Cost Attribution
Associating and tracking costs at the tenant level is a much more challenging proposition in a full stack pooled environment. While many environments give you tools to map tenants to specific infrastructure resources, they don’t typically support mechanisms that allow you to attribute consumption to the individual tenants that are consuming a shared resource. For example, if three tenants are consuming a compute resource in a multi-tenant setting, I won’t typically have access to tools or mechanisms that would let me determine what percentage of that resource was consumed by each tenant at a given moment in time. We’ll get into this challenge in more detail in Chapter 14. The main point here is that, with the efficiency of a full stack pooled model also comes new challenges around understanding the cost footprint of individual tenants.
Operational Simplification
I’ve talked about this need for a single pane of glass that provides a unified operational and management view of your multi-tenant environment. Building this operational experience requires teams to ingest metrics, logs, and other data that can be surfaced in this centralized experience. Creating these operational experiences in a full stack pooled environment tends to be a simpler experience. Here, where all tenants are running in shared infrastructure, I can more easily assemble an aggregate view of my multi-tenant environment. There’s no need to connect with one-off tenant infrastructure and create paths for each of those tenant-specific resources to publish data to some aggregation mechanism. Deployment is also simpler in the full stack pooled environment. Releasing a new version of a microservice simply means deploying one instance of that service to the pooled environment. Once it’s deployed all tenants are now running on the new version.
