The occasion of the 3.3.2 release of the rating-charging-billing solution for cloud software and platform providers, Cyclops, is a good opportunity for a deep dive into the new forecasting engine, the how and the why of its functionality and how to use it.
First, a bit of news. Active maintenance and further updates to Cyclops will now be found under the repository https://github.com/serviceprototypinglab/cyclops. The primary new addition is the forecasting engine. It helps SaaS/PaaS/CaaS/…XaaS providers to not only charge customers for their services, but also predict a revenue flow for deciding about future investments.
The latest update to the open source Cyclops Framework, part of our ongoing work to advance metering and monetization across cloud platforms, brings yet more new features and improvements:
Small fixes to the versioning/rollback features
New estimation and forecasting engine
The new forecasting engine is now built into Cyclops’ UDR service and can generate individual or global usage forecasts and cost/revenue estimates based on the existing usage data and be used to evaluate new pricing models.
A full-featured CLI client for the forecasting engine was also created to make using the new functionality more intuitive.
Through several years of research on the subject of cloud functions, researchers including ourselves have gained a thorough understanding of the advantages and disadvantages of function-based application development. Along with increased maturity of FaaS, a more specialised consideration of potential use cases is needed to filter out the ones where the technology shines compared to the ones where significant weaknesses become apparent and other technologies, perhaps even in combination, would be a better fit. This early experience report informs about how we have deployed cloud functions around an existing cloud management platform as a variant of the well-known solar system approach of introducing microservices around monoliths.