Virtual metrics
Various aspects of the subject technology relate to systems, methods, and machine-readable media for visualizing performance data of infrastructure components. The method includes receiving a query through an application for a metric for an infrastructure component, the metric comprising metric time series (MTS) data. The method also includes identifying sources for the metric. The method also includes querying the identified sources for the metric. The method also includes selecting from the identified sources best available data for the metric based on a selection algorithm. The method also includes enriching the best available data comprising linking dimensions and properties from the identified sources to the best available data. The method also includes causing display of the enriched best available data through a user interface of the application.
1. A computer-implemented method for visualizing performance data of infrastructure components, comprising:
receiving a query through an application for a metric for an infrastructure component, the metric comprising metric time series (MTS) data;
identifying sources for the metric;
querying the identified sources for the metric;
selecting, from the identified sources, best available data for the metric based on a selection algorithm, the selection algorithm including:
determining whether the identified sources have null values for the metric,
excluding sources from the identified sources determined to have the null values for the metric,
comparing remaining data sources from the identified sources based on policies that define an identity of a particular metric, and
when data from at least two of the remaining data sources are available, selecting the best available data;
enriching the best available data comprising linking dimensions and properties from the identified sources to the best available data; and
causing display of the enriched best available data through a user interface of the application.
2. The computer-implemented method of claim 1 , wherein the sources comprise at least one of a third party metrics collection tool or an infrastructure as a service (IAAS) platform's native monitoring and metrics collection service.
3. The computer-implemented method of claim 1 , further comprising:
scaling the data by a scaling factor based on a value of the data.
4. The computer-implemented method of claim 1 , further comprising:
normalizing the data based on dimensions in common between the sources.
5. The computer-implemented method of claim 1 , further comprising:
passing the query onto the sources as a filter.
6. The computer-implemented method of claim 1 , wherein the selection algorithm comprises:
determining a most recent metric for each source;
comparing the most recent metrics for each source; and
selecting the most recent metric based on the comparing.
7. The computer-implemented method of claim 1 , wherein the selection algorithm comprises:
determining a best available data source.
8. The computer-implemented method of claim 7 , wherein the best available data source comprises at least one of a data source that provides frequent values, has a highest granularity, has a highest cardinality, has a shortest lag, and/or is specified as a preferred source.
9. The computer-implemented method of claim 1 , further comprising:
renaming the metric.
10. The computer-implemented method of claim 1 , wherein each source comprises a preference order.
11. A computing device, comprising:
a processor; and
a non-transitory computer-readable medium having stored thereon instructions that, when executed by the processor, cause the processor to perform operations for visualizing performance data of infrastructure components, including:
receiving a query through an application for a metric for an infrastructure component, the metric comprising metric time series (MTS) data;
identifying sources for the metric;
querying the identified sources for the metric;
selecting, from the identified sources, best available data for the metric based on a selection algorithm, the selection algorithm including:
determining whether the identified sources have null values for the metric,
excluding sources from the identified sources determined to have the null values for the metric,
comparing remaining data sources from the identified sources based on policies that define an identity of a particular metric, and
when data from at least two of the remaining data sources are available, selecting the best available data;
enriching the best available data comprising linking dimensions and properties from the identified sources to the best available data; and
causing display of the enriched best available data through a user interface of the application.
12. The computing device of claim 11 , wherein the sources comprise at least one of a third party metrics collection tool or an infrastructure as a service (IAAS) platform's native monitoring and metrics collection service.
13. The computing device of claim 11 , wherein the operations further include:
scaling the data by a scaling factor based on a value of the data.
14. The computing device of claim 11 , wherein the operations further include:
normalizing the data based on dimensions in common between the sources.
15. The computing device of claim 11 , wherein the operations further include:
passing the query onto the sources as a filter.
16. The computing device of claim 11 , wherein the selection algorithm further comprises operations including:
determining a most recent metric for each source;
comparing the most recent metrics for each source; and
selecting the most recent metric based on the comparing.
17. The computing device of claim 11 , wherein the selection algorithm further comprises operations including:
determining a best available data source.
18. The computing device of claim 17 , wherein the best available data source comprises at least one of a data source that provides frequent values, has a highest granularity, has a highest cardinality, has a shortest lag, and/or is specified as a preferred source.
19. The computing device of claim 11 , wherein each source comprises a preference order.
20. A non-transitory computer-readable medium having stored thereon instructions that, when executed by one or more processors, cause the one or more processor to perform operations for visualizing performance data of infrastructure components, including:
receiving a query through an application for a metric for an infrastructure component, the metric comprising metric time series (MTS) data;
identifying sources for the metric;
querying the identified sources for the metric;
selecting, from the identified sources, best available data for the metric based on a selection algorithm, the selection algorithm including:
determining whether the identified sources have null values for the metric,
excluding sources from the identified sources determined to have the null values for the metric,
comparing remaining data sources from the identified sources based on policies that define an identity of a particular metric, and
when data from at least two of the remaining data sources are available, selecting the best available data;
enriching the best available data comprising linking dimensions and properties from the identified sources to the best available data; and
causing display of the enriched best available data through a user interface of the application.