Providing and surfacing metrics for visualizations
Embodiments are directed to generating metrics based on visualizations. A dashboard that may be associated with source visualizations display a current value of metrics from source visualization models. A classifier may automatically use characteristics from the source visualizations to determine metrics for the source visualization. The source visualization models may be sample to provide values of the metrics across time, at a sampling rate determined by a metric profile. The sampled values may be stored with time values in a metric data store such that the time values may correspond to when the values sampled from the visualization. Metric visualizations may be generated based on the values and the time values such that the metric visualizations display previously sampled values of the metrics.
1. A method for generating metrics based on visualizations using one or more processors that execute instructions to perform actions, comprising:
providing a dashboard that is associated with one or more source visualizations that each display a current value of one or more metrics;
evaluating data of the one or more source visualizations to determine one or more characteristics of the data of each source visualization, wherein the one or more source visualizations are classified based on one or more classifiers and the one or more characteristics;
determining one or more of anomaly metrics and trend metrics for one or more of the classified source visualizations based on the one or more classifiers; and
generating one or more metric visualizations that correspond to the one or more of the anomaly metrics or trend metrics based on the one or more classifiers, wherein the one or more of anomaly metrics and trend metric visualizations display one or more previous values of the one or more metrics.
2. The method of claim 1 , further comprising:
sampling one or more source visualization models to provide one or more values of the one or more metrics, wherein a sampling rate is based on one or more metric profiles.
3. The method of claim 1 , further comprising:
storing one or more sampled values of one or more visualization models with one or more time values in a metric data store, wherein the one or more time values correspond to when the one or more values were sampled.
4. The method of claim 1 , wherein the one or more source visualizations that each display the current value of the one or more metrics is based on one or more source visualization models that correspond to a specification.
5. The method of claim 1 , further comprising:
providing one or more anomaly detectors that are arranged to identify one or more anomalies that are present in the one or more values of the one or more metrics; and
providing one or more anomaly alerts that include one or more of one or more notifications, or one or more reports, wherein the one or more anomaly alerts are presented to one or more of a responsible party or a service.
6. The method of claim 1 , wherein the classified one or more source visualizations, further comprises:
determining a class of visualizations that corresponds to the one or more source visualizations; and
excluding each of the one or more source visualizations that remains unclassified.
7. The method of claim 1 , wherein generating the one or more metric visualizations further comprises:
generating one or more metric profiles that include one or more specifications to render the one or more metric visualizations.
8. A network computer for generating metrics based on visualizations, comprising:
a memory that stores at least instructions; and
one or more processors that execute instructions to enable performance of actions, including:
providing a dashboard that is associated with one or more source visualizations that each display a current value of one or more metrics;
evaluating data of the one or more source visualizations to determine one or more characteristics of the data of each source visualization, wherein the one or more source visualizations are classified based on one or more classifiers and the one or more characteristics;
determining one or more of anomaly metrics and trend metrics for one or more of the classified source visualizations based on the one or more classifiers; and
generating one or more metric visualizations that correspond to the one or more of the anomaly metrics or trend metrics based on the one or more classifiers, wherein the one or more of anomaly metrics and trend metric visualizations display one or more previous values of the one or more metrics.
9. The network computer of claim 8 , further comprising:
sampling one or more source visualization models to provide one or more values of the one or more metrics, wherein a sampling rate is based on one or more metric profiles.
10. The network computer of claim 8 , further comprising:
storing one or more sampled values of one or more visualization models with one or more time values in a metric data store, wherein the one or more time values correspond to when the one or more values were sampled.
11. The network computer of claim 8 , wherein the one or more source visualizations that each display the current value of the one or more metrics is based on one or more source visualization models that correspond to a specification.
12. The network computer of claim 8 , further comprising:
providing one or more anomaly detectors that are arranged to identify one or more anomalies that are present in the one or more values of the one or more metrics; and
providing one or more anomaly alerts that include one or more of one or more notifications, or one or more reports, wherein the one or more anomaly alerts are presented to one or more of a responsible party or a service.
13. The network computer of claim 8 , wherein the classified one or more source visualizations, further comprises:
determining a class of visualizations that corresponds to the one or more source visualizations; and
excluding each of the one or more source visualizations that remains unclassified.
14. The network computer of claim 8 , wherein generating the one or more metric visualizations further comprises:
generating one or more metric profiles that include one or more specifications to render the one or more metric visualizations.
15. A computer readable non-transitory storage media for storing instructions, wherein execution of the instructions by one or more processors enables performance of actions for generating metrics based on visualizations, comprising:
providing a dashboard that is associated with one or more source visualizations that each display a current value of one or more metrics;
evaluating data of the one or more source visualizations to determine one or more characteristics of the data of each source visualization, wherein the one or more source visualizations are classified based on one or more classifiers and the one or more characteristics;
determining one or more of anomaly metrics and trend metrics for one or more of the classified source visualizations based on the one or more classifiers; and
generating one or more metric visualizations that correspond to the one or more of the anomaly metrics or trend metrics based on the one or more classifiers, wherein the one or more of anomaly metrics and trend metric visualizations display one or more previous values of the one or more metrics.
16. The computer readable non-transitory storage media of claim 15 , further comprising:
sampling one or more source visualization models to provide one or more values of the one or more metrics, wherein a sampling rate is based on one or more metric profiles.
17. The computer readable non-transitory storage media of claim 15 , further comprising:
storing one or more sampled values of one or more visualization models with one or more time values in a metric data store, wherein the one or more time values correspond to when the one or more values were sampled.
18. The computer readable non-transitory storage media of claim 15 , wherein the one or more source visualizations that each display the current value of the one or more metrics is based on one or more source visualization models that correspond to a specification.
19. The computer readable non-transitory storage media of claim 15 , further comprising:
providing one or more anomaly detectors that are arranged to identify one or more anomalies that are present in the one or more values of the one or more metrics; and
providing one or more anomaly alerts that include one or more of one or more notifications, or one or more reports, wherein the one or more anomaly alerts are presented to one or more of a responsible party or a service.
20. The computer readable non-transitory storage media of claim 15 , wherein generating the one or more metric visualizations further comprises:
generating one or more metric profiles that include one or more specifications to render the one or more metric visualizations.