CenterOS Capacity Management vs Google Cloud Capacity Planner

CenterOS Capacity Management gives data-center teams a graphical view of racks, rooms, and resources for managing space, power, and cooling. It tracks power, cooling, space, weight, connectivity, and compute, with custom dimensions available. Rack elevations let users inspect layouts and model installations, moves, or decommissioning before work starts. Equipment templates populate vendor values such as power draw, heat output, weight, dimensions, and rack space when assets are added. Listed monitoring protocols include SNMP, Modbus, BACnet, MQTT, IPMI, and Prometheus. Estate data can be imported from spreadsheets, NetBox, Ralph, or legacy DCIM systems. Deployment choices are multi-tenant SaaS, dedicated private cloud, or sovereign on-premises operation, including air-gapped environments. CenterOS says sovereign deployments keep AI inference inside the customer boundary. Its AI can answer plain-English questions, plan capacity, and correlate incidents; human approval is required for agent proposals. Field-level audit trails record state changes as replayable events. Pricing is available on request for SaaS, private cloud, and sovereign on-premises plans.

Google Cloud Capacity Planner shows current and forecasted use of Google Cloud resources to help teams plan capacity and quota needs. It covers Compute Engine instances, Persistent Disk and Hyperdisk volumes, GPUs, TPUs, and Cloud Storage bucket egress bandwidth. Forecasts combine linear and superlinear models, with yearly seasonality for scopes holding at least two years of usage history. Compute usage is available at P50, P75, and P99 percentiles; Cloud Storage bucket usage is shown at P100 only. Historical usage spans up to two years, forecasts up to six months, and historical forecast snapshots up to one year. Usage is sampled every five minutes and displayed within 24 hours; Overview insights refresh at least every 48 hours. Data can be exported as CSV or through the REST API to Cloud Storage or BigQuery. The API supports project, folder, and organization scopes. The service costs nothing, but billable Google Cloud resources used with it are charged separately. It is in Preview under Pre-GA terms, may have limited support, and some organizations may need to request access.