Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Elastic Stack
- Introduction to the Elastic Stack
- Overview of the Product Landscape
- Enterprise Search Solutions
- Core Elastic Concepts
- Elastic Terminology
- Nodes and Node Roles
- Scalability and Resilience
- Application Scenarios: When, Where, Pros, and Cons
- How the Search Engine Works
- Elastic Setup
- Prerequisites and Installation Steps
- Configuration Files and Key Settings
- Elastic Cluster Principles
- Discovery and Cluster Formation
- Master Election, Split-Brain Issues, and Cluster Bootstrapping
- Cluster State and Shard Allocation
- High Availability and Backup Strategies
- Cross-Cluster Replication
- Index Templates and Mappings
- Security and Encryption Configuration
- Operational Configurations and Best Practices
- Heap Size Management
- Shard Size Optimization
- Shard Count Considerations
- Hot-Warm-Cold Architecture
- Linux Server-Specific Settings
- Index Rollover
- Cluster Settings
- Text Analytics
- Query DSL
- Normalizers and Tokenizers
Kibana
- Purpose and Value
- Kibana Terminology and Components
- Best Practices
- Kibana Setup
- Prerequisites and Installation Steps
- Configuration Files and Key Settings
Logstash
- Purpose and Value
- Logstash Queues
- High Availability and Failure Resilience Design
- Logstash Troubleshooting
- Common Filter Plugins and Use Cases
- Best Practices
- Logstash Setup
- Prerequisites and Installation Steps
- Configuration Files and Key Settings
- Filebeat
- Core Concepts
- Configuration Files and Settings
- Filebeat Installation and Directory Structure
- Processors
- Bonus:
Production Best Practices and Strategies to Reduce MTTR
Requirements
Foundational knowledge of Linux commands and system administration. Understanding of networking principles, including IP addressing and ports. Proficiency with text editors and command-line interfaces. Familiarity with common data formats such as JSON, XML, and CSV. Awareness of data analytics and visualization methodologies. Knowledge of concepts related to clusters, nodes, and storage systems.
28 Hours
Testimonials (1)
the practice learning
