Abstract: Systems and methods are provided for implementing cloud distributed database capacity planning and/or adjustment, using time-series data analysis. In various embodiments, a computing system may be used to analyze collected throughput data associated with consumption of provisioned throughput resources of a distributed cloud database over one or more past periods by an entity. Based on the analysis, a set of predicted throughput data may be determined or generated for the entity over a future upcoming period. In some cases, based on a determination that adding physical partitions would be required, the computing system may adjust the set of predicted throughput data to reduce or minimize a number of physical partitions to be added. The provisioned capacity of the distributed cloud database may then be dynamically adjusted based at least in part on one of the unadjusted or adjusted set of predicted throughput data.

Abstract: Systems and methods are provided for implementing cloud distributed database capacity planning and/or adjustment, using time-series data analysis. In various embodiments, a computing system may be used to analyze collected throughput data associated with consumption of provisioned throughput resources of a distributed cloud database over one or more past periods by an entity. Based on the analysis, a set of predicted throughput data may be determined or generated for the entity over a future upcoming period. In some cases, based on a determination that adding physical partitions would be required, the computing system may adjust the set of predicted throughput data to reduce or minimize a number of physical partitions to be added. The provisioned capacity of the distributed cloud database may then be dynamically adjusted based at least in part on one of the unadjusted or adjusted set of predicted throughput data.

Abstract: Systems and methods are provided for implementing cloud distributed database capacity planning and/or adjustment, using time-series data analysis. In various embodiments, a computing system may be used to analyze collected throughput data associated with consumption of provisioned throughput resources of a distributed cloud database over one or more past periods by an entity. Based on the analysis, a set of predicted throughput data may be determined or generated for the entity over a future upcoming period. In some cases, based on a determination that adding physical partitions would be required, the computing system may adjust the set of predicted throughput data to reduce or minimize a number of physical partitions to be added. The provisioned capacity of the distributed cloud database may then be dynamically adjusted based at least in part on one of the unadjusted or adjusted set of predicted throughput data.

Abstract: The present technology provides a method to regenerate secrets while a version of the system is operational, thus avoiding the loss of availability that would have resulted from a system shutdown. The technology described herein may work in a computing context that assigns a first secret in an active role and a second secret in the backup role. The technology described herein activates a second instance of the service with the key not being regenerated serving as the active key. The second instance is then moved to the production mode and the first version of the service is moved to the staging mode. A new secret is generated and then assigned to the first instance of the service while it runs in the staging mode. Once the secret rotation is complete, the primary service instance is then moved back to the production mode with the new key configuration.

Abstract: The present technology provides a method to regenerate secrets while a version of the system is operational, thus avoiding the loss of availability that would have resulted from a system shutdown. The technology described herein may work in a computing context that assigns a first secret in an active role and a second secret in the backup role. The technology described herein activates a second instance of the service with the key not being regenerated serving as the active key. The second instance is then moved to the production mode and the first version of the service is moved to the staging mode. A new secret is generated and then assigned to the first instance of the service while it runs in the staging mode. Once the secret rotation is complete, the primary service instance is then moved back to the production mode with the new key configuration.