At PointFive, we're redefining how organizations understand and manage their cloud spend. As we champion the emerging category of Cloud Efficiency Posture Management (CEPM), we’re proud to offer the industry's most advanced cost optimization detection engine, built from the ground up to work seamlessly across AWS, GCP, and Azure.

In this post, we spotlight Azure—a cloud that presents a particularly thorny challenge when it comes to granular cost attribution.

The Challenge: Hidden Costs Within Containers

Azure’s billing model often consolidates multiple resources under a single entity, obscuring the true cost contributors. This opacity makes it nearly impossible for finance and engineering teams to identify specific inefficiencies, let alone act on them.

Here are three common examples:

• Log Analytics Tables: These don’t show up as independent line items. Their costs are rolled into the Log Analytics Workspace, hiding table-level inefficiencies. Pinpointing noisy tables or adjusting ingestion costs against real usage becomes significantly harder.
  
  
• SQL Databases in Elastic Pools: Individual databases inherit cost from the Elastic Pool, masking how databases actually utilize compute resources. This makes it difficult to detect workload imbalance or right-size the pool.
  
  
• NetApp Volumes: Their costs are absorbed into the NetApp Capacity Pool.  It becomes challenging to isolate and optimize volume-specific usage, often leading to over-allocated storage and inefficient capacity planning.
  
  

The result? Missed opportunities and cloud inefficiencies hidden in plain sight.

PointFive’s Approach: Granular Cost Attribution

Our detection engine delivers granular cost visibility that native billing data doesn’t expose. Using proprietary models and a deep understanding of Azure’s architecture, we reconstruct cost lineage down to the actual consuming resource, as non-trivial and fragmented as it can be.

This method is analogous to what OpenCost and AWS SCAD do for Kubernetes: slicing shared cluster costs down to the level of individual pods or deployments.

The Value to Customers

This proprietary cost decomposition unlocks two major benefits:

1. Precision & Visibility
   Gain true resource-level cost attribution. You can now slice and dice your costs by the exact Azure entity consuming them—be it a specific database, a storage volume, or a log table.
   
   
2. Hidden Opportunity Detection
   Surface cost optimization opportunities that are otherwise completely invisible under the standard billing view. Our engine detects and flags inefficiencies buried under pooled or abstracted Azure services.