Elasticsearch Index Lifecycle Management

  elasticsearch index lifecycle management: Elasticsearch 8 for Developers Anurag Srivastava, 2023-10-30 Learn how to build and deploy scalable, real-time search applications with Elasticsearch 8 KEY FEATURES ● Learn the basics of Elasticsearch, including its key features and use. ● Understand the Elastic Stack and how its components, such as Kibana, Logstash, and Beats work with Elasticsearch to search, analyze, and visualize data. ● Learn how to tune Elasticsearch to improve its performance, scalability, and reliability. DESCRIPTION Elasticsearch is a powerful tool for handling and managing large amount of data. It is scalable, reliable, and fast, with various features for data analysis and search. This book is a comprehensive guide to using Elasticsearch to manage data. It starts with an overview of Elasticsearch, detailing its importance in today's world. The book further covers the basics of Elasticsearch, including installation, configuration, and index management. Next, the book covers more advanced topics, such as handling geospatial data and using aggregations to analyze data. It also covers performance optimization and administration. Throughout the book, the author provides practical examples to help you understand and apply the concepts learned. By the end of this book, you will have a deep understanding of Elasticsearch and use it to manage and extract valuable insights from large amount of data. WHAT YOU WILL LEARN ● Learn how to ingest, store, and visualize data using Elasticsearch for efficient management. ● Understand how Elasticsearch works and compare it to other search engines. ● Install Elasticsearch on different operating systems. ● Learn about Elasticsearch index management in detail. ● Use practical examples to learn how to import data from various sources, such as relational databases and files. ● Build high-performance search systems and optimize Elasticsearch clusters. WHO THIS BOOK IS FOR This book is for everyone who wants to learn Elasticsearch, whether you are a developer, architect, database administrator, DevOps engineer, or someone curious about working with data. TABLE OF CONTENTS 1. Getting Started with Elasticsearch 2. Installing Elasticsearch 3. Elastic Stack: The Ecosystem of Elasticsearch 4. Preparing Data for Indexing 5. Importing Data into Elasticsearch 6. Index Management: Creating, Updating, and Deleting Elasticsearch Indices 7. Search Capabilities: Mastering Query DSL and Search Techniques 8. Handling Geo with Elasticsearch 9. Analyzing Data with Elasticsearch Aggregations 10. Performance Tuning 11. Administration: Managing Elasticsearch Clusters
  elasticsearch index lifecycle management: Learning Elasticsearch 7.x Anurag Srivastava, 2020-12-09 A step-by-step guide that will teach you how to use Elasticsearch in your application effectively Ê KEY FEATURESÊÊÊ _Ê Get familiar with the core concepts of Elasticsearch. _Ê Understand how the search engine works and how Elasticsearch is different from other similar tools. _Ê Learn to install Elasticsearch on different operating systems. _Ê Get familiar with the components of Elastic Stack such as Kibana, Logstash, and Beats, etc. _Ê Learn how to import data from different sources such as RDBMS, and files, etc DESCRIPTIONÊ In the modern Information Technology age, we are flooded with loads of data so we should know how to handle those data and transform them to fetch meaningful information. This book is here to help you manage the data using Elasticsearch. The book starts by covering the fundamentals of Elasticsearch and the concept behind it. After the introduction, you will learn how to install Elasticsearch on different platforms. You will then get to know about Index Management where you will learn to create, update, and delete Elasticsearch indices. Then you will understand how the Query DSL works and how to write some complex search queries using the Query DSL. After completing these basic features, you will move to some advanced topics. Under advanced topics, you will learn to handle Geodata which can be used to plot the data on a map. The book then focuses on Data Analysis using Aggregation.Ê You will then learn how to tune Elasticsearch performance. The book ends with a chapter on Elasticsearch administration. Ê WHAT YOU WILL LEARN Ê_Ê Learn how to create and manage a cluster _Ê Work with different components of Elastic Stack _Ê Review the list of top Information Security certifications. _Ê Get to know more about Elasticsearch Index Management. _Ê Understand how to improve the performance by tuning Elasticsearch Ê ÊWHO THIS BOOK IS FORÊ This book is for developers, architects, DBA, DevOps, and other readers who want to learn Elasticsearch efficiently and want to apply that in their application whether it is a new one or an existing one. It is also beneficial to those who want to play with their data using Elasticsearch. Basic computer programming is a prerequisite. Ê TABLE OF CONTENTS 1 Getting started with Elasticsearch 2 Installation Elasticsearch 3 Working with Elastic Stack 4 Preparing your data 5 Importing Data into Elasticsearch 6 Managing Your Index 7 Apply Search on Your Data 8 Handling Geo with Elasticsearch 9 Aggregating Your Data 10 Improving the Performance 11 Administer Elasticsearch
  elasticsearch index lifecycle management: Elasticsearch in Action, Second Edition Madhusudhan Konda, 2023-10-31 Build powerful, production-ready search applications using the incredible features of Elasticsearch. In Elasticsearch in Action, Second Edition you will discover: Architecture, concepts, and fundamentals of Elasticsearch Installing, configuring, and running Elasticsearch and Kibana Creating an index with custom settings Data types, mapping fundamentals, and templates Fundamentals of text analysis and working with text analyzers Indexing, deleting, and updating documents Indexing data in bulk, and reindexing and aliasing operations Learning search concepts, relevancy scores, and similarity algorithms Elasticsearch in Action, Second Edition teaches you to build scalable search applications using Elasticsearch. This completely new edition explores Elasticsearch fundamentals from the ground up. You’ll deep dive into design principles, search architectures, and Elasticsearch’s essential APIs. Every chapter is clearly illustrated with diagrams and hands-on examples. You’ll even explore real-world use cases for full text search, data visualizations, and machine learning. Plus, its comprehensive nature means you’ll keep coming back to the book as a handy reference! Foreword by Shay Banon. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Create fully professional-grade search engines with Elasticsearch and Kibana! Rewritten for the latest version of Elasticsearch, this practical book explores Elasticsearch’s high-level architecture, reveals infrastructure patterns, and walks through the search and analytics capabilities of numerous Elasticsearch APIs. About the book Elasticsearch in Action, Second Edition teaches you how to add modern search features to websites and applications using Elasticsearch 8. In it, you’ll quickly progress from the basics of installation and configuring clusters, to indexing documents, advanced aggregations, and putting your servers into production. You’ll especially appreciate the mix of technical detail with techniques for designing great search experiences. What's inside Understanding search architecture Full text and term-level search queries Analytics and aggregations High-level visualizations in Kibana Configure, scale, and tune clusters About the reader For application developers comfortable with scripting and command-line applications. About the author Madhusudhan Konda is a full-stack lead engineer, architect, mentor, and conference speaker. He delivers live online training on Elasticsearch and the Elastic Stack. Table of Contents 1 Overview 2 Getting started 3 Architecture 4 Mapping 5 Working with documents 6 Indexing operations 7 Text analysis 8 Introducing search 9 Term-level search 10 Full-text searches 11 Compound queries 12 Advanced search 13 Aggregations 14 Administration 15 Performance and troubleshooting
  elasticsearch index lifecycle management: Advanced Elasticsearch 7.0 Wai Tak Wong, 2019-08-23 Master the intricacies of Elasticsearch 7.0 and use it to create flexible and scalable search solutions Key FeaturesMaster the latest distributed search and analytics capabilities of Elasticsearch 7.0Perform searching, indexing, and aggregation of your data at scaleDiscover tips and techniques for speeding up your search query performanceBook Description Building enterprise-grade distributed applications and executing systematic search operations call for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and understand how you can develop a sophisticated, real-time search engine confidently. In addition to this, you'll also learn to run machine learning jobs in Elasticsearch to speed up routine tasks. You'll get started by learning to use Elasticsearch features on Hadoop and Spark and make search results faster, thereby improving the speed of query results and enhancing the customer experience. You'll then get up to speed with performing analytics by building a metrics pipeline, defining queries, and using Kibana for intuitive visualizations that help provide decision-makers with better insights. The book will later guide you through using Logstash with examples to collect, parse, and enrich logs before indexing them in Elasticsearch. By the end of this book, you will have comprehensive knowledge of advanced topics such as Apache Spark support, machine learning using Elasticsearch and scikit-learn, and real-time analytics, along with the expertise you need to increase business productivity, perform analytics, and get the very best out of Elasticsearch. What you will learnPre-process documents before indexing in ingest pipelinesLearn how to model your data in the real worldGet to grips with using Elasticsearch for exploratory data analysisUnderstand how to build analytics and RESTful servicesUse Kibana, Logstash, and Beats for dashboard applicationsGet up to speed with Spark and Elasticsearch for real-time analyticsExplore the basics of Spring Data Elasticsearch, and understand how to index, search, and query in a Spring applicationWho this book is for This book is for Elasticsearch developers and data engineers who want to take their basic knowledge of Elasticsearch to the next level and use it to build enterprise-grade distributed search applications. Prior experience of working with Elasticsearch will be useful to get the most out of this book.
