Elasticsearch 7.11 introduces significant optimizations to its date_histogram aggregation, a key feature used in Kibana's Discover and Logs Monitoring UI, by addressing performance issues related to daylight savings time transitions. Initially, the java.util.time APIs caused inefficiencies due to object allocations, prompting the development of a custom daylight savings time conversion code that leverages precomputed transitions and binary search, which significantly speeds up the process. Further enhancements involved transforming date_histogram aggregations into range and filters aggregations, offering up to an eightfold performance boost by using the search index instead of doc values. The new "filter by filter" execution mode, which optimizes filters aggregations, reduces maintenance burdens and opens possibilities for future aggregation optimizations. These improvements not only enhance performance but also provide a basis for further experimentation and benchmarking, with nightly tests conducted using JMH and Rally, and the Elastic team encouraging contributions and offering job opportunities for those interested in full-time work on these advancements.