Crucial Exams

GCP Professional Cloud Architect Practice Question

Your SRE team wants to adopt Gemini Cloud Assist to speed up incident response. They need the service to ingest Cloud Logging entries and help them diagnose IAM-related permission problems from within the Google Cloud Console. Company policy mandates that any AI tool (1) keep all customer code, logs, and metadata inside Google-controlled infrastructure and (2) guarantee that this data is never used to retrain foundation models. Which implementation meets the policy while still giving the team the required Gemini troubleshooting capabilities?

  • Install the GitHub Copilot extension in Cloud Shell Editor and restrict egress traffic with VPC firewall rules to keep suggestions within Google Cloud.

  • Enable Gemini Cloud Assist in enterprise privacy mode for the relevant Google Cloud project and assign the SRE group the roles/gemini.cloudAssistUser role so they can analyze Cloud Logging data and IAM policies directly from the Cloud Console.

  • Deploy an open-source Llama model on a hardened Compute Engine VM, export logs to it daily, and query the model for IAM diagnostics during incidents.

  • Have engineers paste logs and IAM policy snippets into the public gemini.google.com chat after disabling Web & App Activity so user data is reportedly not stored long-term.

GCP Professional Cloud Architect
Designing and planning a cloud solution architecture
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