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Monitoring and Administering Elasticsearch

Diagnose and Troubleshoot Elasticsearch Clusters


Our Elasticsearch training classes have a 4.74/5 rating based on 20 reviews

This online course offers a clear and deep understanding of Elasticsearch’s management APIs and exposed metrics. It covers everything from backups to upgrades, to how one can diagnose and troubleshoot an Elasticsearch cluster. You’ll also bridge the gap between having proper Elasticsearch monitoring in place and understanding how to diagnose and troubleshoot the cluster. Radu Gheorghe, a seasoned Elasticsearch instructor, and consultant from Sematext, author of “Elasticsearch in Action”, and frequent conference speaker will be your trainer.

Why attend?

  • Small, interactive, instructor-led classes
  • Lots of hands-on exercises
  • Customized learning experience
  • More flexible – no need to travel
  • Certificate of Completion included

What’s Included

  • 2-hour online training
  • A digital copy of the training material
  • Docker Compose files, configs, scripts, etc.
  • Certificate of Completion

Next Class: TBA See Upcoming Classes

$200.00 -10% Early Bird Register Now

Full day classes available upon request

Looking for a more general and extended knowledge-based Elasticsearch training?

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Who should attend?

This Elasticsearch online course is designed for anyone operating Elasticsearch clusters:

  • A good understanding of core concepts (indices, shards, replicas, nodes) is required
  • This class dives deep under the hood of how Elasticsearch uses system resources, how nodes communicate to each other, etc.

What attendees say

Sematext was an ideal training partner for We had just recently adopted Elasticsearch on a new project, and they gave us two days of solid training that was tailored to our team’s needs. The material was built atop strong foundations and moved quickly into advanced areas around querying, Lucene internals, and cluster performance. It was clear that it was all informed by real-world experience operating these systems at scale.

Andrew Montalenti CTO/Founder –

Course Outline

Monitoring Elasticsearch
  • Using and understanding the health and stats APIs and their outputs
  • Overview of the most important Cat APIs and metrics they provide
  • How, when, and why to collect hot threads
  • Which metrics to monitor, how to interpret them, and what actions they call for
  • Configure logging and using slowlogs to catch non-performant queries
  • Lab
    • Using CAT APIs to get information about the current state of the cluster
    • Fetching the cluster state to estimate load on master nodes
    • Configuring logging and slowlogs
Administering Elasticsearch
  • Predefining index mappings and settings through templates
  • Moving queries from code to configuration via search templates
  • Identify and cancel long-running operations via task management
  • How to do cluster restarts properly to minimize downtime and inconsistencies
  • Rolling upgrades vs full cluster upgrades. When to do which.
  • How snapshots work and how to perform them to minimize backup time and data loss
  • Control chatter between nodes through allocation settings: options and trade-offs
  • Lab
    • Setting up multiple index templates with different orders
    • Making sure cluster starts recovery when enough nodes are up
    • Avoiding the domino effect when a node goes down via allocation settings

Main Topics

  • Cat APIs and JSON APIs
  • Which Elasticsearch metrics to watch and alert on
  • Logging, slow logs
  • Index and search templates
  • Snapshot and restore
  • Elasticsearch cluster restarts and upgrades

Elasticsearch Training

Upcoming Classes

Pick from a wide range of short (2h), use case focused classes to match your exact needs. Delivery method: Live Online. Time: 11:00 AM to 1:00 PM ET.

To be announced
Radu Gheorghe

About the trainer

Radu Gheorghe

Your trainer is an active Elasticsearch consultant. Radu has worked with clients from 20+ different industries and is the author of Elasticsearch in Action. Here are some problems that Radu solved for Sematext clients recently:

  • Improved search relevancy using Learning to Rank
  • Optimized multiple petabyte-scale clusters. Some up to 400 nodes.
  • Designed Elasticsearch index and cluster architecture for dozens of clients
  • Optimized log ingestion pipelines to parse and enrich 100K+ events/second
  • Helped clients reduce production Elasticsearch and ingestion pipeline costs by as much as 10x

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