Initializing datacenters

Determining whether to use a single or multiple datacenter deployment per workload type.

In most circumstances, each workload type, such as search, analytics, and transactional, should be organized into separate virtual datacenters. Workload segregation avoids contention for resources. However, workloads can be combined in SearchAnalytics nodes when there is not a large demand for analytics, or when analytics queries must use a DSE Search index. Generally, combining transactional (OLTP) and analytics (OLAP) workloads results in decreased performance.

When creating a keyspace using CQL, DataStax Enterprise creates a virtual datacenter for a cluster, even a one-node cluster, automatically. You assign nodes that run the same type of workload to the same datacenter. The separate, virtual datacenters for different types of nodes segregate workloads that run DSE Search from those nodes that run other workload types.

Single datacenters per workload type

If using a single, physical datacenter, single datacenter deployments are useful.

Multiple datacenters per workload type

If using multiple datacenters, consider multiple datacenter deployments.

The following scenarios describe some benefits of using multiple, physical datacenters:
  • Isolating replicas from external infrastructure failures, such as networking between datacenters and power outages.
  • Distributing data replication across multiple, geographically-dispersed nodes.
  • Adding separation between different physical racks in a physical datacenter.
  • Diversifying assets between public cloud providers and on-premise managed datacenters.
  • Preventing the slow down of a real-time analytics cluster by a development cluster running analytics jobs on live data.
  • Using virtual datacenters in the physical datacenter to ensure reads from a specific datacenter is local to the requests, especially when using a consistency level greater than ONE. This strategy ensures lower latency because it avoids reads from one node in New York and another read from a node in Los Angeles.