Rally installation and air-gapped setup to benchmark Elasticsearch performance

The blog post by Philipp Kahr provides a detailed guide on installing and configuring Rally, a benchmarking tool used by Elastic to identify performance improvements and regressions in Elasticsearch. The post explains the steps required to set up Rally both in standard and air-gapped environments, emphasizing the importance of not running benchmarks on production clusters due to potential data loss. It outlines the prerequisites for installation, including Python and Git versions, and provides a step-by-step process for running a benchmark, known as a "race," using specific tracks and challenges. Additionally, it highlights the configuration of metrics collection and the importance of understanding tracks and challenges to effectively benchmark Elasticsearch performance. The blog also touches on troubleshooting common issues and suggests utilizing the Rally documentation for further assistance.