  elasticsearch index lifecycle management: Learning Elastic Stack 7.0 Pranav Shukla, Sharath Kumar M N, 2019-05-31 A beginner's guide to storing, managing, and analyzing data with the updated features of Elastic 7.0 Key FeaturesGain access to new features and updates introduced in Elastic Stack 7.0Grasp the fundamentals of Elastic Stack including Elasticsearch, Logstash, and KibanaExplore useful tips for using Elastic Cloud and deploying Elastic Stack in production environmentsBook Description The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. This book will give you a fundamental understanding of what the stack is all about, and help you use it efficiently to build powerful real-time data processing applications. The first few sections of the book will help you understand how to set up the stack by installing tools, and exploring their basic configurations. You’ll then get up to speed with using Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for data visualization. As you work through the book, you will discover the technique of creating custom plugins using Kibana and Beats. This is followed by coverage of the Elastic X-Pack, a useful extension for effective security and monitoring. You’ll also find helpful tips on how to use Elastic Cloud and deploy Elastic Stack in production environments. By the end of this book, you’ll be well versed with the fundamental Elastic Stack functionalities and the role of each component in the stack to solve different data processing problems. What you will learnInstall and configure an Elasticsearch architectureSolve the full-text search problem with ElasticsearchDiscover powerful analytics capabilities through aggregations using ElasticsearchBuild a data pipeline to transfer data from a variety of sources into Elasticsearch for analysisCreate interactive dashboards for effective storytelling with your data using KibanaLearn how to secure, monitor and use Elastic Stack’s alerting and reporting capabilitiesTake applications to an on-premise or cloud-based production environment with Elastic StackWho this book is for This book is for entry-level data professionals, software engineers, e-commerce developers, and full-stack developers who want to learn about Elastic Stack and how the real-time processing and search engine works for business analytics and enterprise search applications. Previous experience with Elastic Stack is not required, however knowledge of data warehousing and database concepts will be helpful.
  elasticsearch index lifecycle management: Advanced Mastery of Elasticsearch: Innovative Search Solutions Explored Peter Jones, 2024-10-17 Unlock the full potential of Elasticsearch with our definitive guide, Advanced Mastery of Elasticsearch: Innovative Search Solutions Explored. This comprehensive book is crafted for professionals aspiring to enhance their skills in developing robust, scalable search and analytics solutions. Whether you're a software developer, data analyst, system administrator, or IT professional, this resource covers everything from setup, configuration, and cluster management to advanced querying, data indexing, and security. Delve deep into the core concepts of Elasticsearch architecture, uncover the intricacies of Query DSL, and master text analysis with analyzers, tokenizers, and filters. Discover best practices for managing large datasets, optimizing performance, and ensuring your deployments are secure and efficient. Each chapter is meticulously organized to build on your knowledge, offering detailed insights and practical examples to address real-world challenges. Advanced Mastery of Elasticsearch: Innovative Search Solutions Explored is more than a book; it's an indispensable resource guiding you through the creation of cutting-edge search and analytics implementations. Elevate your Elasticsearch expertise and revolutionize how you handle data in your organization.
  elasticsearch index lifecycle management: Elasticsearch 8.x Cookbook Alberto Paro, 2022-05-27 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.
  elasticsearch index lifecycle management: Mastering Elasticsearch Saravanan Kuppusamy, 2024-06-05 Welcome to Mastering Elasticsearch: A Comprehensive Guide. If you're reading this book, it's because you've recognized Elasticsearch's immense potential and are eager to utilize its power for your projects and organization. This guide is designed for data engineers, developers, architects, and anyone seeking to navigate the intricacies of Elasticsearch, empowering you to extract valuable insights from data efficiently. Mastering Elasticsearch serves as your definitive guide to unlocking the full potential of this powerful search engine, known for its versatility in managing modern data. Whether you're a developer, data engineer, or system architect, this book provides the skills to leverage Elasticsearch’s capabilities, giving you a critical edge in search and data analytics. Why Elasticsearch? In today's digital landscape, the sheer volume of data generated every second is staggering. We face the challenge of searching, analyzing, and making sense of this data to deliver actionable insights. Elasticsearch, a cornerstone of the ELK (Elasticsearch, Logstash, Kibana) stack, has emerged as a leading search and analytics engine, renowned for its speed, scalability, and flexibility. It powers systems from full-text search to complex, real-time analytics, handling massive datasets and providing mission-critical support to global organizations. This book takes you on a journey through the vast capabilities of Elasticsearch, from foundational concepts to advanced implementations. Whether you're setting up your first cluster or looking to fine-tune existing deployments, this guide will offer insights tailored to your needs. Foundational Understanding: We'll begin with a robust introduction to Elasticsearch's architecture, terminology, and basic operations. You'll understand how Elasticsearch indexes, searches, and maps data to provide rapid search results. Cluster Architecture: Gain a thorough understanding of Elasticsearch’s distributed architecture, from nodes and shards to clusters, and how these elements work together for horizontal scaling. Indexing Techniques: Learn about creating, managing, and optimizing indices, the cornerstone of Elasticsearch data storage, for efficient search operations. Intermediate Techniques: Building on this foundation, we'll delve into more advanced features such as aggregations, data visualization, and effective index management. We'll discuss geo queries, nested data structures, and how to optimize queries to handle complex data types. Advanced Topics: In the final section, you'll encounter specialized topics like performance tuning, scaling Elasticsearch clusters, and developing custom plugins. We'll explore practical strategies for enhancing security, setting up monitoring, and employing machine learning features to identify patterns and trends in your data. Advanced Querying and Aggregation: Query DSL: Master Elasticsearch’s Query Domain-Specific Language, enabling you to construct sophisticated queries that handle nuanced search requirements with precision. Aggregations: Dive deep into aggregation frameworks that provide powerful tools for real-time analytics, including complex aggregations like nested, scripted, and pipeline. Data Ingestion and Integration: Ingestion Pipelines: Explore ways to seamlessly ingest and transform data with Elasticsearch’s ingest nodes and processors. External Integrations: Implement data ingestion strategies using Logstash, Beats, and other ETL solutions to connect with various data sources. Indexing Strategy: Optimize indexing through sharding, replication, and customized mapping. Caching and Memory: Leverage caching mechanisms and JVM tuning to reduce latency and boost throughput. Security Practices: Implement robust security through authentication, authorization, and encryption to safeguard sensitive data. Monitoring and Troubleshooting: Use Kibana and other tools for real-time monitoring and diagnostics, ensuring high availability and minimizing downtime. Case Studies: Examine case studies that showcase Elasticsearch’s versatility, from e-commerce search solutions to log analytics and beyond. This book aims to cater to both newcomers and seasoned Elasticsearch users. If you're starting out, we'll guide you through initial setup and offer step-by-step instructions to implement core features. Experienced users will find fresh insights, best practices, and advanced techniques to elevate their Elasticsearch knowledge. The book is structured to offer a comprehensive understanding of Elasticsearch while maintaining accessibility. Each chapter provides practical examples, code snippets, and exercises that reinforce key concepts. By working through the examples, you'll gain the confidence to tackle real-world Elasticsearch projects, whether for search, analytics, or application logging. I wrote this guide with the intention of creating a one-stop resource for all things Elasticsearch. With constant evolution in the software and big data landscape, it's essential to stay updated with the latest practices and developments. This guide aims to cover both tried-and-tested fundamentals and emerging trends to ensure you're well-prepared for the challenges ahead. Finally, thank you for choosing this book. I'm thrilled to share my knowledge and insights with you as you begin your journey toward Mastering the Elasticsearch. Let's work together to fully unlock this incredible technology, enabling us to build faster, smarter, and more efficient applications. By the end of Mastering Elasticsearch, you'll have the expertise needed to design, implement, and manage scalable and secure search applications. You'll gain both theoretical understanding and practical insights, enabling you to tailor Elasticsearch to your organization's unique data management needs.
