At the beginning of any planning and modeling, the forecast of consumption is based on assumptions, and as a result, it probably won’t be a good match for the actual bill. With Federator.ai, the machine learning-based algorithm builds a more accurate consumption forecast model suited for continuous planning and budgeting activities on an ongoing basis.
Automatic forecasting in CI/CD process is also proposed in the Guidance Framework. As many organizations adopt a “shift left” strategy that places the onus for quality, reliability, and uptime with application delivery teams, such teams have increased expectations to forecast costs, optimize resources, and implement continuous optimization. This requires integrating the forecasting into an automated CI/CD process. Federator.ai machine learning-based application resource forecasting can be easily integrated into automated CI/CD processes. Through Federator.ai open APIs, it is easy to obtain the forecast and recommendations for application resources integrated into any CI/CD process. Furthermore, CI/CD integration sample scripts for any application are available directly from the Federator.ai GUI, making integration even more straightforward.