Abstract: A validating service of a plurality of services that compose an application receives a security token that identifies an entity that has submitted a transaction to the application, the security token indicating that the entity is authorized to submit the transaction to the application. The validating service obtains a transaction identifier that uniquely identifies the transaction. The validating service sends, to a collector service, the transaction identifier and data derived from the security token that identifies the entity. A downstream service receives input data associated with the transaction, the input data including the transaction identifier. The downstream service accesses an information source to obtain information. The downstream service sends, to the collector service, the transaction identifier and metadata about the information.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: Systems, methods, and computer-readable media for identifying and categorizing epoch events between a first epoch and a second epoch. Epoch event data for a first epoch and a second epoch is retrieved. The retrieved epoch event data is categorized to determine event category, specific event, and respective object identification. The categorized first and second epoch event data is then labeled to identify new, resolved, and persistent epoch events over multiple epochs.

Abstract: Systems, methods, and computer-readable media for identifying and categorizing changes in epoch policies between a first epoch and a second epoch. Epoch network policy data for a first epoch and a second epoch is retrieved. The retrieved epoch network policy data is used to generate hierarchically structured documents to perform epoch network policy comparisons. Epoch diffs products from the epoch network policy comparisons are provided to a user through a searchable aggregated interface.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: The technology disclosed relates to detecting anomalous behavior of network components in a complex network setting.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: The technology disclosed relates to building ensemble analytic rules for reusable operators and tuning an operations monitoring system. In particular, it relates to analyzing a metric stream by applying an ensemble analytical rule. After analysis of the metric stream by applying the ensemble analytical rule, quantized results are fed back for expert analysis. Then, one or more type I or type II errors are identified in the quantized results, and one or more of the parameters of the operators are automatically adjusted to correct the identified errors. The metric stream is further analyzed by applying the ensemble analytical rule with the automatically adjusted parameters.

Abstract: The technology disclosed relates to detecting anomalous behavior of network components in a complex network setting.