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Key metrics for Elasticsearch performance monitoring

Elasticsearch is a highly scalable, distributed, open-source RESTful search and analytics engine that offers log analytics, real-time application monitoring, click stream analytics, and more. Elasticsearch stores and retrieves data structures in real time. It has multi-tenant capabilities with an HTTP web interface, presents data in the form of structured JSON documents, makes full-text search accessible via RESTful API, and maintains web clients for languages like PHP, Ruby, .Net, and Java.

Honeycomb vs Elastic Stack: It's about priorities

If you’ve been paying attention, you know that although collecting and reviewing metrics and logs is a core part of running a stable and successful service, access to raw events and the ability to search and pivot on any dimension of your production environment, no matter how high-cardinality, is what will help your team debug and troubleshoot new problems and outages more quickly.

Elasticsearch Performance Tuning

Once you have your Elasticsearch running, you’ll likely eventually find that performance starts to suffer over time. This can be due to a variety of factors, including changes in the way you’re using your cluster to how much and what types of data are being sent in. In order to maintain your cluster, you’ll need to set up monitors to alert you to any warning signs so that you can proactively handle available maintenance windows.

Solr on Docker: The Good, the Bad and the Ugly

This talk was given during Lucene Revolution 2017 and has two goals: first, to discuss the tradeoffs for running Solr on Docker. For example, you get dynamic allocation of operating system caches, but you also get some CPU overhead. We'll keep in mind that Solr nodes tend to be different than your average container: Solr is usually long running, takes quite some RSS and a lot of virtual memory. This will imply, for example, that it makes more sense to use Docker on big physical boxes than on configurable-size VMs (like Amazon EC2).

Solr: Optimize Is Not Bad For You Deep Dive Into The Segment Merge Abyss

They say optimize is bad for you, they say you shouldn't do it, they say it will invalidate operating system caches and make your system suffer. This is all true, but is it true in all cases? In this presentation we will look closer on what optimize or better called force merge does to your Solr search engine. You will learn what segments are, how they are built and how they are used by Lucene and Solr for searching.