medy-gribkov Container Right-Sizing
Monitor CPU and memory for 7 days before setting limits. Set requests to P50, limits to P99.
BAD: Guessing resource limits. Over-provisioned containers waste money.
resources:
requests:
memory: "1Gi"
cpu: "1000m"
limits:
memory: "2Gi"
cpu: "2000m"
GOOD: Use actual usage data from monitoring.
kubectl top pod myapp-12345 --containers
If P50 is 200Mi/100m and P99 is 400Mi/300m:
resources:
requests:
memory: "200Mi"
cpu: "100m"
limits:
memory: "400Mi"
cpu: "300m"
Vertical Pod Autoscaler
Get sizing recommendations from real workload data.
apiVersion: autoscaling.k8s.io/v1
kind: VerticalPodAutoscaler
metadata:
name: myapp-vpa
spec:
targetRef:
apiVersion: apps/v1
kind: Deployment
name: myapp
updateMode: "Off" # Recommendation mode only
Check recommendations:
kubectl describe vpa myapp-vpa
Cost Calculation
Example: 10 pods running 24/7 with 1Gi memory, 1 CPU.
- Memory: 10 pods x 1 GiB x $0.0004/hr = $29/month
- CPU: 10 pods x 1 core x $0.04/hr = $292/month
- Total: $321/month
Right-size to 200Mi memory, 100m CPU:
- Memory: 10 pods x 0.2 GiB x $0.0004/hr = $5.80/month
- CPU: 10 pods x 0.1 core x $0.04/hr = $29.20/month
- Total: $35/month
Savings: 89% ($286/month)
Horizontal Pod Autoscaler
Scale replicas based on actual load. Do not run excess capacity during low traffic.
BAD: Fixed replica count. Wastes money overnight and weekends.
spec:
replicas: 10
GOOD: HPA scales from 2 to 10 based on CPU usage.
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: myapp-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: myapp
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
Cost Impact
If baseline traffic needs 2 pods and peak traffic needs 10 pods for 2 hours/day:
- Fixed 10 replicas: 10 x 24hr = 240 pod-hours/day
- HPA (2 baseline + 8 peak for 2hr): 2 x 24 + 8 x 2 = 64 pod-hours/day
Savings: 73% (176 pod-hours/day)
CDN Caching
Cache static assets with long TTLs. Use content hashes for cache busting.
BAD: No cache headers. Every request hits the origin.
GET /app.js
Cache-Control: no-cache
GOOD: 1-year cache with content hash in filename.
GET /app.abc123.js
Cache-Control: public, max-age=31536000, immutable
API Response Caching
Even 60 seconds of caching eliminates burst traffic.
GET /api/categories
Cache-Control: public, max-age=60, s-maxage=60
Stale-While-Revalidate
Serve cached content while fetching fresh data in the background.
Cache-Control: max-age=60, stale-while-revalidate=300
Cost Impact
Example: 1M requests/month to origin at $0.01/10k requests = $100/month. With 90% cache hit rate: origin requests drop to 100k ($1/month). Savings: 99%.
Database Query Cost
Monitor query frequency x duration. A 10ms query running 10,000/min costs more than a 1s query running once.
BAD: N+1 query in a loop.
const orders = await db.orders.findMany();
for (const order of orders) {
order.user = await db.users.findUnique({ where: { id: order.userId } });
}
GOOD: Single query with join.
const orders = await db.orders.findMany({ include: { user: true } });
Slow Query Logging
Enable slow query log. Investigate queries over 100ms.
-- PostgreSQL
SET log_min_duration_statement = 100;
-- MySQL
SET long_query_time = 0.1;
Use EXPLAIN ANALYZE to find missing indexes.
EXPLAIN ANALYZE SELECT * FROM orders WHERE user_id = 123;
Serverless Cold Starts
BAD: Java Lambda with 1GB memory, VPC attached. Cold start: 5 seconds.
GOOD: Node.js Lambda with 512MB memory, no VPC. Cold start: 200ms.
Lambda allocates CPU proportional to memory. Under-provisioned memory = slower execution = higher duration costs.
Provisioned Concurrency
Eliminate cold starts for latency-sensitive functions. Cost: ~$26/month for 5 concurrent x 512MB. Use only for critical functions.
Build Time Optimization
Cache dependencies. Download once, reuse until lockfile changes.
BAD: Installing dependencies on every build.
COPY . .
RUN npm install
GOOD: Cache dependencies in a separate layer.
COPY package*.json ./
RUN npm ci
COPY . .
Parallel Build Steps
Run linting, type checking, and tests concurrently in CI. Total time = max(build, lint, test), not sum.
Turborepo Remote Cache
Share build artifacts across CI machines. First build uploads cache, subsequent builds skip rebuilding. Savings: ~70% on CI costs.
Spot Instances, Reserved Capacity, and Cost Monitoring
AWS spot instances (70-90% savings), reserved instances (40% savings), budget alerts, resource tagging, and non-production shutdown automation. See references/cloud-examples.md for detailed configs and scripts.