  elasticsearch index lifecycle management: Mastering ElasticSearch Cybellium Ltd, 2023-09-26 Unveil the Power of ElasticSearch for Efficient Data Search and Analysis Are you ready to explore the realm of advanced data search and analysis? Mastering Elasticsearch is your definitive guide to harnessing the capabilities of ElasticSearch for unlocking insights and making informed decisions. Whether you're a data enthusiast or a professional seeking to optimize data retrieval, this comprehensive book equips you with the knowledge and skills to navigate the intricacies of ElasticSearch and create high-performance applications. Key Features: 1. Deep Dive into ElasticSearch: Immerse yourself in the core principles of ElasticSearch, understanding its architecture, indexing, and querying mechanisms. Build a strong foundation that empowers you to harness the full potential of this powerful search engine. 2. Indexing Strategies: Explore advanced indexing techniques for efficiently storing and retrieving data. Learn about document structures, data normalization, and custom mapping to optimize search performance. 3. Search Query Mastery: Master the art of crafting precise and complex search queries. Dive into full-text search, filtering, aggregation, and geospatial queries, enabling you to extract meaningful insights from large datasets. 4. Scaling and Performance Optimization: Discover strategies for scaling ElasticSearch to handle massive amounts of data. Learn about sharding, replication, and optimization techniques that ensure high availability and responsiveness. 5. Data Analysis and Visualization: Uncover techniques for data analysis and visualization using ElasticSearch. Explore aggregations, histograms, and date math, and learn how to create insightful visualizations that aid decision-making. 6. Elasticsearch for Logging and Monitoring: Delve into the world of logging and monitoring using ElasticSearch and the ELK stack (Elasticsearch, Logstash, Kibana). Learn how to centralize logs, monitor system performance, and gain real-time insights. 7. Security and Access Control: Explore strategies for securing your ElasticSearch cluster. Learn about authentication, authorization, and encryption mechanisms that protect your data and prevent unauthorized access. 8. Machine Learning Integration: Discover how to integrate machine learning capabilities into ElasticSearch workflows. Learn how to build and deploy machine learning models for tasks such as anomaly detection and predictive analysis. 9. Elasticsearch in Real-World Applications: Explore real-world use cases of ElasticSearch across industries. From e-commerce to healthcare, learn how organizations are leveraging ElasticSearch to drive business success. 10. Future Trends and Advancements: Gain insights into the future trends and advancements in ElasticSearch. Explore topics such as new features, integration possibilities, and emerging use cases. Who This Book Is For: Mastering Elasticsearch is an essential resource for data professionals, developers, system administrators, and enthusiasts eager to unlock the potential of ElasticSearch. Whether you're a novice seeking a comprehensive introduction or an experienced practitioner aiming to enhance your ElasticSearch skills, this book will guide you through the intricacies and empower you to create high-performance applications.
  elasticsearch index lifecycle management: Getting Started with Elastic Stack 8.0 Asjad Athick, Shay Banon, 2022-03-23 Use the Elastic Stack for search, security, and observability-related use cases while working with large amounts of data on-premise and on the cloud Key FeaturesLearn the core components of the Elastic Stack and how they work togetherBuild search experiences, monitor and observe your environments, and defend your organization from cyber attacksGet to grips with common architecture patterns and best practices for successfully deploying the Elastic StackBook Description The Elastic Stack helps you work with massive volumes of data to power use cases in the search, observability, and security solution areas. This three-part book starts with an introduction to the Elastic Stack with high-level commentary on the solutions the stack can be leveraged for. The second section focuses on each core component, giving you a detailed understanding of the component and the role it plays. You'll start by working with Elasticsearch to ingest, search, analyze, and store data for your use cases. Next, you'll look at Logstash, Beats, and Elastic Agent as components that can collect, transform, and load data. Later chapters help you use Kibana as an interface to consume Elastic solutions and interact with data on Elasticsearch. The last section explores the three main use cases offered on top of the Elastic Stack. You'll start with a full-text search and look at real-world outcomes powered by search capabilities. Furthermore, you'll learn how the stack can be used to monitor and observe large and complex IT environments. Finally, you'll understand how to detect, prevent, and respond to security threats across your environment. The book ends by highlighting architecture best practices for successful Elastic Stack deployments. By the end of this book, you'll be able to implement the Elastic Stack and derive value from it. What you will learnConfigure Elasticsearch clusters with different node types for various architecture patternsIngest different data sources into Elasticsearch using Logstash, Beats, and Elastic AgentBuild use cases on Kibana including data visualizations, dashboards, machine learning jobs, and alertsDesign powerful search experiences on top of your data using the Elastic StackSecure your organization and learn how the Elastic SIEM and Endpoint Security capabilities can helpExplore common architectural considerations for accommodating more complex requirementsWho this book is for Developers and solutions architects looking to get hands-on experience with search, security, and observability-related use cases on the Elastic Stack will find this book useful. This book will also help tech leads and product owners looking to understand the value and outcomes they can derive for their organizations using Elastic technology. No prior knowledge of the Elastic Stack is required.
  elasticsearch index lifecycle management: Application Observability with Elastic Navin Sabharwal, Ravishankar Shukla, 2022-01-28 Real User Monitoring, Application Performance Monitoring, Alerting, and Dashboarding Using Elastic Stack KEY FEATURES ● Numerous examples and visual representations of Elastic APM's capabilities. ● Covers Elastic APM cloud deployment, Kubernetes clusters, and real-user monitoring. ● Includes Kibana's visualization, Alerting and Dashboarding features. DESCRIPTION This book teaches an APM engineer how to monitor software services and applications in real time, including collecting detailed performance data on the response time for incoming requests, database queries, cache calls, and external HTTP requests. The book helps readers to explore the architecture and components of the Elastic APM stack. It also teaches you how to architect, deploy, and configure the Elastic APM stack to meet your specific requirements. The book focuses on monitoring and observability for applications and infrastructures built with Containers and Kubernetes. The book helps you configure APM capabilities like synthetic transaction and real-user transaction monitoring, integration with open-source tools like Prometheus, and data collection and processing using Logstash. Additionally, the book discusses how to use the Kibana dashboard features provided by Elastic APM in conjunction with alerting and dashboards to analyze the application's performance. Finally, the book teaches Site Reliability Engineers (SREs) how to meet service-level objectives through indicators such as availability, latency, quality, and saturation. WHAT YOU WILL LEARN ● Unleash the need and the applications of observability. ● Learn to architect and deploy the Elastic APM stack. ● Practice observability of monolithic and microservices-based applications. ● Learn advanced observability of Containers and Kubernetes cluster infrastructure. ● Uncover insights on user experience, uptime, and synthetic monitoring. ● Learn to use Kibana for exploiting alerts and visualization features. WHO THIS BOOK IS FOR Professionals in the fields of Application Performance Monitoring, Observability, Site Reliability Engineering, Software Development, AIOPS, and Cloud and Data Center Architecture will benefit greatly from this book. It would be beneficial, but not necessary, to have some knowledge of programming. TABLE OF CONTENTS 1. Introduction to Application Observability 2. Elastic Observability Features 3. Elastic Observability Deployment Architecture 4. Deployment of the Elastic Observability Platform 5. Use Case. Observability for a Containerized Java Application 6. Use Case. Observability for a Kubernetes-based Application 7. Observability for a .Net Core Application 8. Elastic Observability. User Experience, Uptime, and Synthetic Monitoring 9. Logstash Pipelines in Elastic Observability 10. Prometheus Integration with the Elastic Observability Platform 11. Machine Learning, Alerting, and Dashboards
  elasticsearch index lifecycle management: Cloud Native Software Security Handbook Mihir Shah, 2023-08-25 Master widely used cloud native platforms like Kubernetes, Calico, Kibana, Grafana, Anchor, and more to ensure secure infrastructure and software development Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn how to select cloud-native platforms and integrate security solutions into the system Leverage cutting-edge tools and platforms securely on a global scale in production environments Understand the laws and regulations necessary to prevent federal prosecution Book DescriptionFor cloud security engineers, it’s crucial to look beyond the limited managed services provided by cloud vendors and make use of the wide array of cloud native tools available to developers and security professionals, which enable the implementation of security solutions at scale. This book covers technologies that secure infrastructure, containers, and runtime environments using vendor-agnostic cloud native tools under the Cloud Native Computing Foundation (CNCF). The book begins with an introduction to the whats and whys of the cloud native environment, providing a primer on the platforms that you’ll explore throughout. You’ll then progress through the book, following the phases of application development. Starting with system design choices, security trade-offs, and secure application coding techniques that every developer should be mindful of, you’ll delve into more advanced topics such as system security architecture and threat modelling practices. The book concludes by explaining the legal and regulatory frameworks governing security practices in the cloud native space and highlights real-world repercussions that companies have faced as a result of immature security practices. By the end of this book, you'll be better equipped to create secure code and system designs.What you will learn Understand security concerns and challenges related to cloud-based app development Explore the different tools for securing configurations, networks, and runtime Implement threat modeling for risk mitigation strategies Deploy various security solutions for the CI/CD pipeline Discover best practices for logging, monitoring, and alerting Understand regulatory compliance product impact on cloud security Who this book is forThis book is for developers, security professionals, and DevOps teams involved in designing, developing, and deploying cloud native applications. It benefits those with a technical background seeking a deeper understanding of cloud-native security and the latest tools and technologies for securing cloud native infrastructure and runtime environments. Prior experience with cloud vendors and their managed services is advantageous for leveraging the tools and platforms covered in this book.
  elasticsearch index lifecycle management: Elastic Stack 8.x Cookbook Huage Chen, Yazid Akadiri, 2024-06-28 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.
