This chapter covers
- Building and deploying your Solr distribution
- Monitoring for and debugging issues with Solr
- Scaling Solr across servers to handle large content and query volumes
- Choosing the right configuration (hardware, OS, JVM, and Solr caches)
Most of the examples in previous chapters have used small datasets intended to demonstrate how Solr’s core functionality works. At some point, however, you will want to move beyond a prototype and into a production system capable of handling a large number of queries and/or documents. This means that you will have additional concerns beyond Solr’s functional capabilities: You will care about server configuration (CPU, RAM, and OS), how many servers you need, how the servers communicate, which Solr settings need to be “tuned” to handle load, how to monitor performance issues and debug Solr’s code, and how to fix problems when they arise. You will also have to worry about writing code to communicate with Solr (or using libraries) to run queries, and how to most efficiently get your data indexed into Solr. This chapter will cover some of these practical nuts and bolts of taking Solr to production.