An energy utility enterprise is modernizing a legacy asset monitoring platform by migrating it from an on-premises data center to Google Cloud. The environment contains a 2.5 PB historical sensor dataset residing on aging SAN storage, along with a batch analytics process comprised of lightweight, stateless microservices. The company's existing 1 Gbps Dedicated Interconnect is heavily saturated, running at 90% capacity to support real-time operational telemetry. Organizational policies require moving the 2.5 PB dataset into Cloud Storage within 45 days, containerizing the batch analytics with minimal operational management overhead, and enforcing strict perimeter controls to prevent data exfiltration by compromised or authorized identities.
Which architectural strategy best fulfills these technical and business requirements?
- Order a Google Cloud Transfer Appliance to perform an offline bulk data import to Cloud Storage, execute the stateless batch analytics microservices using Cloud Run, and enclose the cloud resources within a VPC Service Controls perimeter.Cevap
- BStream the 2.5 PB historical dataset over the existing 1 Gbps Dedicated Interconnect using Storage Transfer Service, execute the stateless batch analytics microservices using Cloud Run, and enclose the cloud resources within a VPC Service Controls perimeter.
- COrder a Google Cloud Transfer Appliance to perform an offline bulk data import to Cloud Storage, provision a high-availability Google Kubernetes Engine (GKE) cluster to execute the stateless batch analytics microservices, and enclose the cloud resources within a VPC Service Controls perimeter.
- DOrder a Google Cloud Transfer Appliance to perform an offline bulk data import to Cloud Storage, execute the stateless batch analytics microservices using Cloud Run, and enforce fine-grained IAM roles without configuring a VPC Service Controls perimeter.