  elasticsearch index lifecycle management: DevOps Unleashed Aditya Pratap Bhuyan, 2024-09-26 In today’s rapidly evolving digital landscape, organizations are increasingly seeking faster, more efficient ways to develop, test, and deploy software. DevOps Unleashed: Bridging Development and Operations for Continuous Success is a comprehensive guide that demystifies the world of DevOps and its transformative impact on modern enterprises. Written by Aditya Pratap Bhuyan, a seasoned expert with over 20 years of experience in enterprise and cloud applications, this book is tailored for professionals at all levels, offering both technical insights and a deep understanding of the cultural changes essential for DevOps success. With more than 40 industry certifications and extensive experience in Java, Spring, microservices, cloud computing, and container technologies like Docker and Kubernetes, Aditya brings a wealth of knowledge to this book. He not only covers the tools and technologies that form the backbone of a successful DevOps strategy but also emphasizes the importance of collaboration and breaking down silos between development and operations teams. DevOps Unleashed begins by exploring the origins of DevOps, examining how it evolved from traditional software development practices to a modern, agile framework. Aditya delves into the cultural mindset needed to fully embrace DevOps, illustrating how collaboration, communication, and continuous improvement are as vital as the technical aspects. The book is divided into well-structured chapters that cover key pillars of DevOps, such as Continuous Integration/Continuous Delivery (CI/CD), Infrastructure as Code (IaC), automation, monitoring, and security. Aditya walks readers through setting up CI/CD pipelines, automating infrastructure with tools like Terraform, and leveraging real-time monitoring tools like Prometheus and Grafana to ensure system health. The practical hands-on examples, case studies, and real-world scenarios make complex topics accessible for both novices and seasoned practitioners. One of the standout aspects of the book is its focus on DevSecOps—integrating security at every stage of the software development lifecycle. Aditya emphasizes the growing importance of security in DevOps pipelines and provides practical strategies for automating security checks and ensuring compliance. For those looking to go beyond the basics, the book also covers advanced DevOps topics such as chaos engineering, site reliability engineering (SRE), and the role of AI and machine learning in automating DevOps processes. This book is not just about tools or methodologies—it’s about adopting a new mindset. Aditya helps readers understand that DevOps is a journey, one that requires continuous learning, adaptation, and a commitment to innovation. Whether you’re an engineer, a team lead, or an executive looking to implement DevOps at scale, DevOps Unleashed offers a roadmap to success. By the end of this book, readers will have gained a holistic understanding of DevOps—both its cultural foundations and technical implementations—and be equipped to build, scale, and optimize DevOps practices in their own organizations.
  elasticsearch index lifecycle management: Data Engineering with Python Paul Crickard, 2020-10-23 Build, monitor, and manage real-time data pipelines to create data engineering infrastructure efficiently using open-source Apache projects Key Features Become well-versed in data architectures, data preparation, and data optimization skills with the help of practical examples Design data models and learn how to extract, transform, and load (ETL) data using Python Schedule, automate, and monitor complex data pipelines in production Book DescriptionData engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.What you will learn Understand how data engineering supports data science workflows Discover how to extract data from files and databases and then clean, transform, and enrich it Configure processors for handling different file formats as well as both relational and NoSQL databases Find out how to implement a data pipeline and dashboard to visualize results Use staging and validation to check data before landing in the warehouse Build real-time pipelines with staging areas that perform validation and handle failures Get to grips with deploying pipelines in the production environment Who this book is for This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition. No previous knowledge of data engineering is required.
  elasticsearch index lifecycle management: Kubernetes - A Complete DevOps Cookbook Murat Karslioglu, 2020-03-13 Leverage Kubernetes and container architecture to successfully run production-ready workloads Key FeaturesImplement Kubernetes to orchestrate and scale applications proficientlyLeverage the latest features of Kubernetes to resolve common as well as complex problems in a cloud-native environmentGain hands-on experience in securing, monitoring, and troubleshooting your applicationBook Description Kubernetes is a popular open source orchestration platform for managing containers in a cluster environment. With this Kubernetes cookbook, you’ll learn how to implement Kubernetes using a recipe-based approach. The book will prepare you to create highly available Kubernetes clusters on multiple clouds such as Amazon Web Services (AWS), Google Cloud Platform (GCP), Azure, Alibaba, and on-premises data centers. Starting with recipes for installing and configuring Kubernetes instances, you’ll discover how to work with Kubernetes clients, services, and key metadata. You’ll then learn how to build continuous integration/continuous delivery (CI/CD) pipelines for your applications, and understand various methods to manage containers. As you advance, you’ll delve into Kubernetes' integration with Docker and Jenkins, and even perform a batch process and configure data volumes. You’ll get to grips with methods for scaling, security, monitoring, logging, and troubleshooting. Additionally, this book will take you through the latest updates in Kubernetes, including volume snapshots, creating high availability clusters with kops, running workload operators, new inclusions around kubectl and more. By the end of this book, you’ll have developed the skills required to implement Kubernetes in production and manage containers proficiently. What you will learnDeploy cloud-native applications on KubernetesAutomate testing in the DevOps workflowDiscover and troubleshoot common storage issuesDynamically scale containerized services to manage fluctuating traffic needsUnderstand how to monitor your containerized DevOps environmentBuild DevSecOps into CI/CD pipelinesWho this book is for This Kubernetes book is for developers, IT professionals, and DevOps engineers and teams who want to use Kubernetes to manage, scale, and orchestrate applications in their organization. Basic understanding of Kubernetes and containerization is necessary.
  elasticsearch index lifecycle management: Mastering Python Networking Eric Chou, Michael Kennedy, Mandy Whaley, 2020-01-30 New edition of the bestselling guide to mastering Python Networking, updated to Python 3 and including the latest on network data analysis, Cloud Networking, Ansible 2.8, and new libraries Key FeaturesExplore the power of Python libraries to tackle difficult network problems efficiently and effectively, including pyATS, Nornir, and Ansible 2.8Use Python and Ansible for DevOps, network device automation, DevOps, and software-defined networkingBecome an expert in implementing advanced network-related tasks with Python 3Book Description Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In Mastering Python Networking, Third edition, you'll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This new edition is completely revised and updated to work with Python 3. In addition to new chapters on network data analysis with ELK stack (Elasticsearch, Logstash, Kibana, and Beats) and Azure Cloud Networking, it includes updates on using newer libraries such as pyATS and Nornir, as well as Ansible 2.8. Each chapter is updated with the latest libraries with working examples to ensure compatibility and understanding of the concepts. Starting with a basic overview of Python, the book teaches you how it can interact with both legacy and API-enabled network devices. You will learn to leverage high-level Python packages and frameworks to perform network automation tasks, monitoring, management, and enhanced network security followed by Azure and AWS Cloud networking. Finally, you will use Jenkins for continuous integration as well as testing tools to verify your network. What you will learnUse Python libraries to interact with your networkIntegrate Ansible 2.8 using Python to control Cisco, Juniper, and Arista network devicesLeverage existing Flask web frameworks to construct high-level APIsLearn how to build virtual networks in the AWS & Azure CloudLearn how to use Elastic Stack for network data analysisUnderstand how Jenkins can be used to automatically deploy changes in your networkUse PyTest and Unittest for Test-Driven Network Development in networking engineering with PythonWho this book is for Mastering Python Networking, Third edition is for network engineers, developers, and SREs who want to use Python for network automation, programmability, and data analysis. Basic familiarity with Python programming and networking-related concepts such as Transmission Control Protocol/Internet Protocol (TCP/IP) will be useful.
  elasticsearch index lifecycle management: Ultimate Certified Kubernetes Administrator (CKA) Certification Guide Rajesh Vishnupant Gheware, 2024-07-09 TAGLINE Unlock the Power of Kubernetes: Master Cluster Excellence! KEY FEATURES ● Master Kubernetes from the ground up, covering foundational to expert-level skills. ● Enhance learning with practical examples, clear diagrams, and real-world applications. ● Tailored content to help you confidently pass the CKA certification exam. DESCRIPTION Embark on a journey from beginner to pro with this CKA Certification Guide. Seamlessly blending theory with hands-on practice, this indispensable Kubernetes companion provides clear explanations and real-world scenarios to guide you to success in Kubernetes administration. The book starts by giving a solid understanding of Kubernetes platform and how to confidently set up your clusters with step-by-step instructions. You will dive into Workload Objects to master crucial concepts, then explore Service and Ingress for a deep understanding of networking. Next, it moves to deploy and scale applications, ensuring you're ready for any workload. This book offers the tools needed to design, deploy, and maintain efficient, scalable, and resilient applications in Kubernetes environments. It covers essential topics such as Pods, Deployments, and StatefulSets, along with providing insights into Kubernetes architecture and operations. The advanced section of the book focuses on enhancing your skills with chapters on security and troubleshooting, ensuring you can maintain your clusters effectively and managing microservices with precision. The final section of the book covers focused content and practice exercises to prepare you to ace the CKA certification exam. WHAT WILL YOU LEARN ● Gain the skills to set up, configure, and maintain Kubernetes clusters, ensuring secure and efficient operations. ● Learn how to create, deploy, and manage applications on Kubernetes, including handling updates and scaling. ● Acquire in-depth knowledge of Kubernetes networking and storage, enabling you to design and implement robust solutions. ● Develop expertise in automating application deployments and managing their scaling and availability for optimal performance. ● Build the ability to identify, diagnose, and resolve common Kubernetes problems, ensuring smooth cluster operations. WHO IS THIS BOOK FOR? This book is tailored for IT professionals, including DevOps engineers, system administrators, cloud architects, and Kubernetes enthusiasts, who possess a foundational understanding of containerization concepts and aspire to become proficient in Kubernetes for managing cloud-native applications. If you are a Kubernetes enthusiast looking forward to obtaining your Certified Kubernetes Administrator (CKA) certification, this book will be your indispensable companion. TABLE OF CONTENTS 1. Introduction to Kubernetes 2. Installing Kubernetes 3. Workload Objects – Pod, Deploy, StatefulSet 4. Service and Ingress - Exposing Apps Outside the Cluster 5. Deploy and Scale - Stateless Apps 6. Deployment Strategies - RollingUpdate, Recreate 7. Data Persistence - Local and Cloud 8. Deploy and Scale - StatefulSet 9. Configure Apps for Production Deployment 10. Cluster Database - Backup and Restore 11. Cluster Upgrade – kubeadm 12. CoreDNS 13. Networking - Pod Service and Ingress 14. Kubernetes CNI 15. Kubernetes Security 16. Troubleshooting 17. Kubernetes Production Essentials 18. Microservices Observability 19. Scalable Jenkins on Kubernetes 20. GitOps using ArgoCD and GitHub 21. CKA Exam Mastery Index
  elasticsearch index lifecycle management: Elastic Stackで作るBI環境　Ver.7.4対応改訂版 石井 葵, 2019-11-29 サーバーのアクセスログやTwitterのつぶやき、様々な機器の動作状況など各種のログファイルをExcelで分析していませんか？本書はBIツール「Elastic Stack」をつかってログファイルを集計し、グラフなどでビジュアル豊かに分析するための環境構築チュートリアルのバージョン7.4対応版です。 【目次】 第1章 Elastic Stackって何？ 1.1 Logstash 1.2 Elasticsearch 1.3 Kibana 1.4 Beats 1.5 Elastic Licenseで使用できる機能 1.6 APM 1.7 SIEM 1.8 Elastic Cloud 1.9 この本における基本的な構成 第2章 環境構築 2.1 インストールの順番 2.2 事前準備 2.3 Elasticsearchのインストール 2.4 Kibanaのインストール 2.5 Logstashのインストール 第3章 データを集めて可視化しよう（CSVのデータを集める編） 3.1 可視化するデータの準備 3.2 logstash.confの概要を知る 3.3 inputプラグインコンフィグの作成 3.4 outputプラグインコンフィグの作成 3.5 logstash.confをテストしつつ内容を調整する 第4章 データを集めて可視化しよう（Beatsを使って情報を集めてみる） 4.1 Beatsのインストール 4.2 Metricbeatのセットアップ 4.3 Metricbeatの起動 第5章 Kibanaを使ったデータの閲覧 5.1 Kibanaの画面項目 5.2 Discover画面を使ってみよう 5.3 Discoverでデータを閲覧する 第6章 Visualize画面でデータを可視化する 6.1 Visualize種別を知る 6.2 Visualize画面でグラフを作成する 6.3 グラフを作成する：グラフを保存する 第7章 Dashboard画面を使ってグラフを一覧表示する 7.1 グラフを並べる 7.2 グラフの大きさを指定する 7.3 保存する（検索期間を保持する/しないを選択する） 7.4 作成したDashboardを編集する
  elasticsearch index lifecycle management: Securing Networks with ELK Stack Ram Patel, 2024-06-19 Strengthening networks, redefining security: ELK Stack leading the charge KEY FEATURES ● This book provides a thorough examination of zero trust network architecture, ELK Stack, and Elastic Security, encompassing foundational principles and practical deployment strategies. ● Readers gain practical insights into building resilient zero trust networks, leveraging ELK Stack's capabilities for data gathering, visualization, and advanced analytics. ● Through real-world case studies and examples, the book illustrates how to integrate Zeek and Elastic Security effectively. DESCRIPTION Step into the dynamic world of zero trust network architecture with this comprehensive handbook. Starting with an exploration of zero trust principles, each chapter unveils new insights and practical strategies. From crafting strategic blueprints to implementing hands-on deployment tactics, discover the intricacies of building a resilient zero trust network capable of thwarting modern threats. Journey through the extensive capabilities of ELK Stack, essential for fortifying a zero trust paradigm. Learn the nuances of data acquisition strategies and efficient ingestion methods with ELK, enabling robust data visualization and dashboard creation using Kibana. Explore advanced functionalities like Machine Learning driven anomaly detection to enhance your defenses against emerging threats. Explore Elastic Security's suite, encompassing threat detection, incident response, and compliance reporting, crucial elements in strengthening network defenses. Utilize the transformative potential of Zeek in network security, from foundational principles to advanced integration with Elastic Security. Real-world case studies showcase the synergy between Zeek and Elastic Security, providing insights into future-proof network protection strategies. Arm yourself with the knowledge and tools necessary to navigate the evolving landscape of network security. Traverse the realms of zero trust architecture, ELK Stack, and Elastic Security, empowered by practical insights and real-world applications. WHAT YOU WILL LEARN ● Understanding the core principles and intricacies of zero trust network architecture. ● Designing and deploying a robust zero trust network using strategic methodologies. ● Leveraging ELK Stack's capabilities to support and enhance a zero trust approach. ● Implementing effective data gathering and ingestion strategies with ELK. ● Mastering data visualization and dashboard creation using Kibana for actionable insights. WHO THIS BOOK IS FOR The book is primarily aimed at security professionals, network architects, and IT managers who are responsible for securing their organization's network infrastructure and sensitive data. The book is suitable for both technical and non-technical readers. TABLE OF CONTENTS 1. Introduction to Zero Trust Network Architecture 2. Zero Trust Network Architecture: Design and Deployment Strategies 3. Zero Trust Network Architecture: Data Gathering Strategies 4. Overview of ELK Stack and its Capabilities 5. Design of ELK Stack Components 6. Data Ingestion with ELK 7. Data Visualization with ELK 8. Effective Dashboards with Kibana 9. Unlocking Insights: ELKʼs Machine Learning Capabilities 10. Introduction to Elastic Security 11. Threat Detection and Prevention 12. Incident Response and Investigation 13. Compliance and Reporting 14. Introduction to Zeek 15. Zeek Data Collection and Analysis 16. Unlocking Synergies: Zeek and Elastic Security Integration in Action 17. Future Directions for Elastic Security 18. A Unified Recap: Safeguarding Networks with ELK
  elasticsearch index lifecycle management: 처음 배우는 네트워크 보안 장상근(맥스), 2021-07-05 보안 시스템 구축부터 관제까지 네트워크 보안의 모든 것 이 책은 네트워크 보안 시스템을 구축하고 관제하기 위해 반드시 알아야 하는 내용으로 채웠다. 보안 담당자가 네트워크 보안 실무를 파악하는 것은 물론 중소기업이나 소규모 상업시설, 가정집처럼 상대적으로 보안에 취약한 기업과 개인이 저비용으로 보안 시스템을 구축하고 관제할 수 있다. 네트워크 구축을 시작으로 보안 시스템 구축과 운영, 보안 조직 구성, 보안 관제 센터를 만드는 방법에 대해 알아보고 보안 관제 시 사이버 공격 유형에 따른 대응 방법을 학습한다. 추천사 비용 대비 효과적으로 네트워크 보안 시스템을 구축하는 데 많은 도움을 준다. 다양한 경험을 체화한 저자의 노하우가 고스란히 녹아 있다. 각 장마다 설명된 기초 지식과 이론을 익히고, 실제 실습 수준의 예제를 따라 하도록 구성되어 기본기뿐 아니라 더 깊은 지식을 얻기에도 적절하다. _ 조민재 아톤 정보보호실 실장/CISO 이 책은 네트워크 보안과 관제 업무를 주로 다루고 있지만 저자는 공격과 방어 전 분야를 아우르는 폭넓은 지식을 보유하고 있다. 이를 통해 정보보호 전 분야를 통찰할 수 있는 수준 높은 가이드를 제시한다. 빠른 속도로 고도화되는 현대 사이버 위협에 맞서 효율적으로 기업 내 인프라를 보호하고자 하는 많은 이들에게 나침반과 같은 책이 될 것이다. _ 곽경주 에스투더블유랩 이사 네트워크 구축, 보안 시스템 운영 한 권으로 배우는 네트워크 보안 시중에 있는 해킹과 보안 관련 책은 웹 해킹, 리버스 엔지니어링, 모의 해킹 등 공격과 분석에 초점이 맞춰져 있다. 그러나 보안 업체와 기업에서는 공격이 목표가 아니라 어떻게 하면 서버, 네트워크, PC, 데이터 등 기업 자산을 안전하게 보호할 수 있을까를 고민한다. 이 책은 중소기업, 스타트업, 학교, 게임방 등 소규모 조직에서 오픈소스를 활용해 적은 예산으로 자체적으로 네트워크 보안 체계를 구축하는 것을 목표로 한다. 네트워크 구축부터 보안 시스템 구축, 운영에 이르기까지 보안 관제 중 발생할 수 있는 다양한 사이버 공격 유형에 대응할 수 있도록 구성했다. 네트워크를 구축하고 그 위에 보안 시스템을 만드는 것은 네트워크 보안의 시작이다. 이를 바탕으로 보안 관제를 통해 보안 위협을 관리하는 것이 중요하다. 이 책은 네트워크 보안에 있어 꼭 필요한 만큼의 정보로 도움을 준다. 네트워크 보안 배경지식, 보안 조직 구성, 관제 센터 구축 네트워크 시뮬레이션을 통한 네트워크 구축 실습 네트워크 보안 시스템 구축과 운영 호스트 기반 침입 탐지/차단 시스템 구축과 운영 네트워크/서버 보안 이벤트 분석 무선 네트워크 보안, 클라우드 네트워크 보안
  elasticsearch index lifecycle management: Learning ELK Stack Saurabh Chhajed, 2015-11-26 Build mesmerizing visualizations, analytics, and logs from your data using Elasticsearch, Logstash, and Kibana About This Book Solve all your data analytics problems with the ELK stack Explore the power of Kibana4 search and visualizations built over Elasticsearch queries and learn about the features and plugins of Logstash Develop a complete data pipeline using the ELK stack Who This Book Is For If you are a developer or DevOps engineer interested in building a system that provides amazing insights and business metrics out of data sources, of various formats and types, using the open source technology stack that ELK provides, then this book is for you. Basic knowledge of Unix or any programming language will be helpful to make the most out of this book. What You Will Learn Install, configure, and run Elasticsearch, Logstash, and Kibana Understand the need for log analytics and the current challenges in log analysis Build your own data pipeline using the ELK stack Familiarize yourself with the key features of Logstash and the variety of input, filter, and output plugins it provides Build your own custom Logstash plugin Create actionable insights using charts, histograms, and quick search features in Kibana4 Understand the role of Elasticsearch in the ELK stack In Detail The ELK stack—Elasticsearch, Logstash, and Kibana, is a powerful combination of open source tools. Elasticsearch is for deep search and data analytics. Logstash is for centralized logging, log enrichment, and parsing. Kibana is for powerful and beautiful data visualizations. In short, the Elasticsearch ELK stack makes searching and analyzing data easier than ever before. This book will introduce you to the ELK (Elasticsearch, Logstash, and Kibana) stack, starting by showing you how to set up the stack by installing the tools, and basic configuration. You'll move on to building a basic data pipeline using the ELK stack. Next, you'll explore the key features of Logstash and its role in the ELK stack, including creating Logstash plugins, which will enable you to use your own customized plugins. The importance of Elasticsearch and Kibana in the ELK stack is also covered, along with various types of advanced data analysis, and a variety of charts, tables ,and maps. Finally, by the end of the book you will be able to develop full-fledged data pipeline using the ELK stack and have a solid understanding of the role of each of the components. Style and approach This book is a step-by-step guide, complete with various examples to solve your data analytics problems by using the ELK stack to explore and visualize data.
