Scale Your Metrics with Elasticsearch

A presentation at HighLoad++ in in Moscow, Russia by Philipp Krenn

"Only accept features that scale" is one of Elasticsearch's engineering principles. So how do we scale metrics stored in Elasticsearch? And is that even possible on a full-text search engine?

This talk explores:

  • How are metrics stored in Elasticsearch and how does this translate to disk use as well as query performance?
  • What does an efficient multi-tier architecture look like to balance speed for today's data against density for older metrics?
  • How can you compress old data and what does the mathematical model look like for different metrics?

We are trying all of this hands-on during the talk, since this has become much simpler recently.



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