According to Compute Engine documentation on Shared Reservations , the most flexible and manageable way to handle capacity across multiple projects is to use a centralized Owner Project . This is a dedicated project used to create and manage the reservation, which is then shared with " Consumer Projects " (in this case, your GKE production and development projects).
This architecture specifically addresses the requirement to " ensure GPU capacity is always available " by securing the resources at the organizational level. Because the reservation is shared , the GPU capacity is not
" locked " into a single project. If the production environment scales down and leaves unused capacity in the shared pool, the development project can immediately consume those reserved GPUs for its own scaling needs without requiring manual transfers or new configurations.
Google ' s Best Practices for Shared Reservations recommend that the owner project should only own the reservation and not necessarily consume it, which simplifies billing and quota management. Option D is technically possible but less " manageable " at scale than a centralized owner project. Options A and B lack the automated, fluid capacity shifting required by the AI/ML workload ' s dynamic scaling needs.
The following solutions are based on Google Cloud Architect documents and industry-standard best practices for global content delivery, data migration, and high-performance file access.