Optimizing adaptive monitoring in resource constrained environments
View Patent ↗Adaptive monitoring dynamically optimizes the monitoring frequency of metrics with respect to system constraints. One or more metrics are monitored. The monitoring includes receiving a value for the metric and evaluating the received metric value. If the evaluation is determined to affect one or monitoring parameters, or if an environment-based event occurs the metrics are adapted. Adapting metrics includes removing or adding a metric based on each metric's correlation to the affected monitoring parameter or environment based trigger. The frequencies of the metrics are optimized based on the available resources.
1. A computer system comprising:
a memory;
a processor, communicatively coupled to the memory;
a functional unit in communication with the processing unit having an adaptive monitor, the adaptive monitor to:
actively monitor, in real-time, at least one metric, including a first metric at a first frequency returning a first metric value;
evaluate the first metric value;
determine that an environment-based event has occurred;
identify an adaptation of the monitoring based on a condition selected from the group consisting of: the evaluated first metric value, the environment-based event, and a combination thereof;
dynamically adapt the monitoring responsive to the condition, the dynamic adaptation comprising the adaptive monitor to:
adjust a selection of metrics, including assess selection of active metrics to retain, assess selection of active metrics to remove, and assess selection of metrics to add, the selections responsive to the evaluated first metric value and the environment-based event;
in response to adjusting the selection of metrics, compute an updated frequency for each retained metric in the adjusted selection of metrics and a new frequency for each added metric in the adjusted selection of metrics based on resource availability; and
selectively assign the respective new and updated frequencies to the corresponding added and retained metrics.
2. The system of claim 1 , further comprising the adaptive monitor to compute a weight for each retained and added metric and selectively assign the computed weight to the added and retained metrics, wherein the computation of the frequency is based on the selectively assigned weight.
3. The system of claim 2 , wherein the weight assignment individually influences a strength of a single metric within a grouping of active metrics.
4. The system of claim 2 , further comprising the adaptive monitor to selectively maximize a monitoring frequency for each added and retained metric, the frequency based on the computed weight and resource availability.
5. The system of claim 2 , wherein the computed weight for each retained and added metric corresponds to a correlation coefficient between at least two metrics selected from the group consisting of: at least one retained metric and at least one added metric.
6. The system of claim 1 , wherein computation of the frequency includes the adaptive monitor to compute an optimal frequency interval and an optimal frequency interval start time.
7. The system of claim 1 , wherein the adaptive monitor is provided as a service in a cloud environment to perform the dynamic adaptation.
8. A computer product for optimal adaptive monitoring, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to:
actively monitor, in real-time, at least one metric, including a first metric at a first frequency returning a first metric value
evaluate the first metric value;
determine that an environment-based event has occurred;
identify an adaptation of the monitoring based on a condition selected from the group consisting of: the evaluated first metric value, the environment-based event, and a combination thereof;
dynamically adapt the monitoring responsive to the condition, the dynamic adaptation comprising the adaptive monitor to:
adjust a selection of metrics, including assess selection of active metrics to retain, assess selection of active metrics to remove, and assess selection of metrics to add, the selections responsive to the evaluated first metric value and the environment-based event;
in response to adjusting the selection of metrics, compute an updated frequency for each retained metric in the adjusted selection of metrics and a new frequency for each added metric in the adjusted selection of metrics based on resource availability; and
selectively assign the respective new and updated frequencies to the corresponding added and retained metrics.
9. The computer program product of claim 8 , further comprising program code to compute a weight for each retained and added metric and selectively assign the computed weight to the added and retained metrics wherein computation of the frequency is based on the selectively assigned weight.
10. The computer program product of claim 9 , wherein the weight assignment individually influences a strength of a single metric within a grouping of active metrics.
11. The computer program product of claim 9 , further comprising program code to selectively maximize a monitoring frequency for each added and retained metric, the frequency based on the computed weight and resource availability.
12. The computer program product of claim 9 , wherein the computed weight for each retained and added metric corresponds to a correlation coefficient between at least two metrics selected from the group consisting of: at least one retained metric and at least one added metric.
13. The computer program product of claim 8 , wherein computation of the frequency includes program code to compute an optimal frequency interval and an optimal frequency interval start time.
14. A method for optimal adaptive monitoring, the method comprising:
actively monitoring, in real-time, at least one metric, including a first metric at a first frequency returning a first metric value;
evaluating the first metric value;
determining that an environment-based event has occurred;
identifying an adaptation of the monitoring based on a condition selected from the group consisting of: the evaluated first metric value, the environment-based event, and a combination thereof;
dynamically adapting the monitoring responsive to the condition, the dynamic adaptation comprising:
adjusting a selection of metrics, including assessing selection of active metrics to retain, assessing selection of active metrics to remove, and assessing selection of metrics to add, the selections responsive to the evaluated first metric value and the environment-based event;
in response to adjusting the selection of metrics, computing an updated frequency for each retained metric in the adjusted selection of metrics and a new frequency for each added metric in the adjusted selection of metrics based on resource availability; and
selectively assigning the respective new and updated frequencies to the corresponding added and retained metrics.
15. The method of claim 14 , further comprising computing a weight for each retained and added metric and selectively assigning the computed weight to the added and retained metrics wherein computing the frequency is based on the selectively assigned weight.
16. The method of claim 15 , wherein the weight assignment individually influences a strength of a single metric within a grouping of active metrics.
17. The method of claim 15 , further comprising selectively maximizing a monitoring frequency for each added and retained metric, the frequency based on the computed weight and resource availability.
18. The method of claim 15 , wherein the computed weight for each retained and added metric corresponds to a correlation coefficient between at least two metrics selected from the group consisting of: at least one retained metric and at least one added metric.
19. The method of claim 14 , wherein computing the frequency includes computing an optimal frequency interval and an optimal frequency interval start time.
20. The method of claim 14 , wherein software is provided as a service in a cloud environment to perform the dynamic adaptation.