Preface

OpenSearch is a “Swiss Army knife” that touches diverse use cases spanning application features, operations, and generative AI. If there’s one unifying theme of the software, it is that it enables storing and retrieving data to support intelligent decision-making. It’s a database, but it’s a funny kind of database that emphasizes speed and volume processing over consistency. It’s a logs store, but a funny kind of logs store that emphasizes aggregations and log-line search. It’s a data source for generative AI, but it’s a funny kind of data source that brings rich search to the retrieval of information for prompts. In all these cases, OpenSearch provides high-volume request processing and intelligent retrieval of data.

In this book, you’ll learn in depth the capabilities of OpenSearch, how and when to apply them, and where you can get the most benefits. You’ll also learn about Amazon OpenSearch Service, its managed clusters and serverless deployment options, and how to get the most out of your OpenSearch Service domain or OpenSearch Serverless collection.

We’ll begin with introductory chapters that give you a history and overview of OpenSearch and show you how to deploy OpenSearch and how to use OpenSearch Service. We’ll then dive deep into OpenSearch’s core capabilities—indexing and querying data and building aggregations and visualizations. We’ll cover OpenSearch’s large collection of plugins that deliver additional features, such as Structured Query Language (SQL), alerting, and k-nearest neighbor search. We’ll dive deep into application-building and delivering AI-powered applications with generative AI. We will then move on to operational topics, including migrations, security, monitoring, backups, and recovery. We will round out the book with a deep dive on scaling and performance optimization.

In writing this book, we wanted to distill our years of experience and thousands of hours of customer interaction for you. We wish you every success, and happy OpenSearching!