Intrigued by the art of cloud architecture? Discover how to design, develop, and manage robust, secure, scalable, and dynamic solutions on Google Cloud as you prepare for the Professional Cloud Architect exam!
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An enterprise maintains a multi-project architecture on Google Cloud. Raw source data is stored in BigQuery tables within a dedicated data warehouse project (project-data), while the machine learning platform team manages a Vertex AI Feature Store instance in a separate project (project-ml).
You need to configure access control so that the Vertex AI Feature Store in project-ml can ingest batch feature data from BigQuery in project-data. In addition, your organization's security policy requires that IT/DevOps administrators who configure and scale the Feature Store infrastructure cannot read or write actual feature values.
Which identity and access management (IAM) configuration should you implement?
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