What this book covers
Chapter 1, Getting Started – Installing the Elastic Stack, explores the installation of the Elastic Stack across environments such as Elastic Cloud and Kubernetes, detailing the setup for Elasticsearch, Kibana, and Fleet along with insights on cluster components and deployment strategies for stack optimization.
Chapter 2, Ingesting General Content Data, dives into the data ingestion process, focusing on indexing, updating, and deleting operations within Elasticsearch, and emphasizes analyzers, index mappings, and templates for effective Elasticsearch index management.
Chapter 3, Building Search Applications, guides you through constructing search experiences using Elasticsearch’s Query DSL and new features in Elastic Stack 8, culminating in comprehensive search applications with advanced queries and analytics.
Chapter 4, Timestamped Data Ingestion, delves into data transformation using Elastic Stack tools, instructing on data structuring, enrichment, reorganization, and downsampling, while utilizing ingest pipelines, processors, Transforms, and Logstash.
Chapter 5, Transform Data, delves into data transformation techniques using Elastic Stack tools. You will learn how to structure, enrich, reorganize, and downsample your data to glean actionable insights. This chapter delivers practical know-how on utilizing ingest pipelines, processors, transforms, and Logstash for efficient data manipulation.
Chapter 6, Visualize and Explore Data, shows how to turn transformed data into visualizations, teaching data exploration in Discover, visual creation with Kibana Lens, and the use of dashboards and maps to deeply understand your data.
Chapter 7, Alerting and Anomaly Detection, outlines the setup of alerts and anomaly detection for proactive data management, covering alert creation and monitoring, anomaly investigation, and unsupervised machine learning job implementation.
Chapter 8, Advanced Data Analysis and Processing, delves into machine learning within the Elastic Stack, covering outlier detection, regression, and classification modeling, as well as deploying NLP models for deep data insights.
Chapter 9, Vector Search and Generative AI Integration, explores advanced search technologies and AI integrations, teaching you about vector search, hybrid search, and Generative AI applications for developing sophisticated AI-driven conversational tools.
Chapter 10, Elastic Observability Solution, demonstrates how to employ the Elastic Stack for comprehensive system insights, covering application instrumentation, real-user monitoring, Kubernetes observability, synthetic monitors, and incident detection.
Chapter 11, Managing Access Control, navigates access control within the Elastic Stack, detailing authentication management, custom role definition, Kibana space security, API key utilization, and single sign-on implementation.
Chapter 12, Elastic Stack Operation, provides essential recipes for Elastic Stack management, such as index life cycle, data stream optimization, and snapshot life cycle management, and explores cluster automation with Terraform and cross-cluster search.
Chapter 13, Elastic Stack Monitoring, equips you with techniques for Elastic Stack monitoring and troubleshooting, focusing on the stack monitoring setup, custom visualization creation, cluster health assessment, and audit logging strategies.
