Elasticsearch offers a versatile array of features to manage cluster topologies, enabling the formation of heterogeneous clusters with varied node capacities. While it might be tempting to consolidate all workloads into a single, powerful cluster, the text argues for the benefits of managing multiple separate clusters. This approach simplifies performance management and limits the impact of failures by allowing different workloads, such as autocompletion, full-text search, and analytics, to be handled independently. It also facilitates safer upgrades through cloning and enables latency-based routing by distributing clusters globally. Additionally, separate clusters can accommodate bulk indexing tasks and experimental testing without risking production stability. Although managing multiple clusters involves additional complexity, tools like Elastic Cloud streamline the process by offering features such as easy cluster creation, snapshot/restore capabilities, and hourly billing, making it feasible to manage both short-lived and continuous production clusters efficiently.