Tune and Scale Your Elasticsearch Clusters
If you are looking to administer, tune and scale clusters, in this class you will learn everything you need to handle your Elasticsearch clusters in production – from tuning OS si JVM for performance through commits, merge policies and caches, query routing, scrolling, thread pools, and so on.
Your trainer is an active Elasticsearch consultant who worked with clients from 20+ different industries and the author of Elasticsearch in Action.
Here are some problems Radu Gheorghe, your Elasticsearch trainer, solved for Sematext clients recently:
A word from Radu Gheorghe
“Attendees come in highly motivated, making the class feel more “alive” than I expected. They constantly look for takeaways to improve their setup, from tweaking a boost to changing the sharding strategy. Their use-cases are very diverse, too, so we end up covering a lot of material.
8-hour online class available upon request
Looking for an extended knowledge-based introduction to Elasticsearch training? You’ve come to the right place.
- Small, interactive, instructor-led classes
- Lots of hands-on exercises
- Customized learning experience
- More flexible – no need to travel
- Certificate of Completion included
Who should attend?
This Elasticsearch course is designed for technical attendees with basic Elasticsearch experience. A person should be able to index data to Elasticsearch, 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 Elasticsearch experience, we strongly suggest you consider attending our Intro to Elasticsearch class first.
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.
- Unicast settings
- Number of shards and replicas
- Node roles
- Set up a cluster; adjust number of shards and replicas for a new index
- Set up dedicated master, data and client nodes in a cluster
Designing for scale
- Time-based indices and aliases
- Shard allocation
- Cross-cluster search
- Create a multi-tier cluster
- Set up a cluster to work across availability zones
- Set up cross-cluster search
- Index and search templates
- Snapshot and restore
- Upgrades and cluster restarts
- Shard allocation
- Set up index templates
- Adjust initial recovery settings
- Adjust rebalancing settings
Troubleshooting and profiling
- Health and stats APIs
- Cat APIs
- Monitoring products
- Task management
- Hot threads API
- Query profiling
- Use the Cat APIs to get nodes and thread pool stats
- Set up slowlogs
- Heap size vs OS caches
- Garbage collection
- Elasticsearch-specific caches
- Hardware considerations
- Adjust heap size and set up G1 Garbage Collector
- Adjust query cache size, field data size and index buffer size
Tuning indexing and queries
- How often to commit: translog, index buffer and refresh interval
- How data is stored: merge policies
- Index sorting
- Thread pools
- Set up routing
- Adjust refresh, flush and merge settings
- Set up index sorting
- Adjust thread pool size and queue sizes
- Scaling with Different Node Types, Multi-Tier and Multi-Cluster Architectures
- Efficient Index Designs for Product and Time-Series Search
- Tuning Caches, Merge Policies and Other Elasticsearch, 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 Elasticsearch 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 Elasticsearch 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 recent version of Java installed.Participants should be comfortable using a terminal/command line. Sematext provides:
- A digital copy of the training material
- A VM with all configs, scripts, exercises, etc.
Want to master your Elasticsearch use case faster?
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