Abstract: Systems and methods are shown for providing metric driven deployments to cloud server services that are adapted to interface with each provider. In some implementations, there is insight and control over network, disk, CPU, and other activity giving the ability to do performance metrics analysis for a given application or service between different cloud server services as each application or service is run in a container within an instance running on the respective cloud server service. This allows for comparison between a plurality of providers for a given container driven by one or more metrics such as cost, flexibility, and performance. The instances which runs the one or more containers can be scaled up and down to a desired workload performance. Replication of images between providers can allow for seamless changing between providers based on changing goals as well as distribution of workload.

Abstract: Systems and methods are shown for providing metric driven deployments to cloud server services that are adapted to interface with each provider. In some implementations, there is insight and control over network, disk, CPU, and other activity giving the ability to do performance metrics analysis for a given application or service between different cloud server services as each application or service is run in a container within an instance running on the respective cloud server service. This allows for comparison between a plurality of providers for a given container driven by one or more metrics such as cost, flexibility, and performance. The instances which runs the one or more containers can be scaled up and down to a desired workload performance. Replication of images between providers can allow for seamless changing between providers based on changing goals as well as distribution of workload.