An enterprise IoT telemetry platform ingests high-volume device metrics through an External Application Load Balancer into BigQuery and Cloud Storage. The security team mandates two specific security controls: first, protection against Layer 7 HTTP flood denial-of-service (DDoS) attacks at the network edge; second, prevention of unauthorized data movement to external storage locations by internal users who hold legitimate IAM access to the dataset. Which TWO security controls should you implement to satisfy these requirements? (Select TWO)
- Attach a Google Cloud Armor security policy with rate-limiting rules to the External Application Load Balancer backend service.Answer
- Configure a VPC Service Controls service perimeter around the BigQuery and Cloud Storage resources.Answer
- CGrant primitive IAM Viewer roles to administrators and enforce IAM Deny policies on storage object export APIs.
- DEstablish VPC Network Peering to a centralized transit VPC and rely on transitive routing to inspect API traffic sent to external Google Cloud projects.
Answer
The architect must configure a Google Cloud Armor security policy with rate limiting attached to the Load Balancer backend service, and establish a VPC Service Controls service perimeter enclosing the BigQuery and Cloud Storage resources.
Attaching a Google Cloud Armor security policy with rate limiting to the load balancer backend service effectively mitigates Layer 7 HTTP flood attacks at the edge. Additionally, placing BigQuery and Cloud Storage inside a VPC Service Controls perimeter blocks unauthorized data movement to external GCP projects or buckets, mitigating exfiltration risks from credentialed users.
Step-by-Step Solution
Key Concept
Combining Google Cloud Armor for edge application security with VPC Service Controls for data exfiltration prevention.