A digital media processing company is migrating its video catalog workflow to Google Cloud. The architecture includes batch-oriented, stateless video rendering tasks that run intermittently when new media arrives, as well as a historical video archive that is retained for compliance and accessed less than once a year. The business objective is to minimize ongoing infrastructure maintenance overhead and optimize total operational expenditure. Which TWO architectural decisions should the cloud architect recommend? (Select TWO)
- Execute the batch video rendering tasks using Cloud Run Jobs to eliminate baseline compute costs and automatically scale to zero when idle.Cevap
- BProvision a dedicated Google Kubernetes Engine (GKE) Standard cluster to manage the batch video rendering containers.
- Store the historical video assets in Cloud Storage using the Archive Storage class with Object Lifecycle Management to automate tiering.Cevap
- DMigrate the historical video assets to a multi-region Cloud Spanner database to guarantee zero recovery point objective (RPO) and low latency.
Cevap
The architect should execute the batch video rendering tasks using Cloud Run Jobs and store the historical video assets in Cloud Storage using the Archive Storage class with Object Lifecycle Management.
Selecting Cloud Run Jobs satisfies the requirement to process intermittent stateless tasks without incurring baseline compute costs, as serverless workloads scale to zero when idle. Storing long-term rarely accessed assets in Cloud Storage Archive Storage provides the lowest storage cost per gigabyte for data accessed less than once annually while maintaining standard Cloud Storage API accessibility.
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Anahtar Kavram
Serverless compute right-sizing and object storage tiering for cost optimization