> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cloudthinker.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Savings Tracking

> Measure realized cloud cost savings against projections and track optimization ROI over time

Savings Tracking measures the actual dollar impact of every implemented recommendation — recording the baseline, monitoring cost changes post-implementation, and surfacing variance against the original projection.

## KPIs

| Metric              | Description                                              |
| ------------------- | -------------------------------------------------------- |
| Monthly savings     | Total realized savings in the current calendar month     |
| Cumulative savings  | All-time savings since tracking began                    |
| Implementation rate | Recommendations implemented ÷ total identified           |
| Accuracy rate       | Actual savings ÷ projected savings (target: 80–120%)     |
| Time to implement   | Days from recommendation creation to implementation      |
| Capture rate        | Percentage of identified savings that have been realized |

## How savings are tracked

When [Alex](/guide/agents/alex) implements a recommendation, CloudThinker records the implementation date, stores the projected savings, and begins monitoring actual cost changes.

For recommendations you implement manually:

1. Open the recommendation and mark it **Implemented**.
2. Enter the actual monthly savings amount.
3. Add implementation notes and any supporting documentation.

## Savings attribution

| Dimension   | Values                                                                                                                                                                                                |
| ----------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| By agent    | [Alex](/guide/agents/alex) (infrastructure, compute), [Kai](/guide/agents/kai) (Kubernetes), [Tony](/guide/agents/tony) (database), [Oliver](/guide/agents/oliver) (security-compliant optimizations) |
| By source   | [CloudKeepers](/guide/infrastructure/cloudkeepers) findings, [assessments](/guide/infrastructure/assessment), conversations, manual entries                                                           |
| By category | Right-sizing, reserved capacity, unused resources, storage optimization, architecture changes                                                                                                         |
| By provider | AWS, GCP, Azure, multi-cloud totals                                                                                                                                                                   |

## Projections

Alex forecasts future savings from your active recommendation backlog:

| Input                   | How it's used                                                    |
| ----------------------- | ---------------------------------------------------------------- |
| Active recommendations  | Sum of estimated savings weighted by implementation probability  |
| Implementation velocity | Historical rate of recommendation completion                     |
| Capture rate trend      | Rolling accuracy of past projections compared to actual outcomes |

## Validation

Actual cost changes are tracked automatically against each implementation:

1. Baseline cost is recorded on the implementation date.
2. Actual costs are monitored at 30, 60, and 90 days post-implementation.
3. Variance from the original projection is calculated and surfaced.

Common causes of variance: workload changes after optimization, new resources created in the same category, provider pricing changes, and seasonal usage patterns.

## Example prompts

```text theme={null}
@alex #report monthly savings summary for October
@alex #report savings breakdown by agent and category for Q3
```

```text theme={null}
@alex what is our total savings potential if we implement all active recommendations?
@alex project savings for next quarter based on pending recommendations
```

```text theme={null}
@alex compare projected vs actual savings for last quarter
@alex why did the RDS right-sizing recommendation save less than projected?
```

```text theme={null}
@alex show implementation rate trend over the past six months
@alex which recommendation categories have the best accuracy rate?
```

```text theme={null}
@alex we are targeting $50,000 monthly savings by Q2 — show progress toward that goal
```

## Related

<CardGroup cols={2}>
  <Card title="Cost Analytics" icon="chart-line" href="/guide/cost-optimization/analytics">
    Explore spending patterns and anomalies before and after optimization
  </Card>

  <Card title="Recommendations" icon="lightbulb" href="/guide/cost-optimization/recommendations">
    Review and implement AI-generated cost-saving recommendations
  </Card>

  <Card title="Artifacts" icon="chart-mixed" href="/guide/artifacts/overview">
    Generate executive savings reports and schedule recurring delivery
  </Card>

  <Card title="CloudKeepers" icon="radar" href="/guide/infrastructure/cloudkeepers">
    Surface waste as continuous findings that feed the savings pipeline
  </Card>
</CardGroup>