Abstract: The technology provides for rule based data driven validation in which a rule engine identifies which rules are applicable to target data items of a target data object by their data types including any inherited data types. Additionally, a condition for a rule or a rule exemption is implemented also as a rule which is processed by the rule engine like any other rule. In one embodiment, a validation system includes an abstract rule store of rule instance data items which link to corresponding concrete rules which may be in different data formats. A corresponding rule provides access to rule logic which implements the corresponding rule. A rule engine and the abstract rule store may be accessed over a network by an application requesting validation of a target data object. Furthermore, in some examples, the data driven rule store can be implemented using the Microsoft .NET™ framework.

Abstract: Systems and methods are disclosed which facilitate the evaluation of machine images. A machine image inspection component processes requests for evaluation of machine images hosted on a virtual machine instance. In response to the request, the machine image inspection component selects executable code that can evaluate the requested machine image prior to instantiating the virtual machine instance with the requested machine image. Based on execution of the selected executable code, the machine image inspection can then process the results of the evaluation of the requested machine image accordingly.

Abstract: A self-adapting classification system (“SACS”) generates an evolving classification for content. The classification may start with a seed review process, which generates a level of trust for initial reviews of the content. Once the seed review is completed and distributed, users may submit content reviews to the self adapting classification system. Using the SACS, users may identify themselves with one or more community groups, which indicate certain shared values and preferences with respect to other members of the same community group. Content reviews received by the SACS may comprise a user identifier pertaining to the submitting user, a content descriptor and an associated classification.

Abstract: The technology provides for rule based data driven validation in which a rule engine identifies which rules are applicable to target data items of a target data object by their data types including any inherited data types. Additionally, a condition for a rule or a rule exemption is implemented also as a rule which is processed by the rule engine like any other rule. In one embodiment, a validation system includes an abstract rule store of rule instance data items which link to corresponding concrete rules which may be in different data formats. A corresponding rule provides access to rule logic which implements the corresponding rule. A rule engine and the abstract rule store may be accessed over a network by an application requesting validation of a target data object. Furthermore, in some examples, the data driven rule store can be implemented using the Microsoft .NET™ framework.

Abstract: A self-adapting classification system (“SACS”) generates an evolving classification for content. The classification may start with a seed review process, which generates a level of trust for initial reviews of the content. Once the seed review is completed and distributed, users may submit content reviews to the self adapting classification system. Using the SACS, users may identify themselves with one or more community groups, which indicate certain shared values and preferences with respect to other members of the same community group. Content reviews received by the SACS may comprise a user identifier pertaining to the submitting user, a content descriptor and an associated classification.