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The frugal HPC architect – ensuring effective FinOps for HPC workloads at scale | Amazon Web Services
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You Should Know:
1. AWS Cost Optimization Commands & Tools
- AWS CLI Cost Reports:
aws ce get-cost-and-usage \ --time-period Start=2025-01-01,End=2025-03-31 \ --granularity MONTHLY \ --metrics "BlendedCost" "UnblendedCost" "UsageQuantity" \ --group-by Type=DIMENSION,Key=SERVICE
- Spot Instances for HPC:
aws ec2 request-spot-instances \ --spot-price "0.50" \ --instance-count 10 \ --type "one-time" \ --launch-specification file://specs.json
2. Linux/Cloud Cost Monitoring
- Check CPU/Memory Usage (Linux):
top -b -n 1 | grep -E "Cpu|Mem"
- AWS Budget Alerts:
aws budgets create-budget \ --account-id 123456789012 \ --budget file://budget.json \ --notifications-with-subscribers file://notifications.json
3. Auto-Scaling for HPC
- Auto-Scaling Group CLI:
aws autoscaling create-auto-scaling-group \ --auto-scaling-group-name HPC-Cluster \ --launch-configuration-name HPC-LaunchConfig \ --min-size 2 --max-size 20 \ --vpc-zone-identifier "subnet-123456"
4. Storage Optimization
- S3 Lifecycle Policies:
aws s3api put-bucket-lifecycle-configuration \ --bucket hpc-data-bucket \ --lifecycle-configuration file://lifecycle.json
5. Windows Cost Tracking (PowerShell):
Get-AWSCostAndUsageReport -ReportName "HPC-Monthly" -TimeUnit MONTHLY -Format CSV -S3Bucket "cost-reports"
What Undercode Say
Optimizing HPC workloads in AWS requires a mix of FinOps strategies and technical commands. Use Spot Instances, auto-scaling, and granular cost monitoring to balance performance and budget. Regularly audit usage with AWS CLI and automate cost-saving policies.
Expected Output:
- AWS Cost Reports
- Spot Instance allocations
- Auto-scaled HPC clusters
- Storage lifecycle logs
References:
Reported By: Angelpizarro The – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
