Updated
October 5, 2026
Explore how Harness and CAST AI stack up for cloud cost management across Kubernetes and multi-cloud.
Feature Comparison
| Feature | Harness | CAST AI |
|---|---|---|
| Solution | ||
| Deployment options | SaaS + Self-managed | SaaS only or limited |
| Multi-cloud support (AWS + Azure + GCP) | ||
| On-premises cost monitoring | ||
| Pricing model | % of cloud spend | |
| Cost Visibility | ||
| Cost Perspectives / Chargeback / Showback | ||
| Cost categories (dynamic bucketing) | ||
| Kubernetes cost allocation (node/cluster/workload) | ||
| Multi-cloud cost visualizations | ||
| Import 3rd-party costs (Datadog, Snowflake, etc.) | ||
| Snowflake Visibility | ||
| Microsoft Databricks Visibility | ||
| Out-of-the-box dashboards | ||
| Custom BI dashboards | ||
| Cost forecasting | ||
| Cloud asset inventory | ||
| Cost Optimization | ||
| Anomaly detection (AI/ML) | ||
| Automated idle resource management (AutoStopping) | Up to 70% savings | |
| Spot instance orchestration | ||
| Cluster orchestration on spot instances | Up to 90% savings | |
| Kubernetes node-pool recommendations | ||
| Kubernetes workload recommendations | ||
| AWS compute recommendations | ||
| Azure compute recommendations | ||
| GCP compute recommendations | ||
| RI/SP planning and recommendations | ||
| Automated RI/SP contract execution | ||
| Snowflake Recommendations | ||
| Microsoft Azure DataBricks Recommendations | ||
| Governance | ||
| Out-of-the-box governance policy rules | ||
| Automated governance rule enforcement | ||
| AI-assisted governance rule creation | ||
| Budgets | ||
| Alerts | ||
| Reporting | ||
| Administrative | ||
| Multi-currency support | ||
| MSP margin adjustments | ||
| Role-based access control | ||
| Full audit trails | ||
| APIs available | ||
| 24/7 support | ||
| Training resources | ||
| Documentation | ||
Key Differentiators
Harness CMA vs CAST AI: key differences
Multi-cloud beyond Kubernetes optimization
Harness CMA manages costs across all cloud resources — Kubernetes workloads and non-Kubernetes compute, storage, and services across AWS, Azure, and GCP — in a single unified platform.
CAST AI focuses primarily on Kubernetes cost optimization through automated node rightsizing and spot instance orchestration. Non-Kubernetes cloud costs (EC2, RDS, S3, Azure VMs) are outside its scope.
Cloud AutoStopping — automated idle resource savings
Harness Cloud AutoStopping automatically detects and stops idle non-production resources (VMs, EKS clusters, RDS instances) and restarts them on demand. Teams typically save 60–70% on non-production cloud costs with no engineer action required.
Most cost tools provide recommendations for idle resources but require engineers to manually act on them. The savings potential exists on paper but is rarely realized in practice.
AI-assisted governance and automated enforcement
Harness CMA includes out-of-the-box governance rules, AI-assisted rule creation, and automated enforcement that can stop non-compliant resources from running — preventing cost overruns before they happen.
Most FinOps tools provide budget alerts but lack automated enforcement. Policy violations are reported after the fact, not prevented.
Decision Guide
CAST AI is good for
- Your entire cloud spend is Kubernetes and you want specialized K8s optimization
- Automated node rightsizing and spot orchestration are the primary goals
Harness is best for
- You need cost management across both Kubernetes and non-Kubernetes resources
- Multi-cloud visibility and governance are requirements
- A single FinOps platform for all cloud costs is preferred
Summary
CAST AI is the best Kubernetes optimizer. Harness CMA is the best FinOps platform — including Kubernetes.
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