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Elasticsearch Scaling

Learn How to Scale Elasticsearch

Rating 

Our Elasticsearch training classes have a 4.67/5 rating based on 15 reviews

This Elasticsearch class will give you a clear picture of how you should design your cluster in terms of number of nodes, shards and replicas. It will help you scale Elasticsearch efficiently from the PoC stage to a level that will fit most use-cases. If you need to scale Elasticsearch, this class will answer most of your questions: how do I choose the right number of shards and replicas? Do I need dedicated master nodes? What about client nodes? How many nodes should I start with? This Elasticsearch online course is taught by Radu Gheorghe‌‌, a seasoned Elasticsearch instructor and consultant from Sematext, author of “Elasticsearch in Action”, and frequent conference speaker.

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: Sept 19 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 who:

  • Is already using Elasticsearch or has a basic understanding of it
  • Wants to understand how to scale the cluster in an efficient and fault-tolerant way.

What attendees say

Sematext was an ideal training partner for Parse.ly. 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 – Parse.ly

Course Outline

Elasticsearch scaling basics
  • How nodes join a cluster: choosing unicast settings
  • Choosing the right number of shards and replicas for your use-case
  • How shards get rebalanced when nodes are added and removed
  • Node roles: when to have a dedicated master, ingest and client nodes
  • How to configure the minimum number of master nodes and why
  • Lab
    • Adding nodes to the cluster
    • Changing the number of shards and replicas
    • Deploy a cluster with a dedicated master, data and client nodes
Designing Elasticsearch for scale
  • When to use time-based indices and why
  • When size-based indices are helpful, and which size thresholds are good
  • APIs making rolled indices easier: aliases, rollover
  • Different nodes/hardware for different workloads: multi-tiered cluster architecture
  • When one cluster just can’t cut it: cross-cluster search
  • High availability across multiple racks, availability zones, etc
  • Lab
    • Deploy a tiered cluster
    • Deploy a cluster across multiple availability entities
    • Set up and run cross-cluster search

Main Topics

  • Elasticsearch node roles
  • When to add more shards, when to add more replicas
  • Time- and size-based indices
  • Multi-tiered Elasticsearch clusters
  • High-availability Elasticsearch clusters
  • Cross-cluster search

Elasticsearch Training

Upcoming Classes

Pick from a wide range of short (2h), use case focused classes to match your exact needs

DateClassPriceRegistration
Sept 19, 2019Elasticsearch Scaling$200 / person Only $180 / person before 20 JulyRegister Now
Dec 5, 2019Elasticsearch Scaling$200 / person Only $180 / person before 30 SeptRegister Now
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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