Cloud spend sprawls across compute, storage, databases, AI APIs, SaaS licenses, Kubernetes, and on-prem infrastructure. Each platform has its own dashboard and export format.
Opactiv replaces that fragmentation with a single, unified analytics layer that represents every billable resource in a consistent model that is fully explorable and filterable.
Opactiv normalizes cost and usage data from heterogeneous sources into a single resource model.
- Compute: VMs, EC2 instances, Kubernetes pods, container workloads
- Storage: Block volumes, object storage buckets, database storage, backups
- Network: Data transfer between regions, cross-cloud traffic, network interfaces
- Database Services: Relational, NoSQL, managed warehouses including Snowflake and Databricks
- AI & ML Services: OpenAI, Anthropic, xAI usage, inference endpoints, model serving
- SaaS: Microsoft 365 license consumption and per-user pricing
- On-Premises & Datacenter: Custom resource types with cost models for physical infrastructure
Every resource shares common attributes – owner, pool, cloud account, region, tags, first seen, last active, enabling cross-cutting analytics.
Opactiv’s analytics layer supports expense breakdowns across nine standard dimensions, switchable on the fly.
| Dimension | What It Answers |
|---|---|
| Cloud Account | Which provider or account is driving spend? |
| Pool | Which team, project, or business unit is spending? |
| Owner | Which engineer or team lead owns the resources? |
| Region | Where geographically is the cost concentrated? |
| Service Name | Which cloud services dominate spend? |
| Resource Type | Is it instances, buckets, databases, clusters, environments? |
| Tag | How does spend break down by your own taxonomy? |
| Kubernetes Namespace | What is each K8s namespace costing? |
| Kubernetes Node | What is the per-node infrastructure cost? |
Switch dimensions in a click, combine filters, and always see daily time series to understand trendlines.
Analytics without filtering is noise. Opactiv supports over twenty filter parameters that can be combined freely.
By ownership and structure: Filter by cloud accounts, pools (including nested subpools), or individual owners.
By resource identity: Filter by resource type, service name, region, or provider; use pattern matching for names and IDs.
By tags – and missing tags: Filter for specific tag values or for resources missing required tags.
By lifecycle: Filter by first seen or last active to uncover long-running or recently idle resources.
By state and health: Filter for active/inactive resources, constraint violations, or those with optimization recommendations.
By Kubernetes metadata: Filter by namespace, node, or service for containerized workloads.
Every breakdown accepts a configurable date range (up to 365 days) and returns daily time series data.
Previous-period totals are computed automatically, so period-over-period comparisons are built into every query.
Opactiv breaks down data transfer costs by source and destination region alongside usage volume.
Cross-region and cross-cloud flows become visible, enabling data-locality and consolidation decisions based on facts.
Commitment-based discounts require ongoing monitoring. Dedicated breakdowns track:
- Reserved Instance utilization - coverage, utilization, idle reservations
- Savings Plan coverage - which workloads are covered vs. paying on-demand
- Discount offer analysis - whether commitments deliver expected savings
Filter the resource explorer to show only items with active recommendations, complete with saving amounts alongside actual cost.
Recommendations track active, dismissed, and excluded states, and their history shows when opportunities were identified and resolved.
Summary endpoints return total resource count, total cost, and total potential savings for any filter set.
Pool expense views provide hierarchical cost summaries with this-month vs. last-month comparison and forward forecasts.
Structured exports keep third-party BI tooling in sync with Opactiv’s enriched data.
- Pool expense exports to cloud storage on-demand or scheduled
- Continuous BI integration streaming cost, resource, and recommendation data
- Billing exports across organizations for multi-entity reporting
- Recommendation downloads in structured formats for offline analysis
Filtering, grouping, and time-series capabilities compose cleanly, so complex queries are as easy as simple ones.
Cost visibility at this granularity closes the gap between billing statements and the teams that generate the spend.
With Opactiv, every resource has an owner. Every dollar has a home. And every question about cloud spend has an answer.
