including Elasticsearch, Kibana, Elastic Agent, and Logstash—to take data reliably and securely from any source, in any format, and then search, analyze, and visualize it in real-time. This cookbook takes a practical approach to unlocking the full potential of Elastic Stack through detailed recipes step by step. Starting with installing and ingesting data using Elastic Agent and Beats, this book guides you through data transformation and enrichment with various Elastic components and explores the latest advancements in search applications, including semantic search and Generative AI. You'll then visualize and explore your data and create dashboards using Kibana. As you progress, you'll advance your skills with machine learning for data science, get to grips with natural language processing, and discover the power of vector search. The book covers Elastic Observability use cases for log, infrastructure, and synthetics monitoring, along with essential strategies for securing the Elastic Stack. Finally, you'll gain expertise in Elastic Stack operations to effectively monitor and manage your system.What you will learn Discover techniques for collecting data from diverse sources Visualize data and create dashboards using Kibana to extract business insights Explore machine learning, vector search, and AI capabilities of Elastic Stack Handle data transformation and data formatting Build search solutions from the ingested data Leverage data science tools for in-depth data exploration Monitor and manage your system with Elastic Stack Who this book is for This book is for Elastic Stack users, developers, observability practitioners, and data professionals ranging from beginner to expert level. If you’re a developer, you’ll benefit from the easy-to-follow recipes for using APIs and features to build powerful applications, and if you’re an observability practitioner, this book will help you with use cases covering APM, Kubernetes, and cloud monitoring. For data engineers and AI enthusiasts, the book covers dedicated recipes on vector search and machine learning. No prior knowledge of the Elastic Stack is required.
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.
A problem-solution guide to encounter various NLP tasks utilizing Java open source libraries and cloud-based solutions Key FeaturesPerform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach Utilize cloud-based APIs to perform machine translation operationsBook Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon’s AWS. You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentences, or semantic words. What you will learnExplore how to use tokenizers in NLP processing Implement NLP techniques in machine learning and deep learning applications Identify sentences within the text and learn how to train specialized NER models Learn how to classify documents and perform sentiment analysis Find semantic similarities between text elements and extract text from a variety of sources Preprocess text from a variety of data sources Learn how to identify and translate languagesWho this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected.