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Best Practices for Tuning Elasticsearch at Scale
Submitted by Yuvraj Gupta (@guptayuvraj) on Friday, 17 November 2017
Technical level: Intermediate
The talk will cover the various problems faced while scaling Elasticsearch along with various parameters to consider for architecht and fine-tuning Elasticsearch cluster before deploying in the Production Environment. It will cover the basic configuration to advanced configuration which should be considered while deploying an Elasticsearch cluster. The key takeaways of the talk will be to broaden your mindset to fine-tune the Elasticsearch cluster which is an ever-learning process. The intended audience for the talk would be those who are familiar with Elasticsearch and are looking to deploy Elasticsearch, fine-tuning some of the configuration to handle some pivotal issues such as OutOfMemory Exception, Unassigned Shards etc.
- Introduction to Elasticsearch
- Various Problems faced while scaling Elasticsearch
- Choosing the right kind of Node for Elasticsearch Cluster
- Choosing the right set of Hardware (Memory, Disks etc.)
- Configuration for Fine-Tuning Elasticsearch
The participants should come with a zeal of learning new ideas :)
Author of the books “Mastering Elastic Stack” & “Kibana Essentials”. Currently, working as an Infrastructure Engineer at Innovaccer responsible to architect, manage and orchestrate Elasticsearch Clusters for various projects across the organization. Keen Technologist with interest towards Big Data, Dev Ops, Data Analytics and Business Intelligence. Love to spend time on various social platforms and contribute by Providing Answers on Stackoverflow, Writing a Blog and Writing answers on Quora.