Running Kubernetes in production can get expensive fast. Over the past year, I've helped several startups reduce their AWS bills by 40-70% through strategic cost optimization.
Here are the five most impactful strategies that delivered real results.
1. Right-Size Your Resource Requests and Limits
The biggest waste I see is over-provisioned pods. Most teams set resource requests based on peak load assumptions, leading to significant waste.
What We Did:
- Implemented monitoring with Prometheus and Grafana
- Analyzed actual resource usage over 30 days
- Right-sized requests to 80% of observed usage
- Set appropriate limits to prevent resource hogging
Result: 40% reduction in compute costs by eliminating unused CPU and memory allocations.
# Before: Over-provisioned
resources:
requests:
memory: "2Gi"
cpu: "1000m"
limits:
memory: "4Gi"
cpu: "2000m"
# After: Right-sized
resources:
requests:
memory: "512Mi"
cpu: "250m"
limits:
memory: "1Gi"
cpu: "500m"
2. Implement Cluster Autoscaling + Spot Instances
Most teams either over-provision nodes or scale manually. Both approaches waste money.
The Strategy:
- Configure Cluster Autoscaler for automatic scaling
- Use Spot Instances for non-critical workloads
- Mix of On-Demand and Spot for resilience
Configuration Example:
apiVersion: v1
kind: ConfigMap
metadata:
name: cluster-autoscaler-status
namespace: kube-system
data:
nodes.max: "20"
nodes.min: "3"
scale-down-delay-after-add: "10m"
scale-down-unneeded-time: "10m"
Result: 30% cost reduction through automatic scaling and spot instance usage.
3. Optimize Data Transfer Costs
Data transfer charges are often overlooked but can be substantial, especially for data-heavy applications.
Key Optimizations:
- Keep related services in the same Availability Zone
- Use VPC endpoints for AWS services
- Implement intelligent caching strategies
- Compress data in transit
Before/After Results:
- Before: $800/month in data transfer costs
- After: $200/month (75% reduction)
4. Storage Optimization
Storage costs accumulate quickly, especially with persistent volumes and backups.
Strategies That Worked:
- Implemented automated PV cleanup for terminated pods
- Moved old data to cheaper storage classes (IA, Glacier)
- Optimized backup retention policies
- Used storage classes based on access patterns
Example Configuration:
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
name: gp3-optimized
provisioner: ebs.csi.aws.com
parameters:
type: gp3
iops: "3000"
throughput: "125"
encrypted: "true"
allowVolumeExpansion: true
volumeBindingMode: WaitForFirstConsumer
5. Monitor and Alert on Cost Anomalies
Without proper monitoring, costs can spiral out of control quickly.
Our Monitoring Stack:
- AWS Cost Explorer for high-level trends
- Kubecost for Kubernetes-specific insights
- Grafana dashboards for real-time monitoring
- Slack alerts for cost anomalies
Alert Configuration Example:
groups:
- name: cost-alerts
rules:
- alert: HighInfrastructureCost
expr: aws_billing_total > 5000
for: 1h
labels:
severity: warning
annotations:
summary: "Infrastructure costs exceeded $5000"
Implementation Timeline
Week 1-2: Resource right-sizing and monitoring setup
Week 3: Cluster autoscaler and spot instance implementation
Week 4: Storage and data transfer optimization
Ongoing: Cost monitoring and continuous optimization
Results Summary
After implementing these strategies across three different startups:
- Average cost reduction: 55%
- Implementation time: 3-4 weeks
- Payback period: 1 month
- Performance impact: None (actually improved in some cases)
Key Takeaways
- Start with monitoring - You can't optimize what you can't measure
- Right-size first - This delivers the biggest immediate impact
- Automate everything - Manual processes don't scale
- Monitor continuously - Costs can drift over time
- Performance matters - Don't sacrifice reliability for cost savings
Cost optimization isn't a one-time activity. Set up proper monitoring, implement these strategies systematically, and review monthly. Your CFO will thank you.
Need help optimizing your Kubernetes costs? We've helped dozens of startups reduce their infrastructure spend while improving reliability. Get in touch for a free cost assessment.
