Cut Kubernetes Costs by 60%
Without Affecting Performance
Eliminate overprovisioning, automate resource right-sizing, and gain complete cost visibility across your Kubernetes infrastructure with AI-powered optimization.
⚡ 5-minute Helm install • 📊 Instant cost analysis • 💰 Average 60% savings
Kubernetes Cost Challenges
Organizations waste 60-80% of their Kubernetes budget on overprovisioned resources.
80% Resource Waste
Kubernetes clusters run with massive overprovisioning due to conservative resource requests
No Cost Visibility
Teams can't see costs by namespace, app, or team making optimization impossible
Manual Optimization
DevOps teams spend weeks manually analyzing resource usage patterns
Fear of Right-sizing
Teams avoid downsizing resources due to fear of performance degradation
How We Solve Kubernetes Cost Problems
Comprehensive AI-powered optimization mapped to your specific challenges.
AI-Powered Resource Right-sizing
Automatically analyze pod resource usage patterns and generate precise right-sizing recommendations
- Pod-level CPU/memory analysis
- ML-powered recommendations
- Gradual optimization
- Performance protection
Intelligent Autoscaling
Enhanced HPA/VPA with predictive scaling based on application patterns and business cycles
- Predictive scaling
- Custom metrics support
- Cost-aware decisions
- Multi-dimensional scaling
Complete Cost Visibility
Real-time cost attribution and allocation across namespaces, teams, and applications
- Namespace cost allocation
- Team chargeback
- Resource cost tracking
- Usage analytics
Spot Instance Optimization
Intelligent spot instance management with automatic fallback and workload placement
- Multi-AZ diversification
- Automatic fallback
- Workload-aware placement
- 90% cost savings
Outcomes You Can Expect
Proven results from hundreds of Kubernetes optimization projects.
Kubernetes Optimization Workflow
Step-by-step process from deployment to ongoing optimization.
Cluster Discovery
Deploy DeepCost agent via Helm chart to start collecting detailed resource metrics
AI Analysis
Machine learning analyzes pod usage patterns, identifies waste, and calculates optimization opportunities
Smart Recommendations
Generate right-sizing, scaling, and spot instance recommendations with confidence scores
Safe Implementation
Gradually apply optimizations with automated rollback if performance issues are detected
Continuous Monitoring
Monitor results and continuously optimize as workload patterns evolve
Customer Success Stories
Real results from teams who optimized their Kubernetes costs.
TechFlow Inc
- $28,000/month saved
- Zero performance impact
- 2-week payback period
"DeepCost cut our K8s costs by 68% in the first month. The AI recommendations were spot-on and saved our team hundreds of hours."
DataStream Co
- 74% cost reduction
- 3x faster job completion
- Automatic scaling
"Our data processing costs dropped from $45K to $12K monthly while actually improving performance. The spot instance management is flawless."
Kubernetes Optimization FAQ
Will optimization affect my application performance?
No. Our AI includes safety margins in all recommendations and continuously monitors performance. If any degradation is detected, changes are automatically rolled back.
How quickly will I see cost savings?
Most customers see 30-50% cost reduction within the first week. Full optimization typically achieves 60-80% savings within 30 days.
Does this work with my existing Kubernetes setup?
Yes. DeepCost integrates with any Kubernetes distribution (EKS, GKE, AKS, self-managed) and works alongside existing monitoring tools like Prometheus and Grafana.
Can I set limits to prevent over-optimization?
Absolutely. You can set minimum resource thresholds, exclude critical workloads, and configure custom safety margins per application or namespace.
What about compliance and security requirements?
DeepCost respects all pod security policies, resource quotas, and compliance requirements. All optimizations maintain your existing security posture.