An enterprise organization operates multiple Google Cloud projects under a single Cloud Billing account. The central Site Reliability Engineering (SRE) team must provision guaranteed compute capacity for three separate service projects (project-core, project-analytics, and project-services) in us-central1-a ahead of a high-traffic seasonal event. The capacity planning strategy must satisfy the following requirements: Guarantee 60 n2-standard-16 virtual machines (VMs) in zone us-central1-a across the three projects. Allow VMs across all three consumer projects to dynamically consume the reserved pool on demand. Ensure each consumer project is billed directly for the reserved capacity it actively consumes, while applying existing organizational Committed Use Discounts (CUDs). Restrict the authority to create and manage shared capacity pools strictly to the central infrastructure management project (project-infra). Which combination of configuration steps meets these requirements?

Add `project-infra` to the allowlist for the `compute.sharedReservationsOwnerProjects` organization policy constraint, create a shared on-demand reservation in `project-infra` targeting `us-central1-a` with consumer projects added, and enable CUD sharing on the Cloud Billing account.: ### What Shared Reservations and Organizational Policies Are **Shared reservations** allow a central owner project in Google Cloud to allocate and guarantee zonal Compute Engine capacity that multiple consumer projects within the same organization can consume. The **`compute.sharedReservationsOwnerProjects`** organization policy constraint provides governance by strictly restricting which projects have permission to create and manage shared reservations. ### How It Meets the Requirements - **Guarantee capacity dynamically across projects**: Provisioning a shared on-demand reservation in `project-infra` for 60 `n2-standard-16` VMs in `us-central1-a` and specifying `project-core`, `project-analytics`, and `project-services` as consumer projects enables VMs in any of those projects to consume the shared capacity pool dynamically. - **Accurate billing and attribution**: By default, unconsumed reserved capacity is billed to the owner project (`project-infra`). However, as soon as a consumer project runs a matching VM that consumes reserved capacity, Compute Engine switches the billing of that consumed portion directly to the consumer project. - **Committed Use Discount (CUD) alignment**: Enabling CUD sharing at the Cloud Billing account level ensures that resource-based or spend-based commitments automatically apply discounted rates to the billed project consuming the reservation. - **Administrative governance**: Adding only `project-infra` to the allowlist for the `compute.sharedReservationsOwnerProjects` constraint prevents unauthorized teams from creating shared reservations elsewhere in the organization. ### Key Advantages and Capabilities - **Centralized governance**: Centralizes capacity procurement while distributing usage across teams. - **Dynamic workload sharing**: When one consumer VM stops, its reserved capacity immediately returns to the pool for other consumer projects. - **Billing attribution**: Accurately charges active consumption to individual service teams while holding unconsumed capacity costs in the central infrastructure project. ### Why This Is Optimal This architecture directly adheres to Google Cloud's multi-project capacity planning best practices by pairing organization policy controls, shared zonal reservations, and billing-level CUD sharing.

Configure Shared Compute Engine Reservations Cuds | Professional Cloud DevOps Engineer

Configure Shared Compute Engine Reservations Cuds

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An enterprise organization operates multiple Google Cloud projects under a single Cloud Billing account. The central Site Reliability Engineering (SRE) team must provision guaranteed compute capacity for three separate service projects (project-core, project-analytics, and project-services) in us-central1-a ahead of a high-traffic seasonal event.

The capacity planning strategy must satisfy the following requirements:

Guarantee 60 n2-standard-16 virtual machines (VMs) in zone us-central1-a across the three projects.
Allow VMs across all three consumer projects to dynamically consume the reserved pool on demand.
Ensure each consumer project is billed directly for the reserved capacity it actively consumes, while applying existing organizational Committed Use Discounts (CUDs).
Restrict the authority to create and manage shared capacity pools strictly to the central infrastructure management project (project-infra).

Which combination of configuration steps meets these requirements?

Create a shared on-demand reservation in project-infra configured with consumption type SPECIFIC_RESERVATION, and configure all consumer VMs with reservationAffinity=none.

Submit a shared future reservation request in project-infra specifying compact placement policies, and rely on the request to automatically bill all unconsumed capacity to the three consumer projects equally.

Create three separate single-project reservations of 20 VMs each across the three consumer projects with default automatic consumption, and rely on automatic cross-project reservation overflow to handle imbalance.

Add project-infra to the allowlist for the compute.sharedReservationsOwnerProjects organization policy constraint, create a shared on-demand reservation in project-infra targeting us-central1-a with consumer projects added, and enable CUD sharing on the Cloud Billing account.

Professional Cloud DevOps Engineer

Configure Shared Compute Engine Reservations Cuds

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