Course Code:
elk
Duration:
7 hours
Prerequisites:
There are no specific requirements needed to attend this course.
Course Outline:
Introduction
- Elastic Stack Overview (ELK)
- Metrics use case
- Elasticsearch
Filebeats
- Logs and problems
- Filebeat architecture
- Installation and configuration
- Backup and restore
- Cluster and availability nuances
- Best practices
Logstash
- What and Why
- Configuration
- Inputs, Filters, and Outputs
- Installation and configuration
- Backup and restore
- Cluster and availability nuances
- Best practices
Elasticsearch:
Overview:
- ∙ What and Why
- ∙ Terminology: Documents, Index, Shards, Node, Cluster, Scale Up/Out
Operate: Configuring & Deploying
- ∙ Configuring Elasticsearch
- ∙ Deploying Elasticsearch
- ∙ Lab
Node: Discovery, Types, and Cluster State
- ∙ Distributed Model and Discovery
- ∙ Master, Data, Client, and Tribe Nodes
- ∙ Master Election and Minimum Master Nodes
- ∙ Cluster State
- ∙ Shard Allocation
Backup: Snapshot and Restore
- ∙ High Availability vs. Backup
- ∙ Repository, Snapshot, and Restore
- ∙ Internals
Production Monitoring
- ∙ Alerting Best Practices
- ∙ JVM
- ∙ Query Performance
- ∙ Thread Pools
- ∙ Diagnosing Problems
Production Operational Best Practices
- ∙ Memory
- ∙ Networking
- ∙ Disk
- ∙ Security
- ∙ Cluster Restart (Rolling and Full)
Kibana
- What and Why
- Configuration Settings
- Time Picker, Search, and Filters
- Kibana Discover, Visualization, and Dashboard Interfaces
- Installation and configuration
- Backup and restore
- Cluster and availability nuances
- Best practices