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 from one or more source visualization models, wherein each source visualization corresponds to a specification and a source visualization model;
evaluating each specification to determine one or more characteristics 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 the one or more metrics for each classified source visualization based on the one or more classifiers;
generating one or more metric profiles that correspond to the one or more metrics based on the one or more classifiers;
sampling the 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 the one or more metric profiles;
storing the one or more sampled values 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; and
generating one or more metric visualizations based on the one or more values and the one or more time values, wherein the one or more metric visualizations display one or more previously sampled values of the one or more metrics.
2. The method of claim 1 , wherein evaluating each specification, further includes:
iterating through the one or more classifiers to determine a class of visualizations that corresponds to the one or more source visualizations;
executing one or more actions to determine the one or more characteristics of each source visualization based on its corresponding class; and
excluding each of the one or more source visualizations that remains unclassified.
3. The method of claim 1 , wherein displaying the one or more metric visualizations, further comprises, displaying the one or more metric visualizations in the dashboard or in another user interface.
4. The method of claim 1 , wherein determining the one or more metrics, further comprises, determining one or more of one or more single values metrics or one or more multiple valued metrics, wherein each of the one or more multiple valued metrics are single metrics that are divided into two or more categories.
5. The method of claim 1 , further comprising:
providing one or more anomaly detectors that are arranged to identify one or more statistical anomalies that are present in the one or more values of the one or more metrics; and
in response to determining one or more statistical anomalies based on the one or more anomaly detectors, performing further actions, including:
providing one or more alerts that include one or more of one or more notifications, one or more alerts, or one or more reports; and
communicating the one or more alerts to one or more of one or more responsible parties or one or more services.
6. The method of claim 1 , wherein sampling the one or more source visualization models to provide the one or more values of the one or more metrics, further comprises, sampling the one or more source visualization models while the dashboard or the one or more source visualizations are inactive, wherein the inactive dashboard or the one or more inactive source visualizations are omitted from being displayed.
7. 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 that perform 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 from one or more source visualization models, wherein each source visualization corresponds to a specification and a source visualization model;
evaluating each specification to determine one or more characteristics 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 the one or more metrics for each classified source visualization based on the one or more classifiers;
generating one or more metric profiles that correspond to the one or more metrics based on the one or more classifiers;
sampling the 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 the one or more metric profiles;
storing the one or more sampled values 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; and
generating one or more metric visualizations based on the one or more values and the one or more time values, wherein the one or more metric visualizations display one or more previously sampled values of the one or more metrics.
8. The network computer of claim 7 , wherein evaluating each specification, further includes:
iterating through the one or more classifiers to determine a class of visualizations that corresponds to the one or more source visualizations;
executing one or more actions to determine the one or more characteristics of each source visualization based on its corresponding class; and
excluding each of the one or more source visualizations that remains unclassified.
9. The network computer of claim 7 , wherein displaying the one or more metric visualizations, further comprises, displaying the one or more metric visualizations in the dashboard or in another user interface.
10. The network computer of claim 7 , wherein determining the one or more metrics, further comprises, determining one or more of one or more single values metrics or one or more multiple valued metrics, wherein each of the one or more multiple valued metrics are single metrics that are divided into two or more categories.
11. The network computer of claim 7 , wherein the one or more processors execute instructions that perform actions, further comprising:
providing one or more anomaly detectors that are arranged to identify one or more statistical anomalies that are present in the one or more values of the one or more metrics; and
in response to determining one or more statistical anomalies based on the one or more anomaly detectors, performing further actions, including:
providing one or more alerts that include one or more of one or more notifications, one or more alerts, or one or more reports; and
communicating the one or more alerts to one or more of one or more responsible parties or one or more services.
12. The network computer of claim 7 , wherein sampling the one or more source visualization models to provide the one or more values of the one or more metrics, further comprises, sampling the one or more source visualization models while the dashboard or the one or more source visualizations are inactive, wherein the inactive dashboard or the one or more inactive source visualizations are omitted from being displayed.
