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Optimizing Cloud Commitment Coverage Against Real Workload Shape
An engineering organization holds reserved instance and savings plan commitments purchased two years ago against a workload that has since changed substantially.
Runs onSahayHow the work runs
The pressure that made this worth automating, the steps the system runs, and what came out the other side.
Pressure & Trigger Points
- Commitment coverage no longer matches the instance families and regions actually in use.
- Finance renews commitments on historic spend because nobody can model the alternative.
- Unused commitment and on-demand overspend coexist in the same monthly bill.
The run · 5 operational steps
Click any step to inspect telemetry signals, model reasoning, and governance gates.
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Coverage Analysis
Current commitments are compared against actual consumption by family, region, and hour.
Input Signal:
Real-time operational telemetry & queue
Reasoning Pattern:
MCP grounded vector inference
Governance Gate:
Policy constrained with audit write-back
Verified Business Outcomes
- Unused commitment and on-demand overspend quantified separately.
- Renewal modelled against projected rather than historic consumption.
- Consumption attributed to the teams and services that drive it.
Capabilities this relies on
- system connectors
- anomaly detection
- root cause reasoning
- forecasting
- workflow orchestration
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