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OpenSearch Operations

Tune and Scale Your OpenSearch Clusters

If you are looking to administer, tune and scale clusters, in this class you will learn everything you need to handle your OpenSearch clusters in production – from use-case-specific cluster and index designs to tuning queries, settings, commits, thread pools and all the way to JVM, OS and hardware specifics.

Your trainer is an active OpenSearch consultant who worked with clients from many different industries on OpenSearch, Elasticsearch and Solr projects for 10+ years.

See Course Outline

What's Included

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

Who should attend?

This OpenSearch course is designed for technical attendees with basic OpenSearch experience. A person should be able to index data to OpenSearch, run queries and aggregations, work with mappings and analysis.

Experience with Linux systems is not a must, but a basic familiarity with running shell commands (e.g., using curl command) will make the course more enjoyable. If you do not have prior OpenSearch experience, we strongly suggest you consider attending our Intro to OpenSearch class first.

Why attend?

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

Get Certified Upon Course Completion

Enroll in our course and take the next step in your professional journey.
Complete the course and receive a certificate that showcases your newly acquired skills.

Learn More

Upcoming Classes

Pick from our 8h online classes, structured to correspond to different roles and Elasticsearch knowledge levels: for beginners to experienced developers or ops who want to learn quickly. Delivery method: Live Online. Time: 09:00 AM – 01:00 PM ET (2 sessions).

opensearch OpenSearch Operations
May 29-30, 2024
$800 / personSee Course OutlineRegister Now!

Course Outline

Scaling basics
  • Bootstrapping and discovery
  • Number of shards and replicas
  • Node roles
  • Lab
    • Set up a cluster; adjust number of shards and replicas for a new index
    • Set up dedicated cluster manager, data and coordinating nodes in a cluster
Designing for scale
  • Time-based indices and aliases
  • Shard allocation
  • Cross-cluster search
  • Lab
    • Roll time-based indices by size
    • Create a multi-tier cluster
    • Set up a cluster to work across availability zones
Cluster maintenance
  • Index and search templates
  • Snapshot and restore
  • Upgrades and cluster restarts
  • Shard allocation troubleshooting
  • Lab
    • Set up index templates
    • Adjust initial recovery settings
    • Adjust rebalancing settings
    • Perform a cluster upgrade
    • Snapshot and restore an index
Troubleshooting and profiling
  • Health and stats APIs
  • Cat APIs
  • Monitoring products
  • Logging
  • Task management
  • Hot threads API
  • Query profiling
  • Lab
    • Use JSON and Cat APIs to get information about the state of the cluster
    • Set up slowlogs
    • Profile a query from the slowlog
    • Reindex data from one index to another
Performance bottlenecks
  • Heap size vs OS caches
  • Garbage collection
  • OpenSearch-specific memory usage and caches
  • Hardware considerations
  • Lab
    • Pick up the right hardware for a use-case
    • Size the heap correctly
    • Tune the garbage collector for more throughput
    • Adjust cache sizing for a use-case
Tuning indexing and queries
  • How often to commit: translog, index buffer and refresh interval
  • How data is stored: merge policies
  • Routing
  • Thread pools
  • Lab
    • Set up routing
    • Adjust refresh, flush and merge settings
    • Adjust thread pool size and queue sizes

Main Topics

  • Scaling with Different Node Types, Multi-Tier and Multi-Cluster Architectures
  • Efficient Index Designs for Enterprise and Time-Series Search
  • Tuning Caches, Merge Policies and Other OpenSearch, JVM and OS Settings
  • Monitoring: Relevant Metrics to Watch and How to React to Them
  • Maintenance: Aliases, Snapshots, Recovery, Upgrades, etc

Course key takeaways

After taking this course you will learn about:

  • Everything you need to handle your OpenSearch clusters in production: from tuning OS and JVM for performance through commits, merge policies and caches, query routing, scrolling, thread pools, and so on.
  • A number of tips and tricks for scaling out your cluster, different types of nodes and deployment topologies, the best way to handle time-based indices, etc.
  • Various OpenSearch APIs important for keeping your cluster healthy, about backups, hot threads, logging, monitoring tools and so on.

Things to remember

  • Participants must use their own computer with OSX, Linux, or Windows, with a container management tool installed (Docker Desktop, Podman, nerdctl) as well as Zoom.
  • Participants should be comfortable using a terminal/command line.
  • Participants need a working audio and video setup for labs, which are done in groups.

Sematext provides:

  • A digital copy of the training material, including slides and many sample requests
  • A docker-compose.yml file for the lab environment

About the trainer

Radu Gheorghe

Radu Gheorghe

Your trainer is an active OpenSearch consultant who worked with clients from many different industries on OpenSearch, Elasticsearch and Solr projects for 10+ years.

Need On-Site or Remote Training

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