Inspecting network performance at diagnosis points
A data-driven approach to network performance diagnosis and root-cause analysis is presented. By collecting and aggregating data attribute values across multiple components of a content delivery system and comparing against baselines for points of inspection, network performance diagnosis and root-cause analysis may be prioritized based on impact on content delivery. Recommended courses of action may be determined and provided based on the tracked network performance analysis at diagnosis points.
1. A method, comprising:
determining a diagnosis point associated with a component of a content delivery system;
receiving data associated with a version of the component of the content delivery system;
generating a metric associated with the diagnosis point based on the data, wherein the metric comprises a first composite metric, the first composite metric comprising one or more data attributes associated with one or more sub-components of the component;
responsive to the metric exceeding a threshold associated with an impact to the content delivery system, identifying one or more sub-components of the component that are likely contributors to an outcome associated with the first composite metric; and
generating a repair recommendation for a sub-component of the one or more sub-components based on a set of rules.
2. The method as recited in claim 1 , wherein the component comprises an agent on a user device of the content delivery system and the data is received from the agent.
3. The method as recited in claim 1 , wherein the component comprises a proxy server communicatively coupled to a server and the data is received from the proxy server, wherein the data is associated with the server.
4. The method as recited in claim 1 , wherein the metric comprises a performance metric comparing a data attribute of the data to a baseline.
5. The method as recited in claim 1 , wherein the identifying one or more sub-components identifies the one or more sub-components of the component that are likely contributors to the outcome based on a calculated savings.
6. The method as recited in claim 1 , wherein the determining the diagnosis point is based on historical data of problems experienced at the diagnosis point.
7. The method as recited in claim 1 , wherein the first composite metric measures a download completion time of one or more objects.
8. One or more non-transitory computer-readable storage media, storing one or more sequences of instructions, which when executed by one or more processors cause performance of:
determining a diagnosis point associated with a component of a content delivery system;
receiving data associated with a version of the component of the content delivery system;
generating a metric associated with the diagnosis point based on the data, wherein the metric comprises a first composite metric, the first composite metric comprising one or more data attributes associated with one or more sub-components of the component;
responsive to the metric exceeding a threshold associated with an impact to the content delivery system, identifying one or more sub-components of the component that are likely contributors to an outcome associated with the first composite metric; and
generating a repair recommendation for a sub-component of the one or more sub-components based on a set of rules.
9. The one or more non-transitory computer-readable storage media as recited in claim 8 , wherein the component comprises an agent on a user device of the content delivery system and the data is received from the agent.
10. The one or more non-transitory computer-readable storage media as recited in claim 8 , wherein the component comprises a proxy server communicatively coupled to a server and the data is received from the proxy server, wherein the data is associated with the server.
11. The one or more non-transitory computer-readable storage media as recited in claim 8 , wherein the metric comprises a performance metric comparing a data attribute of the data to a baseline.
12. The one or more non-transitory computer-readable storage media as recited in claim 8 , wherein the identifying one or more sub-components identifies the one or more sub-components of the component that are likely contributors to the outcome based on a calculated savings.
13. The one or more non-transitory computer-readable storage media as recited in claim 8 , wherein the determining the diagnosis point is based on historical data of problems experienced at the diagnosis point.
14. The one or more non-transitory computer-readable storage media as recited in claim 8 , wherein the first composite metric measures a download completion time of one or more objects.
15. An apparatus, comprising:
a performance analyzer, implemented at least partially in hardware, configured to determine a diagnosis point associated with a component of a content delivery system;
a data receiver, implemented at least partially in hardware, configured to receive data associated with a version of the component of the content delivery system;
wherein the performance analyzer generates a metric associated with the diagnosis point based on the data, wherein the metric comprises a first composite metric, the first composite metric comprising one or more data attributes associated with one or more sub-components of the component;
wherein the performance analyzer, responsive to the metric exceeding a threshold associated with an impact to the content delivery system, identifies one or more sub-components of the component that are likely contributors to an outcome associated with the first composite metric; and
wherein the performance analyzer, generates a repair recommendation for a sub-component of the one or more sub-components based on a set of rules.
16. The apparatus as recited in claim 15 , wherein the metric comprises a performance metric comparing a data attribute of the data to a baseline.
17. The apparatus as recited in claim 15 , wherein the identifying one or more sub-components identifies the one or more sub-components of the component that are likely contributors to the outcome based on a calculated savings.
18. The apparatus as recited in claim 15 , wherein the first composite metric measures a download completion time of one or more objects.
19. The apparatus as recited in claim 15 , wherein the component comprises an agent on a user device of the content delivery system and the data is received from the agent.
20. The apparatus as recited in claim 15 , wherein the performance analyzer determines the diagnosis point based on historical data of problems experienced at the diagnosis point.