Cloud FinOps is a discipline that demands precision. Knowing that your AWS bill went up is not enough – you need to know which team owns the cost, whether the spend was expected, whether the underlying resources are being used efficiently, and what the forward trajectory looks like.
Opactiv is built for exactly this. It covers the full FinOps lifecycle – visibility, allocation, optimization, and governance – across all major public cloud providers, with the depth of analysis that engineering and finance teams need to act with confidence.
Opactiv connects directly to the authoritative cost data source for each cloud provider – not a summary API, but the full-resolution billing data.
AWS integrates via the Cost & Usage Report (CUR), the most granular billing format AWS produces. Opactiv processes CUR files in both Parquet and CSV formats, capturing every line item including product metadata, reservation and Savings Plan fields, EDP discounts, cost categories, and all custom resource tags. Reserved Instance ARNs, Savings Plan ARNs, effective costs, and normalization factors are all imported and tracked.
Microsoft Azure integrates via the Azure Consumption API, with full support for multi-level tenant authentication. Opactiv captures meter IDs, resource groups, subscription isolation, reservation data, and billing currency per account. Budget forecasting data from Azure Cost Management is also imported.
Google Cloud integrates via BigQuery cost export, capturing SKU-based pricing with credit deduction, preemptible instance identification, and the full region and zone metadata. Resource IDs are hashed for deduplication across billing periods.
Alibaba Cloud captures pay-as-you-go charges alongside subscription and commitment costs, resource package discounts, and coupon tracking – reflecting the full economic picture of Alibaba’s pricing model.
Oracle Cloud Infrastructure, OVH, and Yandex Cloud are also fully supported, bringing European and Asia-Pacific cloud environments into the same unified cost model.
Every provider’s data is normalized to a common resource model with consistent fields – owner, pool, region, service, tags, cost, first seen, last seen – so analytics work identically regardless of which cloud is under the lens.
Raw cloud billing data maps poorly to organizational structure. A cloud account is not a team. A resource group is not a cost centre. Opactiv bridges that gap.
The pool hierarchy provides a flexible budget and allocation structure that mirrors your organization’s actual shape – business units, teams, projects, or any other grouping. Resources discovered from cloud accounts are assigned to pools, giving every dollar a clear organizational home.
Tag-based cost allocation lets organizations leverage the tagging strategies already applied to cloud resources. Opactiv breaks down spend by any tag key or value, and surfaces resources that are missing expected tags – turning the tag compliance gap into a visible, actionable report rather than a silent data quality problem.
Owner attribution assigns individual resources to employees, creating accountability at the resource level. Engineers can see the costs their own resources generate. Managers can see costs across their teams. Finance teams see the organizational rollup.
Opactiv’s recommendation engine runs continuously across connected cloud accounts, covering the full range of optimization opportunities that FinOps practitioners care about.
Underutilized compute is one of the largest sources of recoverable cloud spend. Opactiv analyses CPU utilization metrics across instances to identify candidates for rightsizing, with configurable metric types – maximum, average, 50th percentile, 99th percentile – to match the sensitivity required for different workload types.
Rightsizing recommendations are supported for:
- AWS EC2, Azure Virtual Machines, Google Cloud instances, Alibaba ECS
- AWS RDS and Azure database instances for managed database rightsizing
Instance generation upgrade recommendations identify workloads still running on older instance families where a newer generation offers better price-to-performance at the same or lower cost – available for AWS, Azure, and Alibaba.
Reserved Instances and Savings Plans consistently deliver major savings versus on-demand pricing, but identifying the right commitments requires analysis of actual usage patterns rather than guesswork.
Opactiv’s dedicated RISP (Reserved Instance and Savings Plan) system analyses usage across AWS and Azure to:
- Identify workloads running on-demand that have stable enough patterns to justify commitment purchases
- Recommend specific RI types (Standard All Upfront, Convertible No Upfront) with projected savings
- Track existing RI and SP utilization, surfacing idle reservations and uncovered usage
- Monitor effective rates and expected costs against actuals
For Alibaba Cloud, the equivalent subscription commitment analysis identifies instances where switching from pay-as-you-go to monthly or annual subscription pricing would reduce costs.
Resources that accumulate without active use are a persistent drain on cloud budgets. Opactiv detects:
- Abandoned instances - running VMs with consistently low CPU and negligible network traffic
- Stopped instances - VMs in a stopped state incurring storage costs
- Short-living instances - ephemeral workloads that would benefit from spot or preemptible pricing
- Unattached volumes - block storage sitting detached from any instance
- Unused Elastic IPs - allocated but unassociated addresses generating idle charges
- Orphaned load balancers - load balancers with no active targets
- Abandoned object storage buckets - empty buckets generating maintenance costs
- Obsolete snapshots and snapshot chains - backups with no associated base resource
- Unused machine images - AMIs and equivalents not referenced by any current resource
For S3-hosted data, Opactiv analyses object access frequency patterns to identify buckets that would benefit from S3 Intelligent-Tiering.
