Course: Maintaining Elasticsearch in Production Learn how to monitor and maintain a stable Elasticsearch cluster in production

Maintaining Elasticsearch in Production

Learn how to monitor and maintain a stable Elasticsearch cluster in production


This 1-day course is aimed at developers and operations people who need to be able to maintain Elasticsearch clusters in production. In this course you will learn about the various parts that make up a cluster, how it operates, and many do's and don'ts learned by experience over the years.

Objectives

The goal of this course is to make sure you can maintain a stable cluster regardless of the load you put on it.

  • Performance, sizing, scaling out and multi-tenancy
  • Designing the right cluster topology
  • How to monitor the cluster health
  • Understand the various configurations behind the cluster
  • Maintenance and troubleshooting
  • Integration with clouds (AWS, GCP, Azure)
  • Security

Prerequisites

Developers with 1 year of experience or more. Previous hands-on experience with Elasticsearch required - or completion of the 'Elasticsearch for Developers' course.

Modules

  Module 1 - Elasticsearch under the hood
  • Lucene indexes, shards and replicas
  • The inverted index structure
  • FieldData, DocValues and TermVectors
  • Indexing, durability guarantees and it's effects on search
  Module 2 - Scaling out
  • Elasticsearch Nodes and their roles
  • What it means to scale out
  • The Cluster State
  • Routing
  • Distributed search execution and search types
  • Shard allocation control
  • Tribe nodes
  • Installation and security
  • Working with cloud environments
  • Designing the cluster topology
  Module 3 - Deployment, Installation and Security
  • Installation, cluster configurations, and gotchas
  • Deploying on the cloud
  • Pre-flight checklist
  • Security
  • Performing upgrades
  • Configurations and cluster state during normal operation
  • Snapshot and restore
  Module 4 - Monitoring
  • What to monitor?
  • Elasticsearch's configurations and metrics
  • Monitoring the cluster health, and knowing when to react
  • Tweaking configuraitons without risking cluster stability
  • Hard and soft limits
  • Caches and cache invalidation
  Module 5 - Data ingestion architecture
  • What you should use Elasticsearch for
  • Optimal shard size
  • Index Templates and Aliases
  • Index management patterms
  • Logstash, Beats and Ingest Nodes
  • Document versioning and syncing with external data sources

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