Abstract: Configuration datasets from multiple, distinct computing systems can be managed. For example, a computing device can receive multiple configuration datasets describing multiple system configurations for at least two distinct computing systems. The computing device can determine key-value pairs based on the configuration datasets. The computing device store relationships between the key-value pairs in a database. The computing device can then receive a configuration dataset from a computing system of a user that can describe a system configuration for the computing system. The computing device can determine a set of key-value pairs based on the configuration dataset. The computing device can analyze the set of key-value pairs based on the relationships stored in the database to determine configuration feedback for the system configuration. The configuration manager can transmit the configuration feedback to the computing system to allow the user to implement the configuration feedback.

Abstract: Predicting execution duration for user-defined functions on function-as-a-service (FaaS) cloud computing platforms is disclosed herein. In one example, a processor device of an FaaS cloud computing platform detects an event that triggers execution of a user-defined function, and automatically fetches an environmental metric that represents a current attribute or condition of the operating environment in which the user-defined function will execute. The processor device then calculates a predicted execution duration for the user-defined function based on the environmental metric, and compares the predicted execution duration to an execution duration threshold. If the predicted execution duration exceeds the execution duration threshold, the processor device prevents execution of the user-defined function by the FaaS cloud computing platform. If the predicted execution duration does not exceed the execution duration threshold, the processor device may initiate execution of the user-defined function.

Abstract: A query for available plugin extensions is received from a client device. A request for operator images including plugin extensions is transmitted to a repository including multiple operator images, wherein each of the operator images includes corresponding metadata identifying the plugin extensions. Identifications of the operator images including the plugin extensions and the corresponding metadata identifying the plugin extensions are received from the repository. A listing of the plugin extensions is transmitted to the client device.

Abstract: Configuration datasets from multiple, distinct computing systems can be managed. For example, a computing device can receive multiple configuration datasets describing multiple system configurations for at least two distinct computing systems. The computing device can determine key-value pairs based on the configuration datasets. The computing device store relationships between the key-value pairs in a database. The computing device can then receive a configuration dataset from a computing system of a user that can describe a system configuration for the computing system. The computing device can determine a set of key-value pairs based on the configuration dataset. The computing device can analyze the set of key-value pairs based on the relationships stored in the database to determine configuration feedback for the system configuration. The configuration manager can transmit the configuration feedback to the computing system to allow the user to implement the configuration feedback.

Abstract: Predicting execution duration for user-defined functions on function-as-a-service (FaaS) cloud computing platforms is disclosed herein. In one example, a processor device of an FaaS cloud computing platform detects an event that triggers execution of a user-defined function, and automatically fetches an environmental metric that represents a current attribute or condition of the operating environment in which the user-defined function will execute. The processor device then calculates a predicted execution duration for the user-defined function based on the environmental metric, and compares the predicted execution duration to an execution duration threshold. If the predicted execution duration exceeds the execution duration threshold, the processor device prevents execution of the user-defined function by the FaaS cloud computing platform. If the predicted execution duration does not exceed the execution duration threshold, the processor device may initiate execution of the user-defined function.