The analysis calculates actual access distribution across frequent, infrequent, and archive tiers, compares the resulting Intelligent-Tiering cost against current storage costs, and surfaces only the buckets where the switch delivers net savings.
Cloud security gaps frequently have cost implications – exposed resources attract unplanned usage and incident response costs. Opactiv’s security recommendations cover overly permissive security groups, publicly accessible storage, inactive IAM users, and idle service accounts across providers.
Purchasing commitments is only half the work. Monitoring whether they are being used effectively is equally important, and harder without dedicated tooling.
Opactiv tracks RI and SP utilization with normalized capacity factors for AWS, surfacing:
- Coverage gaps - on-demand usage that could be covered by existing or additional commitments
- Idle reservations - RIs with low utilization rates that may need to be sold or exchanged
- Effective rate tracking - the blended rate being achieved across on-demand and committed spend
- Uncovered usage - workloads running without any commitment coverage
Utilization and coverage data feed directly into the analytics layer, so RI/SP performance can be sliced by cloud account, region, or instance family alongside general expense analytics.
Opactiv’s budget system is hierarchical, matching the pool structure used for cost allocation. Every pool in the hierarchy carries a budget limit, and the system continuously monitors actuals against that limit.
Pool budget alerts notify the assigned owner – and optionally additional recipients including Slack channels – when spend approaches or exceeds the limit.
- Organizational constraint policies extend governance beyond individual pools
- Expense Anomaly detection identifies cost spikes against historical baselines
- Resource Count Anomaly detection flags unexpected resource proliferation
- Expiring Budget alerts warn when a pool is approaching exhaustion
- Recurring Budget tracking monitors spend against cyclic allocations
- Resource Quota enforcement applies hard limits on resource counts
- Tagging Policy enforcement requires resources to carry specified tags
Constraints run continuously and capture a history of limit hits, giving operations and finance teams an audit trail of when thresholds were breached and what the spend pattern looked like at the time.
Cloud costs are ultimately generated by individual resources. Opactiv tracks every resource from first discovery to deletion, maintaining a complete lifecycle record that includes:
- First seen - when the resource was first detected in billing data
- Last seen - the most recent billing period in which the resource appeared
- Active status - whether the resource is still generating charges
- Accumulated cost - total spend attributed to the resource
- Constraint violations - whether the resource has breached any limit
Resource-level constraints allow teams to set daily expense limits (DEL) and total expense limits (TEL) on individual resources.
Per-resource recommendations are surfaced inline with cost data, so engineers see not just what each resource costs today but what it could cost if rightsized, reserved, or replaced.
Development, staging, and testing environments that run around the clock consume cloud budget at production rates during the hours nobody is using them. Opactiv’s power scheduling system automates start and stop operations for VM workloads on configurable schedules.
Schedules are timezone-aware, can be scoped to specific resource groups or pools, and support multiple daily triggers – powering environments down at the end of the working day and back up before the team starts.
For shared cloud environments – integration test environments, demo instances, performance testing rigs – uncoordinated access leads to resource conflicts, unreliable results, and persistent idle costs when environments are left running between uses.
Opactiv’s environment booking system lets teams treat shared cloud environments as reservable resources. Engineers check out an environment for a specific window, it is released automatically at the end of the booking, and the system prevents conflicting simultaneous access.
All of the above generates value only if practitioners can get to the data they need without friction. Opactiv’s analytics layer is designed for the questions FinOps teams ask routinely.
- Daily cost time series for any dimension and date range, with automatic previous-period comparison
- Traffic expense analysis that breaks down data transfer costs by source and destination region
- Available filters API that enumerates all distinct values for every filterable dimension
- Summary views returning total resource count, cost, and optimization savings for any filter set
- BI export that pushes raw cost, resource, and recommendation data to AWS S3 or Azure Blob Storage
Whether an organization is at the beginning of its cloud cost management journey or operating a mature FinOps practice, Opactiv provides the capabilities to support it.
Visibility through native billing integration and unified analytics. Allocation through hierarchical pools and owner attribution. Optimization through continuous recommendations. Governance through budget policies, anomaly detection, tagging enforcement, and resource-level constraints.
The result is a cloud cost management practice that scales with your cloud footprint – and keeps every dollar accountable.
