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
Migrating an application from one cloud to another is a challenging activity and one must be mindful of both potential incompatibility and data loss when migrating. It is also, however, often necessary, so a proper way to automate the process and ensure a working deployment on the other end is certain to be a handy tool to an administrator. Since we have been working with multi and cross cloud environments and application portability (see paper and blog), we present a tool to automate this process for Openshift.
As far as use cases for migration go, the easiest example to visualize is moving an application from the development environment to production. Minishift, the single node local development version of Openshift is a great way to develop and test a new application, isolated from the risks and expenses of exposing it to the outside world. But at some point, this application will need to be recreated on a production Openshift instance and while doing this ‘traditionally’ is easy for small applications, it can become cumbersome for larger cases, especially if parts of it were configured using the graphical dashboard.