A company is migrating a legacy monolithic application to Google Cloud. The application has unpredictable traffic patterns and long-running connections. The team wants to minimize operational overhead and only pay for resources when the application is processing requests. Which compute option should they choose?
Trap 1: Google Kubernetes Engine (GKE) Autopilot cluster
GKE Autopilot reduces management but still bills for pods instead of requests, and may not scale to zero as efficiently as Cloud Run for HTTP workloads.
Trap 2: Compute Engine with managed instance groups and autoscaling
Compute Engine requires manual instance management and has per-hour billing, which is not cost-effective for unpredictable traffic with idle periods.
Trap 3: Google Kubernetes Engine (GKE) Standard cluster with node…
GKE Standard requires cluster management and pays for nodes even when idle, increasing overhead and cost.
- A
Google Kubernetes Engine (GKE) Autopilot cluster
Why wrong: GKE Autopilot reduces management but still bills for pods instead of requests, and may not scale to zero as efficiently as Cloud Run for HTTP workloads.
- B
Compute Engine with managed instance groups and autoscaling
Why wrong: Compute Engine requires manual instance management and has per-hour billing, which is not cost-effective for unpredictable traffic with idle periods.
- C
Google Kubernetes Engine (GKE) Standard cluster with node autoscaling
Why wrong: GKE Standard requires cluster management and pays for nodes even when idle, increasing overhead and cost.
- D
Cloud Run
Cloud Run is serverless, scales to zero, and bills per request, making it ideal for unpredictable traffic patterns with minimal overhead.