Correlating log data with performance measurements having a specified relationship to a threshold value

• US 10,318,541 B2
• Filed: 01/31/2017
• Issued: 06/11/2019
• Est. Priority Date: 04/30/2013
• Status: Active Grant

• Current Assignee: Splunk Inc.
• Original Assignee: Splunk Inc.
• Inventors: Bingham, Brian, Fletcher, Tristan, Bhide, Alok Anant
• Primary Examiner(s): Desta, Elias
• Application Number:
  US15/421,395
• Publication Number:
  US 20170255683A1
• Time in Patent Office: 861 Days
• CPC Class Codes: G06F 11/3006 where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems multiprogramming arrangements G06F9/46; allocation of resources G06F9/50
• CPC Class Codes: G06F 11/301 where the computing system is a virtual computing platform, e.g. logically partitioned systems virtual machines G06F9/45533; logical partitioning of resources G06F9/5077
• CPC Class Codes: G06F 11/3024 where the computing system component is a central processing unit [CPU]
• CPC Class Codes: G06F 11/3037 where the computing system component is a memory, e.g. virtual memory, cache accessing, addressing or allocating within memory systems or architectures G06F12/00; checking stores for correct operation G11C29/00
• CPC Class Codes: G06F 11/323 Visualisation of programs or trace data
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 17/40 Data acquisition and logging for input to computer G06F3/00
• CPC Class Codes: G06F 2201/815 Virtual middleware or OS functionality using virtual machines to implement generic software techniques for error detection or fault masking G06F11/1484
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 9/45533 Hypervisors; Virtual machine monitors

Abstract

The disclosed system and method acquire and store performance measurements relating to performance of a component in an information technology (IT) environment and log data produced by the IT environment, in association with corresponding time stamps. The disclosed system and method correlate at least one of the performance measurements with at least one of the portions of log data.

Claims

1. A computer-implemented method for improving data analysis of performance of components in an information technology environment, the method comprising:

acquiring, by a computer system, performance measurements for a performance metric, each of the performance measurements indicating an extent of performance of at least one hardware or software component of an information technology (IT) environment at a particular time for the performance metric;

acquiring, by the computer system, log data representing activity of the at least one hardware or software component of the IT environment;

comparing, by the computer system, the performance measurements to a threshold value to determine a portion of the performance measurements having a specified relationship to the threshold value;

correlating, by the computer system, a portion of the log data with at least one of the performance measurements in the portion of the performance measurements having the specified relationship to the threshold value, the correlation based on a correlation criterion; and

causing display, via a graphical user interface, of an indication of the portion of the log data and an indication of the at least one of the performance measurements having the specified relationship to the threshold value to indicate performance of the at least one hardware or software component of the IT environment for the performance metric in association with the correlated log data wherein the indications of the correlated portion of log data and the at least one of the performance measurements facilitate determining unsatisfactory performance of a hardware or software component of the information technology (IT) environment and implementing a modification to the IT environment to address the unsatisfactory performance of the hardware or software component.

2. A method as recited in claim 1, further comprising:

causing display of the portion of the log data and the at least one of the performance measurements.

3. A method as recited in claim 1, further comprising:

causing concurrent display of the portion of the log data and the at least one of the performance measurements.

4. A method as recited in claim 1, further comprising:

causing concurrent display of a listing of raw log data from the portion of the log data and the at least one of the performance measurements.

5. A method as recited in claim 1, wherein said correlating is based on a user-specified correlation criterion.

6. A method as recited in claim 1, wherein said correlating is based on a user-specified correlation criterion that is not a time-based criterion.

7. A method as recited in claim 1, wherein said correlating is based on a user-specified correlation criterion that relates to a machine in the IT environment.

8. A method as recited in claim 1 further comprising:

obtaining the correlation criterion from a user input to a graphical user interface element that enables a user to input a search criterion as said correlation criterion but does not enable input of a complete search query.

9. A method as recited in claim 1 further comprising:

obtaining the correlation criterion from a user'"'"'s selection from a drop-down list in a graphical user interface.

10. A method as recited in claim 1, wherein said correlating is based on the correlation criterion that relates to a machine in the IT environment and is specified by a user'"'"'s selection from a drop-down list of machines included in the IT environment.

11. A method as recited in claim 1 further comprising, prior to said correlating:

obtaining the correlation criterion from a search query input by a user into a query box in a text-based search query language.

12. A method as recited in claim 1 further comprising

storing each of the acquired performance measurements and each of the acquired log data with a time-stamp in a time-series data store

wherein said correlating further comprises identifying the portion of the log data and the at least one of the performance measurements that have time stamps that satisfy a user-specified time criterion.

13. A method as recited in claim 1, wherein the performance measurements have been determined by direct measurement of a hardware or software component in the IT environment.

14. A method as recited in claim 1, wherein the log data are derived from a text-based log file.

15. A method as recited in claim 1, wherein the performance measurements are not derived from a log file and are acquired independently of the log data.

16. A method as recited in claim 1, wherein the performance measurements are acquired independently of the log data, and wherein the performance measurements have been determined by direct measurement of a hardware or software component in the IT environment and the log data are derived from a text-based log file.

17. A method as recited in claim 1, wherein the performance measurements are acquired independently of the log data by direct measurement of a hardware or software component in the IT environment, and the log data are acquired independently of the performance measurements.

