The International Workshop on Serverless Computing (WoSC) has become an established forum to discuss new serverless technologies, ranging from application development to runtime concerns. Despite FaaS having raised the bar for not being billed for many hours of idle server processes, we are constantly thinking from an application engineering perspective into how the pay-per-use models could become even more fine-grained and fair. Thus, we are happy to announce that an appropriate autotuning approach has been accepted for being presented at WoSC6 in December 2020.
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.
With the increased adoption of serverless computing, so is the need to optimise cloud functions, to make use of resources as efficiently as possible, and to lower the overall costs in the end. At the Service Prototyping Lab at Zurich University of Applied Sciences, we investigate how cloud application and platform providers can achieve a fairer billing model which comes closer to actual utility computing where you pay only for what you really use. We demonstrate our recent findings with AWS Lambda function pricing.
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.
We are announcing the latest release of the open source Cyclops framework, as part of our ongoing work to advance metering and monetization across cloud platforms, bringing improvements and new capabilities:
meaningful logs, now able to identify errors more effectively and
provide more information on generated records
checkpointing, with the ability to roll coin rules back using git
versioning and re-create affected records