  elasticsearch index lifecycle management: Managing Gigabytes Ian H. Witten, Alistair Moffat, Timothy C. Bell, 1999-05-03 This book is the Bible for anyone who needs to manage large data collections. It's required reading for our search gurus at Infoseek. The authors have done an outstanding job of incorporating and describing the most significant new research in information retrieval over the past five years into this second edition. Steve Kirsch, Cofounder, Infoseek Corporation The new edition of Witten, Moffat, and Bell not only has newer and better text search algorithms but much material on image analysis and joint image/text processing. If you care about search engines, you need this book: it is the only one with full details of how they work. The book is both detailed and enjoyable; the authors have combined elegant writing with top-grade programming. Michael Lesk, National Science Foundation The coverage of compression, file organizations, and indexing techniques for full text and document management systems is unsurpassed. Students, researchers, and practitioners will all benefit from reading this book. Bruce Croft, Director, Center for Intelligent Information Retrieval at the University of Massachusetts In this fully updated second edition of the highly acclaimed Managing Gigabytes, authors Witten, Moffat, and Bell continue to provide unparalleled coverage of state-of-the-art techniques for compressing and indexing data. Whatever your field, if you work with large quantities of information, this book is essential reading--an authoritative theoretical resource and a practical guide to meeting the toughest storage and access challenges. It covers the latest developments in compression and indexing and their application on the Web and in digital libraries. It also details dozens of powerful techniques supported by mg, the authors' own system for compressing, storing, and retrieving text, images, and textual images. mg's source code is freely available on the Web.
  elasticsearch index lifecycle management: Nature of Computation and Communication Cong Vinh Phan, Thanh Dung Nguyen, 2023-03-23 This book constitutes the refereed post-conference proceedings of the 8th EAI International Conference on Nature of Computation and Communication, ICTCC 2022, held in Vinh Long, Vietnam, in October 27-28 2022. The 11 revised full papers presented were carefully selected from 32 submissions. The papers of ICTCC 2022 cover formal methods for self-adaptive systems and discuss natural approaches and techniques for natural computing systems and their applications.
  elasticsearch index lifecycle management: Modern Big Data Processing with Hadoop V Naresh Kumar, Prashant Shindgikar, 2018-03-30 A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.
  elasticsearch index lifecycle management: Data Lake Development with Big Data Pradeep Pasupuleti, Beulah Salome Purra, 2015-11-26 Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies About This Book Comprehend the intricacies of architecting a Data Lake and build a data strategy around your current data architecture Efficiently manage vast amounts of data and deliver it to multiple applications and systems with a high degree of performance and scalability Packed with industry best practices and use-case scenarios to get you up-and-running Who This Book Is For This book is for architects and senior managers who are responsible for building a strategy around their current data architecture, helping them identify the need for a Data Lake implementation in an enterprise context. The reader will need a good knowledge of master data management and information lifecycle management, and experience of Big Data technologies. What You Will Learn Identify the need for a Data Lake in your enterprise context and learn to architect a Data Lake Learn to build various tiers of a Data Lake, such as data intake, management, consumption, and governance, with a focus on practical implementation scenarios Find out the key considerations to be taken into account while building each tier of the Data Lake Understand Hadoop-oriented data transfer mechanism to ingest data in batch, micro-batch, and real-time modes Explore various data integration needs and learn how to perform data enrichment and data transformations using Big Data technologies Enable data discovery on the Data Lake to allow users to discover the data Discover how data is packaged and provisioned for consumption Comprehend the importance of including data governance disciplines while building a Data Lake In Detail A Data Lake is a highly scalable platform for storing huge volumes of multistructured data from disparate sources with centralized data management services. This book explores the potential of Data Lakes and explores architectural approaches to building data lakes that ingest, index, manage, and analyze massive amounts of data using batch and real-time processing frameworks. It guides you on how to go about building a Data Lake that is managed by Hadoop and accessed as required by other Big Data applications. This book will guide readers (using best practices) in developing Data Lake's capabilities. It will focus on architect data governance, security, data quality, data lineage tracking, metadata management, and semantic data tagging. By the end of this book, you will have a good understanding of building a Data Lake for Big Data. Style and approach Data Lake Development with Big Data provides architectural approaches to building a Data Lake. It follows a use case-based approach where practical implementation scenarios of each key component are explained. It also helps you understand how these use cases are implemented in a Data Lake. The chapters are organized in a way that mimics the sequential data flow evidenced in a Data Lake.
  elasticsearch index lifecycle management: World Internet Development Report 2017 Chinese Academy of Cyberspace Studies, 2018-09-15 An important outcome of the Fourth World Internet Conference, this book provides a comprehensive account of the status quo and trends in global Internet development. Covering network infrastructure, information technology, digital economy, e-governance, cyber security, and international cyberspace governance, it presents the Global Internet Development Index System to assess the Internet development of various major countries and emerging economies.
  elasticsearch index lifecycle management: Mastering Elasticsearch - Second Edition Rafał Kuć, Marek Rogoziński, 2015-02-27 This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.
  elasticsearch index lifecycle management: Kafka: The Definitive Guide Neha Narkhede, Gwen Shapira, Todd Palino, 2017-08-31 Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you’ll learn Kafka’s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems
  elasticsearch index lifecycle management: Elasticsearch: The Definitive Guide Clinton Gormley, Zachary Tong, 2015-01-23 Whether you need full-text search or real-time analytics of structured data—or both—the Elasticsearch distributed search engine is an ideal way to put your data to work. This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships. If you’re a newcomer to both search and distributed systems, you’ll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, you’ll follow a problem-based approach to learn why, when, and how to use Elasticsearch features. Understand how Elasticsearch interprets data in your documents Index and query your data to take advantage of search concepts such as relevance and word proximity Handle human language through the effective use of analyzers and queries Summarize and group data to show overall trends, with aggregations and analytics Use geo-points and geo-shapes—Elasticsearch’s approaches to geolocation Model your data to take advantage of Elasticsearch’s horizontal scalability Learn how to configure and monitor your cluster in production
  elasticsearch index lifecycle management: Kubernetes for Full-Stack Developers , 2020-02-04 This book is designed to help newcomers and experienced users alike learn about Kubernetes. Its chapters are designed to introduce core Kubernetes concepts and to build on them to a level where running an application on a production cluster is a familiar, repeatable, and automated process. From there, more advanced topics are introduced, like how to manage a Kubernetes cluster itself.
  elasticsearch index lifecycle management: Strategic Blueprint for Enterprise Analytics Liang Wang,
  elasticsearch index lifecycle management: API Design Patterns JJ Geewax, 2021-08-17 A concept-rich book on API design patterns. Deeply engrossing and fun to read. - Satej Sahu, Honeywell API Design Patterns lays out a set of design principles for building internal and public-facing APIs. In API Design Patterns you will learn: Guiding principles for API patterns Fundamentals of resource layout and naming Handling data types for any programming language Standard methods that ensure predictability Field masks for targeted partial updates Authentication and validation methods for secure APIs Collective operations for moving, managing, and deleting data Advanced patterns for special interactions and data transformations API Design Patterns reveals best practices for building stable, user-friendly APIs. These design patterns can be applied to solve common API problems and flexibly altered to fit specific needs. Hands-on examples and relevant cases illustrate patterns for API fundamentals, advanced functionalities, and uncommon scenarios. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology APIs are contracts that define how applications, services, and components communicate. API design patterns provide a shared set of best practices, specifications and standards that ensure APIs are reliable and simple for other developers. This book collects and explains the most important patterns from both the API design community and the experts at Google. About the book API Design Patterns lays out a set of principles for building internal and public-facing APIs. Google API expert JJ Geewax presents patterns that ensure your APIs are consistent, scalable, and flexible. You’ll improve the design of the most common APIs, plus discover techniques for tricky edge cases. Precise illustrations, relevant examples, and detailed scenarios make every pattern clear and easy to understand. What's inside Guiding principles for API patterns Fundamentals of resource layout and naming Advanced patterns for special interactions and data transformations A detailed case-study on building an API and adding features About the reader For developers building web and internal APIs in any language. About the author JJ Geewax is a software engineer at Google, focusing on Google Cloud Platform, API design, and real-time payment systems. He is also the author of Manning’s Google Cloud Platform in Action. Table of Contents PART 1 INTRODUCTION 1 Introduction to APIs 2 Introduction to API design patterns PART 2 DESIGN PRINCIPLES 3 Naming 4 Resource scope and hierarchy 5 Data types and defaults PART 3 FUNDAMENTALS 6 Resource identification 7 Standard methods 8 Partial updates and retrievals 9 Custom methods 10 Long-running operations 11 Rerunnable jobs PART 4 RESOURCE RELATIONSHIPS 12 Singleton sub-resources 13 Cross references 14 Association resources 15 Add and remove custom methods 16 Polymorphism PART 5 COLLECTIVE OPERATIONS 17 Copy and move 18 Batch operations 19 Criteria-based deletion 20 Anonymous writes 21 Pagination 22 Filtering 23 Importing and exporting PART 6 SAFETY AND SECURITY 24 Versioning and compatibility 25 Soft deletion 26 Request deduplication 27 Request validation 28 Resource revisions 29 Request retrial 30 Request authentication
