Spot, Savings Plans, RIs

# Karpenter NodePool — Spot with fallback to On-Demand
apiVersion: karpenter.sh/v1
kind: NodePool
metadata:
  name: spot-general
spec:
  template:
    spec:
      requirements:
        - key: karpenter.sh/capacity-type
          operator: In
          values: ["spot", "on-demand"]   # spot preferred, on-demand fallback
        - key: kubernetes.io/arch
          operator: In
          values: ["arm64", "amd64"]       # Graviton preferred
        - key: karpenter.k8s.aws/instance-family
          operator: In
          values: ["m7g", "m7i", "m6g", "m6i", "c7g", "c7i"]
        - key: karpenter.k8s.aws/instance-size
          operator: In
          values: ["xlarge", "2xlarge", "4xlarge"]
      nodeClassRef:
        group: karpenter.k8s.aws
        kind: EC2NodeClass
        name: default
  disruption:
    consolidationPolicy: WhenUnderutilized
    consolidateAfter: 30s
  limits:
    cpu: "1000"
    memory: 4000Gi

def savings_plan_analysis(
    monthly_on_demand: float,
    commitment_pct: float = 0.70,   # commit 70% of baseline
    discount_1yr: float = 0.33,     # ~33% off with 1-year no-upfront
    discount_3yr: float = 0.50,     # ~50% off with 3-year no-upfront
):
    """
    Simple Savings Plan sizing model.
    Commit to predictable baseline, leave headroom for On-Demand burst.
    """
    annual_on_demand = monthly_on_demand * 12
    committed_monthly = monthly_on_demand * commitment_pct
    hourly_commitment = committed_monthly / 730   # hours/month
 
    cost_1yr = (committed_monthly * (1 - discount_1yr) * 12
                + (monthly_on_demand - committed_monthly) * 12)
    cost_3yr = (committed_monthly * (1 - discount_3yr) * 12 * 3
                + (monthly_on_demand - committed_monthly) * 12 * 3)
 
    saving_1yr = annual_on_demand - cost_1yr
    saving_3yr_annual = (annual_on_demand * 3 - cost_3yr) / 3
 
    print(f"On-Demand baseline:       ${monthly_on_demand:,.0f}/mo  ${annual_on_demand:,.0f}/yr")
    print(f"Hourly commitment:         ${hourly_commitment:.2f}/hr")
    print(f"1-yr Savings Plan saving:  ${saving_1yr:,.0f}/yr")
    print(f"3-yr Savings Plan saving:  ${saving_3yr_annual:,.0f}/yr (annualized)")
    return {"hourly_commitment": hourly_commitment, "saving_1yr": saving_1yr}
 
savings_plan_analysis(monthly_on_demand=8000)
# Output:
# On-Demand baseline:       $8,000/mo  $96,000/yr
# Hourly commitment:         $7.67/hr
# 1-yr Savings Plan saving:  $21,912/yr
# 3-yr Savings Plan saving:  $33,600/yr (annualized)

def ri_payback_analysis(
    on_demand_hourly: float,
    ri_upfront: float,
    ri_hourly: float,
    term_years: int = 1,
):
    hours = term_years * 8760
    on_demand_total = on_demand_hourly * hours
    ri_total = ri_upfront + (ri_hourly * hours)
    saving = on_demand_total - ri_total
    payback_months = ri_upfront / ((on_demand_hourly - ri_hourly) * 730) if ri_upfront > 0 else 0
 
    print(f"On-Demand {term_years}yr:  ${on_demand_total:,.0f}")
    print(f"RI {term_years}yr total:   ${ri_total:,.0f}")
    print(f"Net saving:         ${saving:,.0f}  ({saving/on_demand_total*100:.0f}%)")
    if payback_months:
        print(f"Upfront payback:    {payback_months:.1f} months")
 
# RDS db.r6g.2xlarge: On-Demand $0.96/hr, 1yr partial-upfront RI
ri_payback_analysis(on_demand_hourly=0.96, ri_upfront=1500, ri_hourly=0.506)

SELECT
  line_item_line_item_type,
  ROUND(SUM(line_item_unblended_cost), 0) AS cost_usd,
  ROUND(
    100.0 * SUM(line_item_unblended_cost)
    / SUM(SUM(line_item_unblended_cost)) OVER ()
  , 1) AS pct_of_compute
FROM cur_db.cur_table
WHERE line_item_product_code = 'AmazonEC2'
  AND line_item_usage_type LIKE '%BoxUsage%'
  AND line_item_usage_start_date >= DATE_TRUNC('month', CURRENT_DATE)
GROUP BY 1
ORDER BY cost_usd DESC;