Updated
September 10, 2026
Harness helps engineers focus on creating great software, not chasing down cloud costs — going beyond Yotascale's analytics.
Feature Comparison
| Feature | Harness | Yotascale |
|---|---|---|
| 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
What Harness CCM adds beyond Yotascale
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.
Deep Kubernetes cost allocation
Harness provides granular Kubernetes cost allocation by namespace, workload, label, and team — plus node rightsizing recommendations and Cluster Orchestrator for spot-based cost reduction up to 90%.
Most cost tools cannot allocate shared Kubernetes cluster costs to individual teams, workloads, or namespaces — leaving significant blind spots in multi-tenant cluster cost reporting.
AI-assisted governance and automated enforcement
Harness CCM 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
Yotascale is good for
- Business-context cost allocation and engineering team attribution are primary needs
- Lightweight analytics focused on cost ownership is sufficient
Harness is best for
- FinOps automation beyond contextual analytics is needed
- Kubernetes cost management and rightsizing are priorities
- RI/SP automation and governance enforcement are requirements
Summary
Yotascale shows teams their cloud costs in context. Harness CCM helps them reduce those costs.
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