Systems and methods for importing software license metric data into a configuration management database (CMDB)

Patent metadata

Field	Value
Publication number	US-11520863-B2
Application number	US-201916287655-A
Country	US
Kind code	B2
Filing date	Feb 27, 2019
Priority date	Feb 27, 2019
Publication date	Dec 6, 2022
Grant date	Dec 6, 2022

Abstract

The present disclosure relates to importing license data from a license metric tool server (LMTS) into a configuration management database (CMDB). License records are requested and received from the LMTS and are subsequently imported as into the CMDB of a client instance as configuration item (CI) data. In certain circumstances, a license record may have an identifier field (ID) value that does not correspond to a CI of the CMDB, resulting in the license record failing to import. The disclosed process involves flagging license records that fail import, and then clustering the flagged license records into suitable groups. The flagged license records are then re-pulled from the LMTS in groups, rather than using individual requests for each flagged license record. By effectively clustering of the flagged license records into groups, the disclosed importation process enables a reduction in processing, memory, and/or communication overhead, improving operation of the client instance.

First claim

The invention claimed is:

1. A cloud-based computing system, comprising:
at least one memory storing a configuration management database (CMDB) and a license management tool server (LMTS), wherein the LMTS comprises an application programming interface (API) having a function configured to return series of license records having sequential identifier field (ID) values in response to function calls from the CMDB; and
at least one processor configured to execute stored instructions to perform actions, comprising:
calling the function of the API of the LMTS a first time to return an initial series of license records;
importing, into the CMDB, the initial series of license records and flagging the license records of the initial series that fail to import due to having respective ID values that do not correspond to configuration items (CIs) stored in the CMDB;
clustering the flagged license records of the initial series that failed to import into groups of flagged license records using a sliding window technique;
calling the function of the API of the LMTS additional times to return a respective additional series of license records for each of the groups of flagged license records, wherein a first overhead associated with executing the function the additional times is less than a second overhead associated with executing the function to return the initial series of license records and less than a third overhead associated with successively executing the function to individually return each of the flagged license records; and
importing, into the CMDB, the respective additional series of license records returned for each of the groups of flagged license records.

2. The cloud-based computing system of claim 1 , wherein the license records of the initial series have sequential ID values ranging from a first ID value to a last ID value, and wherein, to call the function of the API of the LMTS the first time to return the initial series of license records, the at least one processor is configured to execute the stored instructions to perform actions, comprising:
calling the function of the API of the LMTS the first time using an offset parameter value that is the first ID value and a limit parameter value that is a difference between the last ID value and the first ID value.

3. The cloud-based computing system of claim 1 , wherein, to use the sliding window technique to cluster the flagged license records of the initial series that failed to import, the at least one processor is configured to execute the stored instructions to perform actions, comprising:
determining a minimum difference, M, between the respective ID values of the flagged license records of the initial series;
traversing the initial series of license records using a sliding window, wherein a sliding window size is varied between M and A/2 to determine the sliding window size, K, to cluster the flagged license records, wherein A is a span of the initial series; and
clustering the flagged license records of the initial series into the groups of flagged license records, wherein a respective span of each of the groups of flagged license records is less than or equal to K.

4. The cloud-based computing system of claim 3 , wherein, to determine the sliding window size, K, to cluster the flagged license records, the at least one processor is configured to execute the stored instructions to perform actions, comprising:
calculating a respective cluster score for each respective sliding window size; and
determining the sliding window size, K, to be the respective sliding window size with a highest respective cluster score.

5. The cloud-based computing system of claim 4 , wherein the cluster score is calculated based on a ratio of a number of the flagged license records in a largest group of flagged license records to the respective sliding window size, a number of the groups of the flagged license records, a respective number of flagged license records in each of the groups of flagged license records, or a combination thereof.

6. The cloud-based computing system of claim 3 , wherein, to call the function of the API of the LMTS the additional times to request the respective additional series of license records for each group of the groups of flagged license records, the at least one processor is configured to execute the stored instructions to perform actions, comprising:
calling the function of the API of the LMTS an additional time to return the respective additional series of license records for each group using an offset parameter value that is a respective first ID value of each group and a limit parameter value that is a respective span of each group, wherein the limit parameter value is less than or equal to K.

7. The cloud-based computing system of claim 1 , wherein, to import the respective additional series of license records, the at least one processor is configured to execute the stored instructions to perform actions, comprising:
flagging license records of each respective additional series of license records having respective ID values that do not correspond to the CIs stored in the CMDB.

8. The cloud-based computing system of claim 1 , wherein the first overhead, the second overhead, and the third overhead comprise usage of the at least one processor, usage of the at least one memory, and communication between the CMDB and the LMTS.

9. A method, comprising:
calling a function of an application programming interface (API) of a license management tool server (LMTS) a first time to return an initial series of license records having sequential identifier field (ID) values;
importing, into a configuration management database (CMDB), the initial series of license records and flagging license records of the initial series that fail to import due to having respective ID values that do not correspond to configuration items (CIs) stored in the CMDB;
clustering the flagged license records of the initial series that failed to import into groups of flagged license records using a sliding window technique;
calling the function of the API of the LMTS additional times to return a respective additional series of license records for each of the groups of flagged license records, wherein a first overhead associated with executing the function the additional times is less than a second overhead associated with executing the function to return the initial series of license records and less than a third overhead associated with successively executing the function to individually return each of the flagged license records;
and
importing, into the CMDB, the respective additional series of license records returned for each of the groups of flagged license records.

10. The method of claim 9 , wherein the license records of the initial series have sequential ID values with a span, A, ranging from a first ID value to a last ID value, and calling the function of the API of the LMTS the first time to request the initial series of license records comprises:
calling the function of the API of the LMTS the first time using an offset parameter value that is the first ID value and a limit parameter value that is the span, A, of the initial series of license records.

11. The method of claim 9 , wherein the initial series of license records has a span, A, and wherein clustering the flagged license records of the initial series comprises:
determining a minimum difference, M, between the respective ID values of the flagged license records of the initial series; and
traversing the initial series of license records using a sliding window having a sliding window size that is varied between M and A/2 to determine the sliding window size, K, to group the flag

Assignees

• Servicenow Inc

Inventors

• Mallappa Preetam

Classifications

• G06F16/35

  Clustering; Classification · CPC title

• G06F9/54

  Interprogram communication · CPC title

• G06F16/2282

  Tablespace storage structures; Management thereof · CPC title

• G06F21/105 Primary

  Arrangements for software license management or administration, e.g. for managing licenses at corporate level · CPC title

• G06F16/285

  Clustering or classification · CPC title