Over the years, natural language processing, in the world of search, went from interesting detail to a must have, especially in areas such as e-commerce. Engineers started incorporating classification, synonym generation, named entity recognition and much more into their search systems giving users better search results and in some cases leading to more revenue.

Real User Monitoring, or RUM, is a type of monitoring technology for digital businesses that analyzes customers’ digital experiences by looking at exactly how online visitors are interacting with a website or application, analyzing everything from page load events to AJAX requests to frontend application crashes. The most commonly known example of RUM would be Google Analytics, or GA, which tracks certain spectrums of the interaction between your user and your website or webapp.

So you’ve got a ClickHouse DBMS, and you’re looking for a tool to monitor it. You’ve come to the right place. In this blog post (which is part 2 of a three-part series on ClickHouse monitoring), we’ll identify and discuss the various ClickHouse monitoring tools available today.

Lucene has a lot of options for configuring similarity. By extension, Solr and Elasticsearch have the same options. Similarity makes the base of your relevancy score: how similar is this document (actually, this field in this document) to the query? I’m saying the base of the score because, on top of this score, you can apply per-field boosts, function scoring (e.g. boost more recent documents) and re-ranking (e.g. Learning to Rank).

More than likely you’re here because you’ve made the leap or are thinking of making the leap in investing in a Real Monitoring Solution. Congrats. You’re one step closer to having the power of user metrics working in your favor. Real User Monitoring is a way for your users to communicate with you how satisfied they were when they interacted with your website or webapp, so how can you be sure you’re listening correctly?