Practical Elastic Stack Piotr Ziental
- Autor:
- Piotr Ziental
- Wydawnictwo:
- BPB Publications
- Ocena:
- Stron:
- 434
- Dostępne formaty:
-
ePubMobi
Opis
książki
:
Practical Elastic Stack
Description
Every device in a network, from routers to applications and IoT devices, produces large volumes of logs, metrics, and traces. Commercial observability systems can process this, but they often mean long contracts, higher costs, and sensitive data leaving the company. The Elastic Stack is the leading open-source solution for log management, system security, and enterprise observability. Practical Elastic Stack is your hands-on guide to mastering this powerful technology, designed to help you transform raw log data and security events into actionable operational intelligence.
Beginning with foundational concepts and hands-on installation, this practical guide walks through core architectural concepts, installation methods, and cluster setup across Linux, Windows, and Docker. You will master data transformation pipelines using Logstash, visualize live data, and build interactive dashboards in Kibana. It also covers agent management with Elastic Fleet, application monitoring with APM, and security monitoring with SIEM, with event correlation and detection rules in Kibana. You will learn to leverage the stack for security threat monitoring and set up automated alerting.
By the end of this book, readers will know what distinguishes monitoring from observability and how to build a scalable platform on their network. Upon completing this practical guide, readers possess the real-world skills to design, deploy, and optimize production-ready Elastic Stack environments to solve complex monitoring and security challenges. What you will learn
Parse logs from any source into structured ECS documents.
Build Kibana dashboards to explore and visualize data.
Manage Beats agents centrally through Elastic Fleet.
Detect security threats by correlating events in Kibana.
Forecast trends and spot anomalies with machine learning. Who this book is for
This book is written for students, DevOps engineers, SREs, security analysts, system administrators, and software developers building in-house observability. Basic familiarity with Linux administration, networking concepts, and Docker containers is helpful, but no prior experience with the Elastic Stack is required. Table of Contents
1. Introduction to the Elastic Stack
2. Installation and Configuration of Elastic Stack Components
3. Data Processing and Transformation with Logstash
4. Data Visualization and Analysis with Kibana
5. Collecting Data from Diverse Sources with Beats
6. Security Monitoring with Elastic Stack
7. Centralized Agent Management with Elastic Fleet
8. Application Monitoring with Elastic Stack
9. Scaling and Optimizing the Elastic Stack
10. Machine Learning in Elasticsearch
11. Achieving Observability and Future of Elastic Stack
Every device in a network, from routers to applications and IoT devices, produces large volumes of logs, metrics, and traces. Commercial observability systems can process this, but they often mean long contracts, higher costs, and sensitive data leaving the company. The Elastic Stack is the leading open-source solution for log management, system security, and enterprise observability. Practical Elastic Stack is your hands-on guide to mastering this powerful technology, designed to help you transform raw log data and security events into actionable operational intelligence.
Beginning with foundational concepts and hands-on installation, this practical guide walks through core architectural concepts, installation methods, and cluster setup across Linux, Windows, and Docker. You will master data transformation pipelines using Logstash, visualize live data, and build interactive dashboards in Kibana. It also covers agent management with Elastic Fleet, application monitoring with APM, and security monitoring with SIEM, with event correlation and detection rules in Kibana. You will learn to leverage the stack for security threat monitoring and set up automated alerting.
By the end of this book, readers will know what distinguishes monitoring from observability and how to build a scalable platform on their network. Upon completing this practical guide, readers possess the real-world skills to design, deploy, and optimize production-ready Elastic Stack environments to solve complex monitoring and security challenges. What you will learn
Parse logs from any source into structured ECS documents.
Build Kibana dashboards to explore and visualize data.
Manage Beats agents centrally through Elastic Fleet.
Detect security threats by correlating events in Kibana.
Forecast trends and spot anomalies with machine learning. Who this book is for
This book is written for students, DevOps engineers, SREs, security analysts, system administrators, and software developers building in-house observability. Basic familiarity with Linux administration, networking concepts, and Docker containers is helpful, but no prior experience with the Elastic Stack is required. Table of Contents
1. Introduction to the Elastic Stack
2. Installation and Configuration of Elastic Stack Components
3. Data Processing and Transformation with Logstash
4. Data Visualization and Analysis with Kibana
5. Collecting Data from Diverse Sources with Beats
6. Security Monitoring with Elastic Stack
7. Centralized Agent Management with Elastic Fleet
8. Application Monitoring with Elastic Stack
9. Scaling and Optimizing the Elastic Stack
10. Machine Learning in Elasticsearch
11. Achieving Observability and Future of Elastic Stack
Szczegóły książki
- ISBN Ebooka:
- 978-93-785-4795-9, 9789378547959
- Data wydania ebooka :
-
2026-09-11
Data wydania ebooka często jest dniem wprowadzenia tytułu do sprzedaży i może nie być równoznaczna
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- Język publikacji:
- angielski
- Rozmiar pliku ePub:
- 10.8MB
- Rozmiar pliku Mobi:
- 10.8MB
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Informatyka » Bazy danych
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Informatyka » Biznes IT » Big data
Informatyka » Bazy danych » Inne
Informatyka » Podręczniki szkolne
Informatyka » Biznes IT » Big data » Power BI
Informatyka » Biznes IT » Big data » Analiza danych
Informatyka » Bazy danych » PostgreSQL
Informatyka » Bazy danych » SQL
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