Anomaly detection and classification using telemetry data

1. A computer-implemented method comprising:

receiving telemetry data originating from a plurality of client devices, wherein the telemetry data was generated in response to the plurality of client devices accessing an online service provided by a service provider;

selecting a class of data from the telemetry data;

converting the class of data to a set of metrics;

aggregating the set of metrics according to a component that is used to implement the online service;

obtaining values of aggregated metrics over time for the component based at least in part on aggregating the set of metrics;

determining a prediction error by comparing the values of the aggregated metrics to a prediction, the prediction being based at least in part on historical telemetry data pertaining to the class of data and the component;

detecting an anomaly based at least in part on the prediction error; and

transmitting an alert message of the anomaly.

2. The computer-implemented method of claim 1 , further comprising initiating an automatic recovery action with respect to the component.

3. The computer-implemented method of claim 1 , further comprising determining that the component is an internet service provider (ISP) that is outside of a domain of the service provider.

4. The computer-implemented method of claim 3 , wherein aggregating the set of metrics comprises:

determining the ISP from an Internet Protocol (IP) address in the telemetry data, the IP address corresponding to a subset of data in the class of data; and

aggregating set of metrics for the subset of data in the class of data that corresponds to the IP address.

5. The computer-implemented method of claim 4 , wherein determining the ISP from the IP address comprises performing a reverse lookup of the ISP using the IP address.

6. The computer-implemented method of claim 3 , wherein the class of data corresponds to an error indicative of a problem with the ISP.

7. The computer-implemented method of claim 1 , further comprising generating the prediction by computing a Fast Fourier Transform (FFT) on historical values pertaining to the class of data accessed from the historical telemetry data.

8. A system comprising:

one or more processors;

memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving telemetry data originating from a plurality of client devices;

selecting a class of data from the telemetry data;

converting the class of data to a set of metrics;

aggregating the set of metrics according to a component of interest to obtain values of aggregated metrics over time for the component of interest;

determining a prediction error by comparing the values of the aggregated metrics to a prediction, the prediction being based at least in part on historical telemetry data pertaining to the class of data and the component of interest;

detecting an anomaly based at least in part on the prediction error; and

initiating an automatic recovery action with respect to the component of interest.

9. The system of claim 8 , the operations further comprising determining that the component of interest is within a domain of a service provider of an online service.

10. The system of claim 9 , wherein:

the component of interest comprises a server in a data center that implements the online service; and

the automatic recovery action comprises at least one of updating code of the server with a code patch, rebooting the server, or transitioning a plurality of user sessions from the server to a different server of the data center.

11. The system of claim 9 , wherein:

the component of interest comprises the online service; and

the automatic recovery action comprises at least one of recycling the online service, or extending a subscription for a tenant of the online service.

12. The system of claim 8 , wherein:

determining the prediction error comprises determining a difference between the prediction and the values of the aggregated metrics at a time of day; and

detecting the anomaly comprises determining that the difference is greater than a threshold difference.

13. The system of claim 8 , wherein:

determining the prediction error comprises determining a series of differences between the prediction and the values of the aggregated metrics over a period of time; and

detecting the anomaly further comprises determining that the series of differences exceeds a threshold difference over the period of time.

14. The system of claim 8 , wherein:

the class of data corresponds to users who access an online service; and

the set of metrics corresponds to counts of the users who access the online service.

15. The system of claim 8 , the operations further comprising generating the prediction by computing a Fast Fourier Transform (FFT) on historical values pertaining to the class of data accessed from the historical telemetry data.

16. One or more computer-readable storage media storing instructions that, when executed by one or more processors, perform operations comprising:

receiving telemetry data originating from a plurality of client devices;

selecting a class of data from the telemetry data;

converting the class of data to a set of metrics;

aggregating the set of metrics according to a component of interest to obtain values of aggregated metrics over time for the component of interest;

determining a prediction error by comparing the values of the aggregated metrics to a prediction, the prediction being based at least in part on historical telemetry data pertaining to the class of data and the component of interest;

detecting an anomaly based at least in part on the prediction error; and

transmitting an alert message of the anomaly.

17. The computer-readable storage media of claim 16 , wherein:

the component of interest comprises an internet service provider (ISP) that enables the plurality of client devices to access to an online service; and

the ISP is outside of a domain of a service provider of the online service.

18. The computer-readable storage media of claim 17 , wherein the class of data corresponds to an error indicative of a problem with the ISP.

19. The computer-readable storage media of claim 18 , wherein the alert message includes an identification of the error and contact information of the ISP.

20. The computer-readable storage media of claim 16 , the operations further comprising generating the prediction by computing a Fast Fourier Transform (FFT) on historical values pertaining to the class of data accessed from the historical telemetry data.