Abstract: Various techniques are described herein for generating and managing computing infrastructure instances within datacenters. Data identifying various computing infrastructure characteristics may be receive and analyzed in order to determine one or more computing infrastructure definitions to be instantiated within a datacenter. Specific datacenters may be determined for instantiating the computing infrastructure definitions, various provisioning and configuration management tools may be selected, and computing infrastructure instances comprising multiple interoperable services (e.g., web services) and other components may be provisioned, configured, tested, and maintained. In some examples, instance execution data may be received and analyzed via instance monitor components transmitted and deployed within computer infrastructure instances executing on datacenters.

Abstract: Various techniques are described herein for generating and managing computing infrastructure instances within datacenters. Data identifying various computing infrastructure characteristics may be receive and analyzed in order to determine one or more computing infrastructure definitions to be instantiated within a datacenter. Specific datacenters may be determined for instantiating the computing infrastructure definitions, various provisioning and configuration management tools may be selected, and computing infrastructure instances comprising multiple interoperable services (e.g., web services) and other components may be provisioned, configured, tested, and maintained. In some examples, instance execution data may be received and analyzed via instance monitor components transmitted and deployed within computer infrastructure instances executing on datacenters.

Abstract: A computer system automatically evaluates the performance of a content generator using content created by the content generator and user and content generator interactions with the content. Specifically, the system analyzes data regarding the content, e.g., a peer-review quality score, and analyzes data regarding user and/or content generator interactions with the content, e.g., website comments regarding the content. In addition, the system considers user and content generator interactions with the content on third-party websites, e.g., the number of Facebook® “likes” or other social media actions. The system applies rules to assign values to various data points (e.g., a value of 0.3 may be assigned for each Facebook® “like” by a user). The rules may also define weighing components to incentivize particular actions. Weighed values are summed to evaluate each content generator. The scores for each content generator may be compared to create a content generator ranking.