Abstract: Systems and methods described herein relate to automatic index recommendations for improved database query performance. Candidate indexes are identified. The candidate indexes are associated with a database query that is classified as a slow query. A feature vector is generated for each candidate index to represent statement features and statistical features associated with the candidate index. The feature vectors are provided to one or more machine learning models to obtain an index recommendation value for each candidate index. An index recommendation is presented at a user device. The index recommendation identifies a first index of the candidate indexes based at least partially on the index recommendation value obtained for the first index. User input indicative of a user selection of the first index is received. A database schema is updated to include the first index in response to the user input.

Abstract: Methods, systems, and computer-readable storage media for providing a VM vector representative of resources that are to be consumed by the VM within the cloud computing environment, comparing the VM vector to each physical node vector in a set of physical node vectors to determine a distance, each physical node vector representative of resources available by a respective physical node, and selecting a physical node from a set of physical nodes based on a respective distance between the VM vector and a physical node vector representative of the physical node, and in response, automatically: deploying the VM to the physical node within the cloud computing environment at least partially by installing the VM on the physical node for execution thereon.

Abstract: Methods, systems, and computer-readable storage media for determining a set of estimated task execution times based on a set of task execution times, each estimated task execution time being calculated for a computing resource size that is different than a computing resource size of a corresponding task execution time in the set of task execution times, assigning a tag to each task in the set of tasks, each tag indicating a computing resource size that the respective tasks is to be executed by, providing the set of tasks and assigned tags for execution of the set of tasks in an iteration within the cloud system, and receiving actual task execution times from computing resources, each actual task execution time indicating an actual time required by a respective computing resource to execute a respective task.