Sammendrag
Various services are now available in the Cloud,
ranging from turnkey databases and application servers to highlevel
services such as continuous integration or source version
control. To stand out of this diversity, robustness of service
compositions is an important selling argument, but which remains
difficult to understand and estimate as it does not only depend on
services but also on the underlying platform and infrastructure.
Yet, choosing a specific service composition may fail to deliver the
expected robustness, but reverting early choices may jeopardise
the success of any Cloud project.
Inspired by existing models used in Biology to quantify the
robustness of ecosystems, we show how to tailor them to obtain
early indicators of robustness for cloud-based deployments.
This technique helps identify weakest services in the overall
architecture and in turn mitigates the risk of having to revert key
architectural choices. We illustrate our approach by comparing
the robustness of four alternative deployments of the SensApp
application, which includes a MongoDB database, four REST
services and a graphical web-front end
ranging from turnkey databases and application servers to highlevel
services such as continuous integration or source version
control. To stand out of this diversity, robustness of service
compositions is an important selling argument, but which remains
difficult to understand and estimate as it does not only depend on
services but also on the underlying platform and infrastructure.
Yet, choosing a specific service composition may fail to deliver the
expected robustness, but reverting early choices may jeopardise
the success of any Cloud project.
Inspired by existing models used in Biology to quantify the
robustness of ecosystems, we show how to tailor them to obtain
early indicators of robustness for cloud-based deployments.
This technique helps identify weakest services in the overall
architecture and in turn mitigates the risk of having to revert key
architectural choices. We illustrate our approach by comparing
the robustness of four alternative deployments of the SensApp
application, which includes a MongoDB database, four REST
services and a graphical web-front end