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Difficulty: HardDesigning Infrastructure for Business Requirements and Cost Optimization

A financial analytics firm executes batch Monte Carlo risk simulations twice per week. Each execution requires rapidly scaling up to 4,000 vCPUs for approximately two hours to perform stateless calculations, after which resource utilization drops back to zero. The firm requires a solution that minimizes total compute costs, eliminates idle infrastructure overhead, and avoids maintaining control plane management overhead when simulations are not running. Which architecture should the Cloud Architect recommend?

  1. Containerize the simulation application and execute it using Cloud Run jobs, allowing tasks to scale on demand and automatically terminate upon completion.Answer
  2. B
    Deploy a multi-zone Google Kubernetes Engine (GKE) cluster with Cluster Autoscaler to scale worker nodes up from zero for each batch execution.
  3. C
    Purchase 3-year Compute Engine vCPU Committed Use Discounts (CUDs) sized for 4,000 vCPUs and run the jobs on a Managed Instance Group.
  4. D
    Store simulation parameters in a multi-region Cloud Spanner instance and orchestrate task execution using Cloud Functions.

Answer

Containerize the simulation application and execute it using Cloud Run jobs, allowing tasks to scale on demand and automatically terminate upon completion.
Executing the batch simulations using Cloud Run jobs is the optimal solution because Cloud Run jobs natively supports containerized, run-to-completion workloads with zero ongoing infrastructure costs when idle. It automatically provisions resources to scale out tasks and terminates immediately upon job completion, aligning cost directly with actual usage.

Step-by-Step Solution

1
Analyze the workload's operational characteristics and scheduling profile.
Identified a stateless, batch compute pattern running for 4 hours total per week (twice per week for 2 hours) scaling up to 4,000 vCPUs.
Understanding usage frequency prevents over-provisioning infrastructure that incurs continuous charges while idle.
2
Evaluate Google Cloud compute choices based on the business constraint of minimizing cost and operational overhead.
Cloud Run jobs provides serverless execution for containerized batch tasks with zero baseline control plane fees and automatic scale-to-zero capability.
Serverless containers charge strictly per vCPU/memory second during active execution, optimizing cost for bursty, intermittent workloads.
3
Eliminate sub-optimal compute, billing, and storage architectures.
GKE introduces unnecessary cluster overhead, CUDs incur 24/7 costs for intermittent tasks, and Cloud Spanner introduces high fixed database node costs.
Choosing serverless batch containers meets all technical and business requirements with minimum total cost of ownership.

Key Concept

Serverless Batch Execution for Intermittent Cost-Optimized Workloads
Estimated Time:2m 0s
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Topics

Designing Infrastructure for Business Requirements and Cost Optimization