Energy Visibility
Achieve unprecedented visibility into your data center energy consumption with rack-level attribution, application fingerprinting, and real-time monitoring that drives actionable cost optimization.
Energy Visibility Services
Fine-grained energy attribution, efficiency ranking, and cost allocation across racks, applications, and business units.
Rack-Level Energy Attribution
Precise energy consumption tracking at the individual rack level, enabling granular visibility into power usage patterns and cost allocation.
- Accurate cost allocation
- Identify inefficient racks
- Optimize placement decisions
Application Energy Fingerprinting
Create unique energy signatures for applications to understand their power consumption characteristics across different operational states.
- Application-level insights
- Workload optimization
- Capacity planning
Real-Time Power Monitoring
Continuous monitoring of power consumption with sub-second granularity for immediate visibility into energy usage patterns.
- Instant anomaly detection
- Real-time dashboards
- Proactive management
Energy Efficiency Ranking
Comparative analysis and ranking of equipment, racks, and zones based on energy efficiency metrics.
- Benchmark performance
- Identify improvement areas
- Track progress
Cost Allocation Engine
Automated distribution of energy costs to business units, applications, and customers based on actual consumption.
- Fair cost distribution
- Chargeback automation
- Budget transparency
Case Studies
Real-world results from organizations that transformed their energy visibility.
Global Financial Services Firm
Challenge
Unable to accurately allocate $12M annual energy costs across 200+ trading applications
Solution
Implemented rack-level attribution with application fingerprinting
Results
- 98.5% cost allocation accuracy achieved
- $2.1M annual savings identified
- 15% reduction in stranded capacity
Hyperscale Cloud Provider
Challenge
Needed real-time visibility across 50,000+ servers to optimize energy procurement
Solution
Deployed real-time power monitoring with predictive analytics
Results
- Sub-second visibility across all infrastructure
- $8.4M saved through demand response participation
- PUE improved from 1.45 to 1.28
Technical Specifications
Enterprise-grade infrastructure designed for accuracy, scalability, and seamless integration with your existing data center management systems.
Integration Capabilities
- DCIM platforms (Nlyte, Sunbird, Device42)
- Hypervisor APIs (VMware, Hyper-V, KVM)
- BMS and EPMS systems
- BI tools (Power BI, Tableau, Grafana)
- Financial systems for chargeback
Frequently Asked Questions
How does rack-level energy attribution work?
Our system combines direct power measurements from intelligent PDUs with inference algorithms that analyze server utilization, thermal signatures, and workload patterns. This hybrid approach achieves ±0.5% accuracy at the rack level without requiring individual server metering.
Can you attribute energy to specific applications?
Yes. Application energy fingerprinting creates unique power consumption signatures by correlating workload metrics (CPU, memory, I/O) with measured power draw. Machine learning models then attribute energy consumption to specific applications, containers, or virtual machines.
What data sources are required?
At minimum, we require power measurements from PDUs or UPS systems. For enhanced accuracy, we integrate with DCIM platforms, hypervisor APIs, and building management systems. Our platform supports SNMP, Modbus, BACnet, and REST APIs.
How quickly can we see ROI?
Most customers identify actionable savings within the first 30 days. Typical ROI is achieved within 6-9 months through improved cost allocation, stranded capacity recovery, and efficiency improvements.