FTS (Full-Text Search) indexes require careful configuration and maintenance to ensure optimal performance, especially when it comes to text analysis pipelines. A user new to the Information Retrieval domain may find configuring an FTS index tedious due to the numerous options available for character filters, tokenisers, and token filters. However, a detailed insight into the text analysis output is crucial as users often struggle with why search results are not returning hits despite proper index definition. The `analyzeDoc` endpoint introduced in 6.5.0 provides a safe way to explore and debug analyser outputs, allowing users to identify issues such as mismatched analysers between index and query time. Additionally, FTS cluster sizing is critical, and while sizing guidelines are recommended, easy indicators like slow indexing progress, rejected search queries with HTTP status code 429, and slow-queries in stats graphs can hint at under-provisioning. Suboptimal queries, such as complex compound queries with many sub-queries, can also lead to inefficient system resource use, highlighting the importance of carefully crafting targeted queries.