Cloud-based platform instrumentation and monitoring system for maintenance of user-configured programs

Patent metadata

Field	Value
Publication number	US-11520761-B2
Application number	US-201916659152-A
Country	US
Kind code	B2
Filing date	Oct 21, 2019
Priority date	Feb 2, 2016
Publication date	Dec 6, 2022
Grant date	Dec 6, 2022

Abstract

Systems and methods for using instrumentation for maintenance of a user-configured program in a cloud computing environment are herein disclosed as comprising, in an implementation, intercepting operation data pertaining to the user-configured program, including a start time, an execution time interval, an operation, and an origin of the operation, canonicalizing the intercepted operation data by stripping operation-specific variable data from the operation data, aggregating the canonicalized operation data based on the start time, the canonicalized operation data, and the origin of the operation, and storing the aggregated operation data within a time series database in the execution time interval based on the start time.

First claim

What is claimed is:

1. A cloud computing system, comprising:
a processor; and
a memory, accessible by the processor, the memory storing instructions, that when executed by the processor, cause the processor to perform operations comprising:
receiving operation data associated with an operation of a user-configured program, the operation data comprising a start time and an origin of the operation;
canonicalizing the operation data into one or more canonicalized representations of the operation data associated with respective executions of the operation by the user-configured program by removing operation-specific variable data to generate stripped operation data for the operation, wherein the operation-specific variable data comprises data associated with one or more parameters from a first execution of the operation and additional data associated with the one or more parameters from a second execution of the operation, wherein the data associated with the first execution of the operation is different from the additional data associated with the second execution of the operation;
creating aggregated operation data based on the stripped operation data, wherein the stripped operation data comprises the start time and the origin; and
identifying a root cause of a performance issue associated with the user-configured program based on the aggregated operation data.

2. The cloud computing system of claim 1 , wherein identifying the root cause of the performance issue comprises identifying one or more operations of the user-configured program that contributed to a slower performance of one or more transactions associated with the user-configured program.

3. The cloud computing system of claim 1 , wherein the origin of the operation is indicative of one or more additional operations that directly call the operation or result in execution of the operation.

4. The cloud computing system of claim 1 , wherein creating the aggregated operation data comprises generating a hashcode representative of the stripped operation data for the operation and creating the aggregated operation data based on the start time, the stripped operation data, the origin, and the hashcode.

5. The cloud computing system of claim 1 , wherein the operation data comprises an execution time interval, and the operations comprise storing the aggregated operation data in a database based on the start time and the execution time interval.

6. The cloud computing system of claim 1 , wherein the operations comprise transmitting a graphical representation of one or more performance metrics associated with each operation of the user-configured program to a user device for display.

7. The cloud computing system of claim 6 , wherein the graphical representation comprises an origin of each operation of the user-configured program, an execution time interval of each operation of the user-configured program, or an execution sequence of each operation of the user-configured program, or a combination thereof.

8. A method, comprising:
receiving operation data associated with an operation of a user-configured program, the operation data comprising a start time, an execution time interval, and an origin of the operation indicative of one or more additional operations that directly call the operation or result in execution of the operation;
canonicalizing the operation data into one or more canonicalized representations of the operation data associated with respective executions of the operation by the user-configured program by removing operation-specific variable data to generate stripped operation data for the operation, wherein the operation-specific variable data comprises data associated with one or more parameters from a first execution of the operation and additional data associated with the one or more parameters from a second execution of the operation, wherein the data associated with the first execution of the operation is different from the additional data associated with the second execution of the operation;
creating aggregated operation data based on the stripped operation data, wherein the stripped operation data comprises the start time and the origin; and
identifying a root cause of a performance issue associated with the operation based on the aggregated operation data.

9. The method of claim 8 , wherein identifying the root cause of the performance issue comprises identifying one or more operations of the user-configured program that contributed to a slower performance of one or more transactions associated with the user-configured program.

10. The method of claim 8 , wherein creating the aggregated operation data comprises generating a hashcode representative of the stripped operation data for the operation and creating the aggregated operation data based on the start time, the stripped operation data, the origin, and the hashcode.

11. The method of claim 8 , comprising transmitting a graphical representation of one or more performance metrics associated with each operation of the user-configured program to a user device for display.

12. The method of claim 11 , wherein the graphical representation comprises an origin of each operation of the user-configured program, an execution time interval of each operation of the user-configured program, or an execution sequence of each operation of the user-configured program, or a combination thereof.

13. The method of claim 8 , wherein the operation-specific variable data comprises a portion of the operation data associated with the respective executions of the operation.

14. A non-transitory, computer-readable medium, comprising instructions that when executed by one or more processors, cause the one or more processors to perform operations comprising:
receiving operation data associated with an operation of a user-configured program, the operation data comprising a start time, an execution time interval, and an origin of the operation;
canonicalizing the operation data into one or more canonicalized representations of the operation data associated with respective executions of the operation by the user-configured program by removing operation-specific variable data to generate stripped operation data for the operation, wherein the operation-specific variable data comprises data associated with one or more parameters from a first execution of the operation and additional data associated with the one or more parameters from a second execution of the operation, wherein the data associated with the first execution of the operation is different from the additional data associated with the second execution of the operation;
creating aggregated operation data based on the stripped operation data, wherein the stripped operation data comprises the start time and the origin; and
identifying a root cause of a performance issue associated with the operation based on the aggregated operation data.

15. The non-transitory, computer-readable medium of claim 14 , wherein identifying the root cause of the performance issue comprises identifying one or more operations of the user-configured program that contributed to a slower performance of one or more transactions associated with the user-configured program.

16. The non-transitory, computer-readable medium of claim 14 , wherein creating the aggregated operation data comprises generating a hashcode representative of the stripped operation data for the operation and creating the aggregated operation data based on the start time, the stripped operation data, the origin, and the hashcode.

17. The non-transitory, computer-readable medium of cl

Assignees

• Servicenow Inc

Inventors

• Laethem Jared

Classifications

• G06F11/3452

  Performance evaluation by statistical analysis · CPC title

• G06F16/22 Primary

  Indexing; Data structures therefor; Storage structures · CPC title

• G06F2201/86

  Event-based monitoring · CPC title

• G06F2201/875

  Monitoring of systems including the internet · CPC title

• G06F11/3612 Primary

  by runtime analysis (performance monitoring G06F11/3466) · CPC title