13. A system for generating metrics based on visualizations over a network, comprising:
a network computer, comprising:
a memory that stores at least instructions; and
one or more processors that execute instructions that perform 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 from one or more source visualization models, wherein each source visualization corresponds to a specification and a source visualization model;
evaluating each specification to determine one or more characteristics 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 the one or more metrics for each classified source visualization based on the one or more classifiers;
generating one or more metric profiles that correspond to the one or more metrics based on the one or more classifiers;
sampling the 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 the one or more metric profiles;
storing the one or more sampled values 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; and
generating one or more metric visualizations based on the one or more values and the one or more time values, wherein the one or more metric visualizations display one or more previously sampled values of the one or more metrics; and
a client computer, comprising:
a memory that stores at least instructions; and
one or more processors that execute instructions that perform actions, including:
displaying the dashboard and the one or more source visualizations.
14. The system of claim 13 , wherein evaluating each specification, further includes:
iterating through the one or more classifiers to determine a class of visualizations that corresponds to the one or more source visualizations;
executing one or more actions to determine the one or more characteristics of each source visualization based on its corresponding class; and
excluding each of the one or more source visualizations that remains unclassified.
15. The system of claim 13 , wherein displaying the one or more metric visualizations, further comprises, displaying the one or more metric visualizations in the dashboard or in another user interface.
16. The system of claim 13 , wherein determining the one or more metrics, further comprises, determining one or more of one or more single values metrics or one or more multiple valued metrics, wherein each of the one or more multiple valued metrics are single metrics that are divided into two or more categories.
17. The system of claim 13 , wherein the one or more processors of the network computer execute instructions that perform actions, further comprising:
providing one or more anomaly detectors that are arranged to identify one or more statistical anomalies that are present in the one or more values of the one or more metrics; and
in response to determining one or more statistical anomalies based on the one or more anomaly detectors, performing further actions, including:
providing one or more alerts that include one or more of one or more notifications, one or more alerts, or one or more reports; and
communicating the one or more alerts to one or more of one or more responsible parties or one or more services.
18. The system of claim 13 , wherein sampling the one or more source visualization models to provide the one or more values of the one or more metrics, further comprises, sampling the one or more source visualization models while the dashboard or the one or more source visualizations are inactive, wherein the inactive dashboard or the one or more inactive source visualizations are omitted from being displayed.
19. 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 from one or more source visualization models, wherein each source visualization corresponds to a specification and a source visualization model;
evaluating each specification to determine one or more characteristics 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 the one or more metrics for each classified source visualization based on the one or more classifiers;
generating one or more metric profiles that correspond to the one or more metrics based on the one or more classifiers;
sampling the 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 the one or more metric profiles;
storing the one or more sampled values 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; and
generating one or more metric visualizations based on the one or more values and the one or more time values, wherein the one or more metric visualizations display one or more previously sampled values of the one or more metrics.
20. The computer readable non-transitory storage media of claim 19 , wherein evaluating each specification, further includes:
iterating through the one or more classifiers to determine a class of visualizations that corresponds to the one or more source visualizations;
executing one or more actions to determine the one or more characteristics of each source visualization based on its corresponding class; and
excluding each of the one or more source visualizations that remains unclassified.
21. The computer readable non-transitory storage media of claim 19 , wherein displaying the one or more metric visualizations, further comprises, displaying the one or more metric visualizations in the dashboard or in another user interface.
22. The computer readable non-transitory storage media of claim 19 , wherein determining the one or more metrics, further comprises, determining one or more of one or more single values metrics or one or more multiple valued metrics, wherein each of the one or more multiple valued metrics are single metrics that are divided into two or more categories.
23. The computer readable non-transitory storage media of claim 19 , wherein the one or more processors execute instructions that perform actions, further comprising:
providing one or more anomaly detectors that are arranged to identify one or more statistical anomalies that are present in the one or more values of the one or more metrics; and
in response to determining one or more statistical anomalies based on the one or more anomaly detectors, performing further actions, including:
providing one or more alerts that include one or more of one or more notifications, one or more alerts, or one or more reports; and
communicating the one or more alerts to one or more of one or more responsible parties or one or more services.
24. The computer readable non-transitory storage media of claim 19 , wherein sampling the one or more source visualization models to provide the one or more values of the one or more metrics, further comprises, sampling the one or more source visualization models while the dashboard or the one or more source visualizations are inactive, wherein the inactive dashboard or the one or more inactive source visualizations are omitted from being displayed.