  elasticsearch index lifecycle management: Real-Time Analytics Byron Ellis, 2014-06-23 Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's recipe layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.
  elasticsearch index lifecycle management: IBM Cloud Pak for Data Hemanth Manda, Sriram Srinivasan, Deepak Rangarao, 2021-11-24 Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource management Key FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook Description Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise. What you will learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is for This book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.
  elasticsearch index lifecycle management: IBM Business Process Manager Operations Guide Bryan Brown, Karri S Carlson-Neumann, Mark Filley, Weiming Gu, Chris Richardson, Dave Spriet, Shuo Zhang, IBM Redbooks, 2016-12-16 This IBM® Redbooks® publication provides operations teams with architectural design patterns and guidelines for the day-to-day challenges that they face when managing their IBM Business Process Manager (BPM) infrastructure. Today, IBM BPM L2 and L3 Support and SWAT teams are constantly advising customers how to deal with the following common challenges: Deployment options (on-premises, patterns, cloud, and so on) Administration DevOps Automation Performance monitoring and tuning Infrastructure management Scalability High Availability and Data Recovery Federation This publication enables customers to become self-sufficient, promote consistency and accelerate IBM BPM Support engagements. This IBM Redbooks publication is targeted toward technical professionals (technical support staff, IT Architects, and IT Specialists) who are responsible for meeting day-to-day challenges that they face when they are managing an IBM BPM infrastructure.
  elasticsearch index lifecycle management: Engineering Resilient Systems on AWS Kevin Schwarz, Jennifer Moran, Nate Bachmeier, 2024-10-11 To ensure that applications are reliable and always available, more businesses today are moving applications to AWS. But many companies still struggle to design and build these cloud applications effectively, thinking that because the cloud is resilient, their applications will be too. With this practical guide, software, DevOps, and cloud engineers will learn how to implement resilient designs and configurations in the cloud using hands-on independent labs. Authors Kevin Schwarz, Jennifer Moran, and Dr. Nate Bachmeier from AWS teach you how to build cloud applications that demonstrate resilience with patterns like back off and retry, multi-Region failover, data protection, and circuit breaker with common configuration, tooling, and deployment scenarios. Labs are organized into categories based on complexity and topic, making it easy for you to focus on the most relevant parts of your business. You'll learn how to: Configure and deploy AWS services using resilience patterns Implement stateless microservices for high availability Consider multi-Region designs to meet business requirements Implement backup and restore, pilot light, warm standby, and active-active strategies Build applications that withstand AWS Region and Availability Zone impairments Use chaos engineering experiments for fault injection to test for resilience Assess the trade-offs when building resilient systems, including cost, complexity, and operational burden
  elasticsearch index lifecycle management: Elasticsearch in Action Roy Russo, Radu Gheorghe, Matthew Lee Hinman, 2015-11-17 Summary Elasticsearch in Action teaches you how to build scalable search applications using Elasticsearch. You'll ramp up fast, with an informative overview and an engaging introductory example. Within the first few chapters, you'll pick up the core concepts you need to implement basic searches and efficient indexing. With the fundamentals well in hand, you'll go on to gain an organized view of how to optimize your design. Perfect for developers and administrators building and managing search-oriented applications. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Modern search seems like magic—you type a few words and the search engine appears to know what you want. With the Elasticsearch real-time search and analytics engine, you can give your users this magical experience without having to do complex low-level programming or understand advanced data science algorithms. You just install it, tweak it, and get on with your work. About the Book Elasticsearch in Action teaches you how to write applications that deliver professional quality search. As you read, you'll learn to add basic search features to any application, enhance search results with predictive analysis and relevancy ranking, and use saved data from prior searches to give users a custom experience. This practical book focuses on Elasticsearch's REST API via HTTP. Code snippets are written mostly in bash using cURL, so they're easily translatable to other languages. What's Inside What is a great search application? Building scalable search solutions Using Elasticsearch with any language Configuration and tuning About the Reader For developers and administrators building and managing search-oriented applications. About the Authors Radu Gheorghe is a search consultant and software engineer. Matthew Lee Hinman develops highly available, cloud-based systems. Roy Russo is a specialist in predictive analytics. Table of Contents PART 1 CORE ELASTICSEARCH FUNCTIONALITY Introducing Elasticsearch Diving into the functionality Indexing, updating, and deleting data Searching your data Analyzing your data Searching with relevancy Exploring your data with aggregations Relations among documents PART 2 ADVANCED ELASTICSEARCH FUNCTIONALITY Scaling out Improving performance Administering your cluster
  elasticsearch index lifecycle management: Mastering Cloud Native Aditya Pratap Bhuyan, 2024-07-26 Mastering Cloud Native: A Comprehensive Guide to Containers, DevOps, CI/CD, and Microservices is your essential companion for navigating the transformative world of Cloud Native computing. Designed for both beginners and experienced professionals, this comprehensive guide provides a deep dive into the core principles and practices that define modern software development and deployment. In an era where agility, scalability, and resilience are paramount, Cloud Native computing stands at the forefront of technological innovation. This book explores the revolutionary concepts that drive Cloud Native, offering practical insights and detailed explanations to help you master this dynamic field. The journey begins with an Introduction to Cloud Native, where you'll trace the evolution of cloud computing and understand the myriad benefits of adopting a Cloud Native architecture. This foundational knowledge sets the stage for deeper explorations into the key components of Cloud Native environments. Containers, the building blocks of Cloud Native applications, are covered extensively in Understanding Containers. You'll learn about Docker and Kubernetes, the leading technologies in containerization, and discover best practices for managing and securing your containerized applications. The DevOps in the Cloud Native World chapter delves into the cultural and technical aspects of DevOps, emphasizing collaboration, automation, and continuous improvement. You'll gain insights into essential DevOps practices and tools, illustrated through real-world case studies of successful implementations. Continuous Integration and Continuous Deployment (CI/CD) are crucial for rapid and reliable software delivery. In the CI/CD chapter, you'll explore the principles and setup of CI/CD pipelines, popular tools, and solutions to common challenges. This knowledge will empower you to streamline your development processes and enhance your deployment efficiency. Microservices architecture, a key aspect of Cloud Native, is thoroughly examined in Microservices Architecture. This chapter highlights the design principles and advantages of microservices over traditional monolithic systems, providing best practices for implementing and managing microservices in your projects. The book also introduces you to the diverse Cloud Native Tools and Platforms, including insights into the Cloud Native Computing Foundation (CNCF) and guidance on selecting the right tools for your needs. This chapter ensures you have the necessary resources to build and manage robust Cloud Native applications. Security is paramount in any technology stack, and Security in Cloud Native Environments addresses the critical aspects of securing your Cloud Native infrastructure. From securing containers and microservices to ensuring compliance with industry standards, this chapter equips you with the knowledge to protect your applications and data. Monitoring and Observability explores the importance of maintaining the health and performance of your Cloud Native applications. You'll learn about essential tools and techniques for effective monitoring and observability, enabling proactive identification and resolution of issues. The book concludes with Case Studies and Real-World Applications, presenting insights and lessons learned from industry implementations of Cloud Native technologies. These real-world examples provide valuable perspectives on the challenges and successes of adopting Cloud Native practices. Mastering Cloud Native is more than a technical guide; it's a comprehensive resource designed to inspire and educate. Whether you're a developer, operations professional, or technology leader, this book will equip you with the tools and knowledge to succeed in the Cloud Native era. Embrace the future of software development and unlock the full potential of Cloud Native computing with this indispensable guide.
  elasticsearch index lifecycle management: Microsoft Azure Essentials - Fundamentals of Azure Michael Collier, Robin Shahan, 2015-01-29 Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. The first ebook in the series, Microsoft Azure Essentials: Fundamentals of Azure, introduces developers and IT professionals to the wide range of capabilities in Azure. The authors - both Microsoft MVPs in Azure - present both conceptual and how-to content for key areas, including: Azure Websites and Azure Cloud Services Azure Virtual Machines Azure Storage Azure Virtual Networks Databases Azure Active Directory Management tools Business scenarios Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the “Microsoft Azure Essentials” series.
Module 5 Elasticsearch Nodes and Index Management
How is a hot/warm architecture deployed? which we discuss next... 1. Tag the Nodes. 2. Configure the Hot Data. "index.routing.allocation.require.my_temp" : "hot" 3. Move Older …

