A financial risk analysis firm is planning the Google Compute Engine architecture for a new quantitative modeling platform. The platform consists of two distinct components:
1. A high-performance simulation engine executing millions of stateless, fault-tolerant Monte Carlo calculations that can be restarted if terminated unexpectedly.
2. A continuous, uninterrupted auditing microservice requiring a non-standard memory ratio of 1 vCPU to 8 GB of RAM to run reliably 24/7.
Which TWO compute resource strategies should you recommend to optimize cost and fulfill workload requirements? (Select TWO.)
- Provision Spot Virtual Machines for the simulation engine compute fleet.Answer
- Configure custom machine types for the continuous auditing microservice.Answer
- CProvision Spot Virtual Machines for the continuous auditing microservice to reduce baseline running costs.
- DDeploy the simulation engine fleet on Cloud Run to avoid managing virtual machine infrastructure.
Answer
Select the option to provision Spot Virtual Machines for the simulation engine compute fleet, and the option to configure custom machine types for the continuous auditing microservice.
Stateless, fault-tolerant compute workloads like Monte Carlo simulations are ideal candidates for Spot Virtual Machines because they can sustain interruptions while drastically reducing compute costs. Furthermore, workloads requiring non-standard memory-to-vCPU ratios benefit from custom machine types, allowing precise resource allocation without paying for unused vCPUs or RAM in standard predefined machine families.
Step-by-Step Solution
Key Concept
Selecting optimal Compute Engine machine types and VM lifecycle options based on workload fault tolerance and resource ratios.