Abstract: A system comprises an interface configured to receive an identifier, a processor configured to determine a grouping associated with the identifier, wherein the grouping is determined using a first clustering, wherein the first clustering is based at least in part on a language processing system, determine a sub-grouping of the grouping associated with the identifier, wherein the sub-grouping is determined using a second clustering, determine a final identifier based at least in part on the identifier and the sub-grouping, determine a resource based at least in part on the final identifier, and store the final identifier associated with the resource, and a memory coupled to the processor and configured to provide the processor with instructions.

Abstract: A system comprises an interface configured to receive an identifier, a processor configured to determine a grouping associated with the identifier, wherein the grouping is determined using a first clustering, wherein the first clustering is based at least in part on a language processing system, determine a sub-grouping of the grouping associated with the identifier, wherein the sub-grouping is determined using a second clustering, determine a final identifier based at least in part on the identifier and the sub-grouping, determine a resource based at least in part on the final identifier, and store the final identifier associated with the resource, and a memory coupled to the processor and configured to provide the processor with instructions.

Abstract: A system for provisioning resources includes a processor and a memory. The processor is configured to receive a time series of past usage data. The past usage data comprises process usage data and instance usage data. The processor is further configured to determine an upcoming usage data based at least in part on the time series of the past usage data, and provision a computing system according to the upcoming usage data.

Abstract: A system comprises an interface configured to receive an identifier, a processor configured to determine a grouping associated with the identifier, wherein the grouping is determined using a first clustering, wherein the first clustering is based at least in part on a language processing system, determine a sub-grouping of the grouping associated with the identifier, wherein the sub-grouping is determined using a second clustering, determine a final identifier based at least in part on the identifier and the sub-grouping, determine a resource based at least in part on the final identifier, and store the final identifier associated with the resource, and a memory coupled to the processor and configured to provide the processor with instructions.

Abstract: A system for false positive detection includes an interface and a processor. The interface is configured to receive a transaction data. The processor is configured to determine whether the transaction data is a statistical outlier; in response to the transaction data being the statistical outlier: query database data to determine whether the transaction data is a false positive; and in response to the transaction data being the false positive, indicate that the transaction data is normal.

Abstract: A system for automatically scaling provisioned resources includes an input interface and a processor. The input interface is configured to receive an estimate of a required number of processing threads. The processor is configured to determine required resources for processing the required number of processing threads using a model; provision the required resources; indicate to execute client tasks using the provisioned resources; determine server telemetry or logging data for the provisioned resources; provide the server telemetry or the logging data to the model; determine a resource utilization score based at least in part on the server telemetry or the logging data; determine a provisioning performance reward based at least in part on the resource utilization score; and adjust model parameters using the provisioning performance reward.

Abstract: A system for provisioning resources includes a processor and a memory. The processor is configured to receive a time series of past usage data. The past usage data comprises process usage data and instance usage data. The processor is further configured to determine an upcoming usage data based at least in part on the time series of the past usage data, and provision a computing system according to the upcoming usage data.

Abstract: A system for provisioning resources includes an input interface and a processor. The input interface is configured to receive a time series of past usage data. The past usage data comprises process usage data and instance usage data. The processor is configured to determine an upcoming usage data based at least in part on the time series of the past usage data, and provision a computing system according to the upcoming usage data.

Abstract: A system for automatically scaling provisioned resources includes an input interface and a processor. The input interface is configured to receive an estimate of a required number of processing threads. The processor is configured to determine required resources for processing the required number of processing threads using a model; provision the required resources; indicate to execute client tasks using the provisioned resources; determine server telemetry or logging data for the provisioned resources; provide the server telemetry or the logging data to the model; determine a resource utilization score based at least in part on the server telemetry or the logging data; determine a provisioning performance reward based at least in part on the resource utilization score; and adjust model parameters using the provisioning performance reward.

Abstract: A system for provisioning resources includes an input interface and a processor. The input interface is configured to receive a time series of past usage data. The past usage data comprises process usage data and instance usage data. The processor is configured to determine an upcoming usage data based at least in part on the time series of the past usage data, and provision a computing system according to the upcoming usage data.