Simplify Cloud Spend, Sharpen Business Insights
The Attribute Platform
Automated Cost Grouping, without tagging
Attribute automatically groups cloud costs based on business metrics without needing to tag a single resource. Correlating cloud usage data from multiple sources, including our unique eBPF sensor, provides richer context and logical grouping of every cloud spend and eliminates blind spots without
manual calculations.
Easy access to Impactful Business Insights
Gain easy access to business insights that impact profit margins without the need for manual cost calculation. Attribute dramatically shortens the time to insight and visualizes the business impact of every cloud spend. Now, business and technical teams can make more accurate strategic decisions that align the cloud with its business value.
Cost-Visibility into the Application Layer
Gain end-to-end visibility of all the resources and services used by your application. Attribute’s eBPF sensor automatically identifies and maps all the interconnections in or between your applications
and calculates the exact costs using Back-propagation. We provide you with unmatched visibility into the cost of the application in real-time.
Query-Level Visibility
Drive accountability by displaying engineering-level granular cost insights on past blind spots. Attribute provides detailed visibility into every query, data transfer, and object consumed, revealing the causes and mechanisms behind the changes in your cloud bill.
Shared Resources Cost-Allocation
Attribute eliminates blind spots by automatically allocating shared resource costs to features, applications, or customers.
Why FinOps & DevOps Teams Are Moving Beyond Tagging
Traditional tools read old data. Attribute reads your live system.
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Cost attribution method
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Time to meaningful data
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Customer-level cost attribution
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Self-managed infrastructure
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Shared resource allocation
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AI cost attribution
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Data freshness
Traditional Tools
Attribute
Cost attribution method
Reads billing exports filtered by manually applied resource tags
Attributed costs based on actual workload behavior, no tags required
Time to meaningful data
Weeks to months of tagging work before attribution is useful
Immediately after sensor is deployed
Customer-level cost attribution
No concept of SaaS customers exists, cost-to-serve is a manual exercise
Automatic maps cloud spend to each customer across shared infrastructure
Self-managed infrastructure
Invisible; Kafka, Elasticsearch, and RabbitMQ on EC2 never appear in billing exports
Visible; eBPF operates on-prem and sees inside self-managed workloads
Shared resource allocation
Even splits or rough estimates
Allocation reflects what actually happened
AI cost attribution
Shows total LLM spend
Consumption based token allocation
Data freshness
Anomalies surface after the damage is done
Near real-time; cost is visible as workloads run