Forecast cloud and infrastructure budgets from historical costs using linear regression.
npx skills add https://github.com/mahg-es/araya --skill budget-forecasting
Please help me install this Agent Skill. Skill: budget-forecasting Source: https://github.com/mahg-es/araya/tree/main/skills/budget-forecasting Command: npx skills add https://github.com/mahg-es/araya --skill budget-forecasting
Cloud and infrastructure budgeting is error-prone; this skill builds predictive models to forecast spend and identify variances.
Provide 12+ months of historical cloud costs and run the forecast to generate a 12-month budget projection.
High-intent search queries and answers about installing and using this skill.
You can forecast cloud costs by providing 12 or more months of historical spend data to generate a 12-month budget projection. The model applies baseline linear regression on trailing 90-day costs to predict future monthly spend.
Cloud cost variance analysis compares predicted spend against actuals to identify discrepancies. This skill outputs alert thresholds at 50, 80, 95, and 100 percent of your budget to help you stay within planned limits.
Yes, you can manually incorporate planned changes into your cloud cost forecast. This allows you to adjust baseline predictions from trailing 90-day historical costs to account for new projects and scaling.
You need at least 12 months of historical cloud cost data to generate a 12-month budget projection. This data feeds the baseline linear regression model to predict future spend across services, environments, and projects.
Yes, the budget forecasting tool outputs a 12-month forecast that includes confidence bands. These bands account for variance in your historical cloud costs to provide a spend prediction range.
You should recalibrate cloud infrastructure cost forecasts quarterly to adjust for scaling and new projects. This updates the baseline linear regression model with recent trailing 90-day costs for accurate variance analysis.
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