optimizations titles updated

Author: eedugon

deploy-manage/production-guidance/optimize-performance/approximate-knn-search.md

@@ -9,7 +9,7 @@ applies_to:
     self: all
 ---
 
-# Approximate kNN search [tune-knn-search]
+# Tune approximate kNN search [tune-knn-search]
 
 {{es}} supports [approximate k-nearest neighbor search](../../../solutions/search/vector/knn.md#approximate-knn) for efficiently finding the *k* nearest vectors to a query vector. Since approximate kNN search works differently from other queries, there are special considerations around its performance.
 

deploy-manage/production-guidance/optimize-performance/disk-usage.md

@@ -9,7 +9,7 @@ applies_to:
     self: all
 ---
 
-# Disk usage [tune-for-disk-usage]
+# Tune for disk usage [tune-for-disk-usage]
 
 This page provides strategies to reduce the storage footprint of your Elasticsearch indices. Disk usage is influenced by field mappings, index settings, document structure, and how you manage segments and shards. Use these recommendations to improve compression, eliminate unnecessary data, and optimize storage for your specific use case.
 

deploy-manage/production-guidance/optimize-performance/indexing-speed.md

@@ -9,7 +9,7 @@ applies_to:
     self: all
 ---
 
-# Indexing speed [tune-for-indexing-speed]
+# Tune for indexing speed [tune-for-indexing-speed]
 
 Elasticsearch offers a wide range of indexing performance optimizations, especially useful for high-throughput ingestion workloads. This page provides practical recommendations to help you maximize indexing speed, from bulk sizing and refresh intervals to hardware and thread management.
 

deploy-manage/production-guidance/optimize-performance/search-speed.md

@@ -9,7 +9,7 @@ applies_to:
     self: all
 ---
 
-# Search speed [tune-for-search-speed]
+# Tune for search speed [tune-for-search-speed]
 
 This page provides guidance on tuning {{es}} for faster search performance. While hardware and system-level settings play an important role, the structure of your documents and the design of your queries often have the biggest impact. Use these recommendations to optimize field mappings, caching behavior, and query design for high-throughput, low-latency search at scale.