Advanced ELK Stack for Log Management and Centralization

• An understanding of the basic ELK Stack architecture and components
• Experience with ingesting and visualizing logs using Kibana and Logstash
• Familiarity with Linux command line and basic scripting

Audience

• System administrators
• Infrastructure engineers
• Technical teams seeking advanced log centralization capabilities

Elastic Stack (ELK) is a powerful platform for searching, analyzing, and visualizing log data in real-time from multiple sources.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT professionals who wish to deepen their ELK expertise for managing distributed log data, automating alerts, and creating advanced visualizations and dashboards.

By the end of this training, participants will be able to:

• Configure advanced ingestion and parsing flows from multiple sources including databases.
• Create customized Kibana dashboards for different teams or use cases.
• Implement email notifications and condition-based alerts.
• Use regular expressions to improve search precision in logs.
• Manage user roles and access rights for secure log environments.
• Interact with the Elasticsearch REST API for automation and integration.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction

• General overview of the Elastic Stack (ELK)

Module 1: ELK Stack Architecture and Review of Existing Environment

• Review of the current architecture of Altor CB
• ELK architecture: Elasticsearch, Logstash, Kibana, Beats
• Ingest node vs. Logstash
• Scalability and performance considerations in on-premise installations
• Administration best practices

Module 2: Beats – Distributed Monitoring (2 hours)

• Configuration and use of Filebeat, Auditbeat, Winlogbeat, and Packetbeat
• Secure shipping with SSL
• Preconfigured modules vs. custom inputs
• Integration with Logstash and Ingest Pipelines

Module 3: Parsing and Ingesting Logs from Applications and Databases (4 hours)

• Ingesting custom logs from applications
• Using Logstash for data parsing and transformation
• Use of filters: grok, dissect, kv, mutate, date
• Database connections (Oracle, PostgreSQL, SQL Server) using JDBC input plugin
• Practical cases: error logs, audit trails, traces, slow queries

Module 4: Advanced Search and Regular Expressions (2 hours)

• Advanced search syntax in Kibana
• Use of regular expressions (regex)
• Filters and OR/AND combinations
• Nested fields and arrays
• Saving reusable queries and filters

Module 5: Custom Dashboards and Visualizations in Kibana (3 hours)

• Visualization types: bar, line, maps, tables
• Aggregations and metrics
• Dynamic filters, controls, and drill-down features
• Dashboard sharing
• Exercises: creating dashboards from database and system logs

Module 6: Alerts and Email Notifications (3 hours)

• Introduction to Watcher and alternatives (ElastAlert, Kibana Alerts)
• Creating custom conditions and triggers
• Email output configuration
• Exercise: send alert when a critical event is detected in Windows or database logs

Module 7: User and Permission Management (2 hours)

• Introduction to X-Pack and free options
• Creating users and roles
• Access control by index, dashboard, and query
• Exercise: define roles for audit and operations

Module 8: Elasticsearch REST API (3 hours)

• Foundations of Elasticsearch RESTful API
• GET / POST queries
• Manual and automated indexing
• Using tools like curl and Postman
• Exercises: searching, inserting, deleting, and updating documents

Summary and Next Steps