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Difficulty: HardDesigning Infrastructure for Business Requirements and Cost Optimization

A healthcare technology enterprise processes nightly batch workloads for genomic sequence analysis and stores raw sequence reads for 7 years to satisfy regulatory compliance mandates. The batch processing jobs are stateless, fault-tolerant, and execute for 4 hours each night. The raw sequence files are accessed frequently during the first 30 days after generation, but subsequent access occurs less than once per year for compliance audits. Which TWO architectural choices should you recommend to minimize overall infrastructure costs while satisfying operational and compliance requirements?

  1. Provision Compute Engine Managed Instance Groups (MIGs) utilizing Spot VMs for the nightly batch processing pipeline.Answer
  2. Implement Cloud Storage Object Lifecycle Management rules to transition raw sequence files to Archive Storage after 30 days.Answer
  3. C
    Deploy a dedicated multi-zone Google Kubernetes Engine (GKE) cluster with always-on node pools to guarantee compute availability.
  4. D
    Store all raw genomic sequence files and metadata in Cloud Spanner to ensure multi-region consistency and low read latencies.
  5. E
    Purchase 3-year Resource-Based Committed Use Discounts (CUDs) sized for the peak CPU and memory footprint of the nightly batch job.

Answer

The correct recommendations are using Compute Engine Spot VMs in Managed Instance Groups for the batch processing workload and configuring Cloud Storage Object Lifecycle Management rules to transition raw data to Archive Storage after 30 days.
Using Spot VMs within Managed Instance Groups provides up to 80% compute cost savings for fault-tolerant, stateless batch workloads running for 4 hours daily. For storage, automating object transitions from Standard to Archive Storage after 30 days minimizes the total cost of ownership for 7-year compliance retention without impacting active processing performance.

Step-by-Step Solution

1
Analyze the compute workload characteristics and cost structure
The batch pipeline is stateless, fault-tolerant, and runs for only 4 hours daily.
Stateless and fault-tolerant workloads that execute for short durations achieve maximum cost savings by leveraging Spot VMs rather than committed baseline instances or 24/7 clusters.
2
Evaluate data access frequency and long-term compliance retention requirements
Files are accessed frequently for 30 days and retained for 7 years with sub-annual retrieval.
Using Standard Storage for the first 30 days handles active processing, while automatically transitioning objects to Archive Storage after 30 days minimizes 7-year storage costs.
3
Eliminate sub-optimal or over-engineered architectural options
Always-on GKE clusters, Cloud Spanner database storage for binary sequence blobs, and continuous CUD commitments introduce unnecessary expenditures.
Aligning service selections with actual operational lifecycles prevents paying for idle compute capacity and high-tier database storage.

Key Concept

Designing infrastructure for cost optimization by pairing Spot instances for fault-tolerant batch compute with automated lifecycle tiering for long-term compliance storage.
Estimated Time:2m 0s
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Designing Infrastructure for Business Requirements and Cost Optimization