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A research institution needs to process massive genomic datasets, often petabytes in size, for bioinformatics analysis. These analyses are batch-oriented, fault-tolerant, and can tolerate occasional interruptions to compute instances as long as the overall job completes. The institution wants to minimize compute costs. Which Google Cloud compute option is the most cost-effective for this scenario?
- APreemptible VMs
- BStandard Compute Engine instances
- CApp Engine Standard environment
- DGoogle Kubernetes Engine (GKE)
Show answer & explanationAnswer & explanation
Correct answer: A. Preemptible VMs
Preemptible VMs are significantly cheaper than standard instances and are designed for fault-tolerant workloads that can withstand instance preemption. Since the genomic analyses are batch-oriented and fault-tolerant, Preemptible VMs are the most cost-effective solution.
Why the other options are wrong
- B. Standard Compute Engine instances are more expensive and not necessary for fault-tolerant, batch-oriented workloads that can tolerate interruptions.
- C. App Engine Standard is a PaaS solution for web applications and APIs, not ideally suited for large-scale, long-running batch processing of petabytes of data.
- D. GKE provides orchestration for containers but doesn't inherently offer the same cost savings for interruptible workloads as Preemptible VMs.
Preemptible VMs
Low-cost Compute Engine instances that can be terminated (preempted) by Google Cloud if resources are needed elsewhere.
- Run for a maximum of 24 hours.
- Significantly cheaper than standard VMs.
- Ideal for fault-tolerant, batch processing, and stateless workloads.
Memory trick: Preemptible VMs: cheap, but they might leave.