18. A method as recited in claim 1, wherein acquiring the performance measurements comprises acquiring, via an application programming interface (API), the performance measurements from a third-party software application that collects the performance measurements.

19. A method as recited in claim 1, wherein the performance measurements are stored in a first time-series data store, and the log data are stored in a second time-series data store separate from the first time-series data store.

20. A method as recited in claim 1, wherein the performance measurements are stored in a time-series data store in a first format, and the log data are stored in said time-series data store in a second format different from the first format.

21. A method as recited in claim 1, wherein the performance measurements are stored in a first time-series data store in a first format, and the log data are stored in a second time-series data store separate from the first time-series data store in a second format different from the first format.

22. A method as recited in claim 1, wherein the performance measurements are stored in a first time-series data store in a first format, and the log data are stored in a second time-series data store separate from the first time-series data store in a second format different from the first format;

the method further comprising;

receiving a user-specified search query in a query language for searching the first and second time-series data stores, the user-specified search query containing the correlation criterion;

wherein said correlating further includes, in response to the user-specified search query, searching the first time-series data store for performance data that satisfy the correlation criterion and searching the second time-series data store for log data that satisfy the correlation criterion.

23. A method as recited in claim 1, wherein the performance measurements are stored in a first time-series data store in a first format, and the log data are stored in a second time-series data store separate from the first time-series data store in a second format different from the first format;

the method further comprising;

receiving a user-specified search query in a query language for searching the first and second time-series data stores, the user-specified search query containing the correlation criterion, wherein the correlation criterion comprises a user-specified value or a user-specified range of values, for a user-specified field;

wherein said correlating further includes, in response to the user-specified search query, searching the first time-series data store for performance data that satisfy the correlation criterion and searching the second time-series data store for log data that satisfy the correlation criterion.

24. A method as recited in claim 1, further comprising:

acquiring structure data indicative of structure characteristics of the IT environment;

storing the acquired structure data indicative of structure characteristics of the IT environment; and

correlating a performance characteristic of the IT environment with a structure characteristic of the IT environment, based on the stored performance measurements and stored structure data.

25. A method as recited in claim 1, further comprising:

acquiring structure data indicative of structure characteristics of the IT environment, wherein the structure data is derived from the log data from the IT environment;

storing the acquired structure data indicative of structure characteristics of the IT environment; and

correlating a performance characteristic of the IT environment with a structure characteristic of the IT environment, based on the stored performance measurements and stored structure data.

26. A method as recited in claim 1, wherein the at least one performance metric comprises a performance metric for at least one hardware or software resource of a computer system.

27. A method as recited in claim 1, wherein the at least one performance metric comprises a performance metric for at least one virtual machine or virtual machine host.

28. A method as recited in claim 1, wherein the at least one performance metric comprises a performance metric for a virtual machine cluster.

29. A non-transitory machine-readable storage medium for use in a processing system of a data intake and query system, the non-transitory machine-readable storage medium storing instructions, an execution of which in the processing system causes the processing system to perform operations comprising:

acquiring, by a computer system, performance measurements a performance metric, each of the performance measurements indicating an extent of performance of at least one hardware or software component of an information technology (IT) environment at a particular time for the performance metric;

acquiring, by the computer system, log data representing activity of the at least one hardware or software component of the IT environment;

comparing, by the computer system, the performance measurements to a threshold value to determine a portion of the performance measurements having a specified relationship to the threshold value;

correlating, by the computer system, a portion of the log data with at least one of the performance measurements in the portion of the performance measurements having the specified relationship to the threshold value, the correlation based on a correlation criterion; and

causing display, via a graphical user interface, of an indication of the portion of the log data and an indication of the at least one of the performance measurements having the specified relationship to the threshold value to indicate performance of the at least one hardware or software component of the IT environment for the performance metric in association with the correlated log data wherein the indications of the correlated portion of log data and the at least one of the performance measurements facilitate determining unsatisfactory performance of a hardware or software component of the information technology (IT) environment and implementing a modification to the IT environment to address the unsatisfactory performance of the hardware or software component.

30. A system comprising:

a communication device through which to communicate on a computer network; and

at least one processor operatively coupled to the communication device and configured to perform operations including

acquiring, by a computer system, performance measurements for a performance metric, each of the performance measurements indicating an extent of performance of at least one hardware or software component of an information technology (IT) environment at a particular time for the performance metric;

acquiring, by the computer system, log data representing activity of the at least one hardware or software component of the IT environment;

comparing, by the computer system, the performance measurements to a threshold value to determine a portion of the performance measurements having a specified relationship to the threshold value;

correlating, by the computer system, a portion of the log data with at least one of the performance measurements in the portion of the performance measurements having the specified relationship to the threshold value, the correlation based on a correlation criterion; and

causing display, via a graphical user interface, of an indication of the portion of the log data and an indication of the at least one of the performance measurements having the specified relationship to the threshold value to indicate performance of the at least one hardware or software component of the IT environment for the performance metric in association with the correlated log data wherein the indications of the correlated portion of log data and the at least one of the performance measurements facilitate determining unsatisfactory performance of a hardware or software component of the information technology (IT) environment and implementing a modification to the IT environment to address the unsatisfactory performance of the hardware or software component.