Professional Cloud DevOps Engineer
Prepare and test your skills
Prepare and test your skills
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Your organization is establishing an AI-assisted observability workflow to speed up incident resolution. DevOps engineers need to use Gemini Cloud Assist directly within Logs Explorer to investigate application errors, analyze log data alongside metrics and resource configurations, and generate ranked root-cause hypotheses.
Which configuration and Identity and Access Management (IAM) strategy should you implement to enable Gemini Cloud Assist for this log analysis workflow?
Gemini Cloud Assist provides AI-powered troubleshooting and automated root-cause analysis across Google Cloud observability tools, including direct integration within Logs Explorer through Gemini Cloud Assist Investigations. To activate this functionality, the geminicloudassist.googleapis.com API must be enabled, which simultaneously activates the underlying cloudaicompanion.googleapis.com service.
geminicloudassist.googleapis.com provisions the necessary API endpoints and backing infrastructure required for conversational and automated investigative features.roles/geminicloudassist.user provides engineers with the identity-level permissions to interact with Gemini Cloud Assist.roles/recommender.viewer alongside resource-specific viewer roles (such as roles/logging.viewer and roles/cloudasset.viewer) ensures Gemini can access and analyze logs, configurations, and telemetry without granting excessive administrative privileges.Gemini Cloud Assist enforces identity-based access control where the AI assistant strictly inherits the querying user's permissions. Assigning roles/geminicloudassist.user paired with standard viewer roles gives DevOps teams the exact visibility needed to generate actionable troubleshooting insights while maintaining strong governance and least privilege.
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