Merge pull request #127117 from changeworld/patch-25

Fix typo: homogenous -> homogeneous

Author: v-regandowner

articles/operator-nexus/concepts-nexus-availability.md

@@ -50,7 +50,7 @@ Go through the following steps to help plan an Operator Nexus deployment.
 
 2.  Determine the capacity requirements for each of these workloads, allowing for redundancy for each one.
 
-3.  If your workloads support a split between control-plane and data-plane elements, consider whether to separately design control-plane sites that can control a larger number of more widely distributed data-plane sites. This option is only likely to be attractive for larger deployments. For smaller deployments, or deployments with workloads that don't support separating the control-plane and the data-plane, you're more likely to use a homogenous site architecture where all sites are identical.
+3.  If your workloads support a split between control-plane and data-plane elements, consider whether to separately design control-plane sites that can control a larger number of more widely distributed data-plane sites. This option is only likely to be attractive for larger deployments. For smaller deployments, or deployments with workloads that don't support separating the control-plane and the data-plane, you're more likely to use a homogeneous site architecture where all sites are identical.
 
 
 4.  Plan the distribution of workload instances to determine the number of racks needed in each site type, allowing for the fact that each rack is an Operator Nexus zone. The platform can enforce affinity/anti-affinity rules at the scope of these zones, to ensure workload instances are distributed in such a way as to be resilient to failures of individual servers or racks. See [this article](./howto-virtual-machine-placement-hints.md) for more on affinity/anti-affinity rules. The Operator Nexus Azure Kubernetes Service (NAKS) controller automatically distributes nodes within a cluster across the available servers in a zone as uniformly as possible, within other constraints. As a result, failure of any single server has the minimum impact on the total capacity remaining.