Abstract: Various aspects described herein are directed to different techniques for automatically and dynamically analyzing a first subscriber system's telemetry information and crowdsourced telemetry information to dynamically evaluate at least one performance metric associated with at least one entity of the first subscriber system; and for automatically and dynamically initiating at least one modification of at least one configuration element at the first subscriber system based on the analysis of the first subscriber system telemetry information and crowdsourced telemetry information.

Abstract: Various aspects described herein are directed to different techniques for automatically and dynamically analyzing a first subscriber system's telemetry information and crowdsourced telemetry information to dynamically evaluate at least one performance metric associated with at least one entity of the first subscriber system; and for automatically and dynamically initiating at least one modification of at least one configuration element at the first subscriber system based on the analysis of the first subscriber system telemetry information and crowdsourced telemetry information,

Abstract: Various aspects described herein are directed to different techniques for: evaluating server system reliability, vulnerability and component compatibility using crowdsourced server and vulnerability data; generating automated recommendations for improving server system metrics; and automatically and conditionally updating or upgrading system packages/components.

Abstract: Various aspects described herein are directed to different techniques for: evaluating server system reliability, vulnerability and component compatibility using crowdsourced server and vulnerability data; generating automated recommendations for improving server system metrics; and automatically and conditionally updating or upgrading system packages/components.

Abstract: Various aspects described herein are directed to different techniques for: evaluating server system reliability, vulnerability and component compatibility using crowdsourced server and vulnerability data; generating automated recommendations for improving server system metrics; and automatically and conditionally updating or upgrading system packages/components.

Abstract: Teachings of this application include a computing network that may include multiple different data centers and/or server grids which are deployed in different geographic locations. In at least one embodiment, at least some of the server grids may be operable to provide on-demand, grid and/or utility computing resources for hosting various types of distributed applications. In at least one embodiment, a distributed application may be characterized as an application made up of distinct components (e.g., virtual appliances, virtual machines, virtual interfaces, virtual volumes, virtual network connections, etc.) in separate runtime environments. In at least one embodiment, different ones of the distinct components of the distributed application may be hosted or deployed on different platforms (e.g., different servers) connected via a network. In some embodiments, a distributed application may be characterized as an application that runs on two or more networked computers.

Abstract: Various aspects described herein are directed to different techniques for: evaluating server system reliability, vulnerability and component compatibility using crowdsourced server and vulnerability data; generating automated recommendations for improving server system metrics; and automatically and conditionally updating or upgrading system packages/components.

Abstract: Teachings of this application include a computing network that may include multiple different data centers and/or server grids which are deployed in different geographic locations. In at least one embodiment, at least some of the server grids may be operable to provide on-demand, grid and/or utility computing resources for hosting various types of distributed applications. In at least one embodiment, a distributed application may be characterized as an application made up of distinct components (e.g., virtual appliances, virtual machines, virtual interfaces, virtual volumes, virtual network connections, etc.) in separate runtime environments. In at least one embodiment, different ones of the distinct components of the distributed application may be hosted or deployed on different platforms (e.g., different servers) connected via a network. In some embodiments, a distributed application may be characterized as an application that runs on two or more networked computers.

Abstract: In at least one embodiment, the computing network may include multiple different data centers and/or server grids which are deployed different geographic locations. In at least one embodiment, at least some of the 20 server grids may be operable to provide on-demand, grid and/or utility computing resources for hosting various types of distributed applications. In at least one embodiment, a distributed application may be characterized as an application made up of distinct components (e.g., virtual appliances, virtual machines, virtual interfaces, virtual volumes, virtual network connections, etc.) in separate runtime environments. In at least one embodiment, different 25 ones of the distinct components of the distributed application may be hosted or deployed on different platforms (e.g., different servers) connected via a network. In some embodiments, a distributed application may be characterized as an application that runs on two or more networked computers.

Abstract: Various techniques are disclosed for use in computing networks such as, for example, on-demand, grid and/or utility computing networks.