Benchmarking Elasticsearch performance using ingest pipelines and custom logs involves creating a reproducible testing environment to evaluate how well a cluster handles specific workloads, such as log ingestion and search. This process includes setting up Elasticsearch with custom log tracks, reindexing data, and utilizing Rally, a benchmarking tool, to simulate different scenarios and analyze performance metrics. The blog emphasizes the importance of not running Rally on production clusters due to potential data loss and cluster instability. It provides detailed steps for creating custom log tracks, setting up and using ingest pipelines, and measuring performance impacts, such as processing time and CPU usage. The overall goal is to understand how different configurations affect the cluster's ability to handle large volumes of data efficiently, with insights into optimizing data ingestion and processing.