One of the advanced platforms for enterprise search is Solr and it includes a developer API as well as instrumentation for making the collection of the detailed performance-oriented metrics across the life-cycle of the Solr service as well as its multiple components. It makes the application of Lucene Java search library at the base for full-text indexing as well as search

The program is written in Java and it is massively used for the search and analysis engine of data. This technology is available with high fault tolerance capability. It works as a standalone search server for full text. Solr support has an extremely active development community and does regular releases too.

It includes the developer API and it uses the feature of dropwizard metrics API. The classes of meters that are used to measure are mentioned below.

• The first one is the counter. It provides a single long value such as the number of requests, etc.
• The next one is the meter. It computes the rates of an event. The count that it provides is quite similar to the Unix System average load technology.
• Histograms do the calculation of the approximate distribution of events depending on their values. It works based on approximate statistics along with an alike exponential decay.
• The timer is used to measure the duration of every event. This offers a count as well as a histogram of timing.
• For the immediate reading of the current value, the gauge is used in solr support. This reads the depth of the current queue, present number of active connections, etc

Important solr metrics to monitor

One must know how we can monitor the Solr metrics and here are the key metrics to do that.

• Request rate: The first key is the request rate. Every handler in the solr sends information relating to the rate of request. A professional for solr consulting notice a sudden drop or increase in the rate of request then you can point out the failure in any one of the components of your system.
• Request latency: This feature measures how fast the request is available for any type of handlers separately. This helps to observe the latency of the queries easily and the update of the request will also be done smoothly. One can easily measure the latency of every handler if these handlers are dedicated to various search needs whether it is for article search or product search.
• Commit events: This feature is also available in different types. The manual commits can be sent with or devoid of indexing requests. Another one is automatic commits. These are required for the persistence of data and make the data visibility ease. You may also be known about the hard commit in solr support. This is used to clear the transaction log and to flush the data to the disk.
• Utilization of caches: Caches have a great contribution in solr performance. The cached data can easily be accessed devoid of the presence of expensive disk operation. Caches will require memory depending on the information you will like to search.

Hope you got a brief about the associated metrics of Solr to be monitored.