Checklist: pros and cons of using multiple Kubernetes clusters, and how to distribute workloads between them

Here is a list of pros and cons I found for using multiple clusters vs. a single one.

Scalability limits, for example a Kubernetes cluster has a limit of 150,000 pods. An OpenShift cluster has a limit of 10,000 services.
Separation of production/development/test
especially for testing a new version of Kubernetes, of a service mesh, of other cluster software.
Compliance
according to some regulations some applications must run in separate clusters/separate VPNs.
Multi-vendor
to prevent vendor lock-in running clusters of multiple providers.
Cloud/on-prem
to split the load between on-premise services.
Regionality for latency
run clusters in different geographical regions to reduce latency in those regions.
Regionality for availability
run in clusters in different regions/availability zones to reduce damage of a failing datacenter/region.
Better isolation for security
Isolation for easier billing/resource allocation

Compliance
some applications must run on separate clusters.
Locality for latency
allocate the applications according to the regions, to reduce latency.
Billing/Quotas
allocate applications together per billing account, to facilitate billing/quota enforcement.
Maintainability
put the applications in the same cluster when it makes sense to perform maintenance of the cluster for all them (upgrading Kubernetes version, etc.).
Hardware requirements
allocate high-performance applications to clusters with hardware for high performance.
Dependencies
reduce the need in intra-cluster service registries by allocating dependent applications together.
Identity and Access management
allocate applications in such a way that in-cluster identity and access management would suffice
Monitoring, tracing, logging
allocate applications to reduce the need for distributed monitoring, tracing, logging.

Vadim Eisenberg's blog