Elasticsearch Diagnose & Index Lifecycle management Service
Jul 23, 2018 · • In broad terms, Index Management contains settings, operations and all the things during its lifecycle. Avoid improper ES usage. Query a bunch of indices by:

How to Handle Title Slides - Devopsschool.com
Index lifecycle management (ILM) We can configure index lifecycle management (ILM) policies to automatically manage indices according to your performance, resiliency, and retention …

Data Application Guide Elasticsearch Service
Index lifecycle management This is implemented through Elasticsearch's ILM feature. You can directly configure ILM policies for an autonomous index with no need to manage policies and …

SCALE YOUR CLUSTER - xeraa
ps: 7.0 improvement index.search.idle.after: 30s iff default index.refresh_interval 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4@xeraa

ELK Master Class - Elasticsearch, Beats, Logstash and Kibana
participants will learn about Elasticsearch's powerful Search and data indexing capabilities, Kibana's data visualization tools, Logstash's data processing pipelines, and how Beats …

Elasticsearch Index Lifecycle Management (Download Only)
CONTENTS 1 Getting Started with Elasticsearch 2 Installing Elasticsearch 3 Elastic Stack The Ecosystem of Elasticsearch 4 Preparing Data for Indexing 5 Importing Data into Elasticsearch …

Learning ELK Stack - api.pageplace.de
components—Elasticsearch, Logstash, and Kibana. Chapter 2 , Building Your First Data Pipeline with ELK , helps you build a basic ELK Stack pipeline using a CSV formatted input, and …

Data Application Guide Elasticsearch Service
Index lifecycle management This is implemented through Elasticsearch's ILM feature. You can directly configure ILM policies for an autonomous index with no need to manage policies and …

OPERATIONAL ANALYTICS Analytics in 15 - Amazon Web …
shard and index lifecycle management . Fast. Automatically scale resources to maintain consistently fast data ingestion rates and query response times . Ecosystem. Get started in …

Elastic Observability© Certification Training
Our Elastic Observability© training course provides you with the knowledge and skills you need to pass the exam. It covers in depth all the topics mentioned in the exam syllabus, providing …

ELK Master Class - Elasticsearch, Beats, Logstash and Kibana
Course Objec1ve: Understanding the ELK Stack - Elas5csearch, Logstash, Kibana, and Beats. Learn installa5on, configura5on, and prac5cal use of each component for efficient data …

Elasticsearch Index Lifecycle Management (2024)
CONTENTS 1 Getting Started with Elasticsearch 2 Installing Elasticsearch 3 Elastic Stack The Ecosystem of Elasticsearch 4 Preparing Data for Indexing 5 Importing Data into Elasticsearch …

JuiceFS 在Elasticsearch 的冷热数据分层实践
Index Lifecycle Management (ILM) •ILM 定义了索引⽣命周期的5 个阶段 •热数据（Hot）：频繁更新和查询的数据 •温数据（Warm）：不再更新，但仍会被较频繁查询的数据 •冷数 …

Enterprise Vault™ Indexing Best Practices: 14 - Veritas
Enterprise Vault 14.2 and later introduces a new 64-bit Elasticsearch indexing engine. The new features and functionality of this engine need to be considered by both existing customers …

The Expert’s Guide to Running Elasticsearch on Kubernetes
• Designing Elasticsearch clusters for High Availability (HA) and optimal performance using Elasticsearch best practices • Implementing storage-aware scheduling and HA • Ways to …

Migrating to the Elastic Stack Guide - piyanit.nl
Finally, index lifecycle management (ILM) can be used to define index lifecycle policies to roll over older indices to lower-cost storage or delete old data in a predefined way. • Use ingest nodes …

Security Onion Certified Professional (SOCP)
Topics for this section include but are not limited to: user management, firewall management, key components of SaltStack, and configuring several core components of the various Security …

ELK Stack Deployment with Ansible - CERN
As the Elasticsearch cluster accumulates data, the num-ber of indices can grow substantially. Curator can be used to manage the lifecycle of indices, such as closing or delet-ing old indices …

Build a Centralized Log Analytics Platform with Amazon …
Delivers high-quality and personalized search results to customers. You get access to all of Elasticsearch’s search APIs, supporting natural language search, auto-completion, faceted …

Module 5 Elasticsearch Nodes and Index Management
How is a hot/warm architecture deployed? which we discuss next... 1. Tag the Nodes. 2. Configure the Hot Data. "index.routing.allocation.require.my_temp" : "hot" 3. Move Older …

Elasticsearch Diagnose & Index Lifecycle management …
Jul 23, 2018 · • In broad terms, Index Management contains settings, operations and all the things during its lifecycle. Avoid improper ES usage. Query a bunch of indices by:

How to Handle Title Slides - Devopsschool.com
Index lifecycle management (ILM) We can configure index lifecycle management (ILM) policies to automatically manage indices according to your performance, resiliency, and retention …

Data Application Guide Elasticsearch Service
Index lifecycle management This is implemented through Elasticsearch's ILM feature. You can directly configure ILM policies for an autonomous index with no need to manage policies and …

SCALE YOUR CLUSTER - xeraa
ps: 7.0 improvement index.search.idle.after: 30s iff default index.refresh_interval 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4@xeraa

ELK Master Class - Elasticsearch, Beats, Logstash and Kibana
participants will learn about Elasticsearch's powerful Search and data indexing capabilities, Kibana's data visualization tools, Logstash's data processing pipelines, and how Beats …

Elasticsearch Index Lifecycle Management (Download Only)
CONTENTS 1 Getting Started with Elasticsearch 2 Installing Elasticsearch 3 Elastic Stack The Ecosystem of Elasticsearch 4 Preparing Data for Indexing 5 Importing Data into Elasticsearch …

Learning ELK Stack - api.pageplace.de
components—Elasticsearch, Logstash, and Kibana. Chapter 2 , Building Your First Data Pipeline with ELK , helps you build a basic ELK Stack pipeline using a CSV formatted input, and …

Data Application Guide Elasticsearch Service
Index lifecycle management This is implemented through Elasticsearch's ILM feature. You can directly configure ILM policies for an autonomous index with no need to manage policies and …

OPERATIONAL ANALYTICS Analytics in 15 - Amazon Web …
shard and index lifecycle management . Fast. Automatically scale resources to maintain consistently fast data ingestion rates and query response times . Ecosystem. Get started in …

Elastic Observability© Certification Training
Our Elastic Observability© training course provides you with the knowledge and skills you need to pass the exam. It covers in depth all the topics mentioned in the exam syllabus, providing …

ELK Master Class - Elasticsearch, Beats, Logstash and Kibana
Course Objec1ve: Understanding the ELK Stack - Elas5csearch, Logstash, Kibana, and Beats. Learn installa5on, configura5on, and prac5cal use of each component for efficient data …

Elasticsearch Index Lifecycle Management (2024)
CONTENTS 1 Getting Started with Elasticsearch 2 Installing Elasticsearch 3 Elastic Stack The Ecosystem of Elasticsearch 4 Preparing Data for Indexing 5 Importing Data into Elasticsearch …

JuiceFS 在Elasticsearch 的冷热数据分层实践
Index Lifecycle Management (ILM) •ILM 定义了索引⽣命周期的5 个阶段 •热数据（Hot）：频繁更新和查询的数据 •温数据（Warm）：不再更新，但仍会被较频繁查询的数据 •冷数 …

Enterprise Vault™ Indexing Best Practices: 14 - Veritas
Enterprise Vault 14.2 and later introduces a new 64-bit Elasticsearch indexing engine. The new features and functionality of this engine need to be considered by both existing customers …

The Expert’s Guide to Running Elasticsearch on Kubernetes
• Designing Elasticsearch clusters for High Availability (HA) and optimal performance using Elasticsearch best practices • Implementing storage-aware scheduling and HA • Ways to …

Migrating to the Elastic Stack Guide - piyanit.nl
Finally, index lifecycle management (ILM) can be used to define index lifecycle policies to roll over older indices to lower-cost storage or delete old data in a predefined way. • Use ingest nodes …

Security Onion Certified Professional (SOCP)
Topics for this section include but are not limited to: user management, firewall management, key components of SaltStack, and configuring several core components of the various Security …

ELK Stack Deployment with Ansible - CERN
As the Elasticsearch cluster accumulates data, the num-ber of indices can grow substantially. Curator can be used to manage the lifecycle of indices, such as closing or delet-ing old indices …

Build a Centralized Log Analytics Platform with Amazon …
Delivers high-quality and personalized search results to customers. You get access to all of Elasticsearch’s search APIs, supporting natural language search, auto-completion, faceted …