A financial technology enterprise is designing an automated monthly statement generation service on Google Cloud. The service processes unpredictable, highly bursty containerized batch rendering tasks (each requiring 2 vCPUs and 4 GB RAM) that run for 15 to 20 minutes when triggered by customer request events. The workload stays completely idle between batches for days at a time. The business requirement is to minimize total operational costs by eliminating all baseline idle infrastructure expenses, while avoiding administrative overhead for cluster management. Which architecture should you recommend?
- AProvision a Google Kubernetes Engine (GKE) Standard cluster with cluster autoscaling and Horizontal Pod Autoscaling (HPA) enabled.
- Trigger containerized Cloud Run jobs on demand via Eventarc notifications, utilizing Cloud Run Spot instances for execution.Cevap
- CProvision Compute Engine Virtual Machines pre-configured to peak batch capacity and purchase 3-year Committed Use Discounts (CUDs).
- DStore state in a multi-region Cloud Spanner instance and process statement rendering on a dedicated pool of persistent Compute Engine instances.
Cevap
Trigger Cloud Run jobs on demand via Eventarc notifications using Cloud Run Spot instances.
Cloud Run jobs provide an ideal serverless execution platform for containerized tasks that run to completion and do not serve web traffic continuously. Combined with Eventarc for event-driven triggering and Cloud Run Spot for discounted pricing, this architecture scales to zero, incurring absolute zero cost during idle days while eliminating container cluster administration overhead.
Adım Adım Çözüm
Anahtar Kavram
Serverless batch architecture and cost optimization for bursty workloads