System and method for resolving error messages in an error message repository
A method for managing error messages includes obtaining, by a message resolution manager, a plurality of error messages, performing an error message consecutive deduplication on the plurality of error messages to obtain a plurality of deduplicated error messages, generating a plurality of message sequences using the plurality deduplicated error messages, applying a message sequence frequency algorithm to the plurality of message sequences to obtain a high severity message sequence list, and initiating an error message resolution on at least one message sequence specified in the high severity message sequence list.
1. A method for managing a production host environment, the method comprising:
obtaining, by a message resolution manager, a plurality of error messages;
performing an error message consecutive deduplication on the plurality of error messages to obtain a plurality of deduplicated error messages;
generating a plurality of message sequences using the plurality deduplicated error messages;
applying a message sequence frequency algorithm to the plurality of message sequences to obtain a high severity message sequence list, wherein applying the message sequence frequency algorithm comprises:
generating a sequence frequency track mapping based on the plurality of message sequences;
generating, using the frequency track mapping, a severity score for each message code specified in each message sequence in the plurality of message sequences;
performing, using the severity scores, a k-means clustering evaluation for each message sequence to obtain a list of sequence clusters, wherein each sequence cluster specifies at least a portion of the plurality of message sequences; and
generating, based on the k-means clustering evaluation, the high severity message sequence list by specifying a message sequence in each sequence cluster in the list of sequence clusters; and
initiating an error message resolution on at least one message sequence specified in the high severity message sequence list.
2. The method of claim 1 , further comprising:
updating an error-resolution mapping based on the high severity error message list.
3. The method of claim 2 , wherein initiating the error resolution comprises using, after the updating, the error-resolution mapping to identify a resolution to an error message specified in the high severity message sequence list.
4. The method of claim 1 , wherein an error message in the plurality of error messages comprises an error message identifier, a device identifier, an error message code, and a timestamp.
5. The method of claim 1 , wherein the plurality of error messages is obtained from at least one selected from a group consisting of a client, a backup storage, and a production host.
6. A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor enables the computer processor to perform a method for performing a backup operation, the method comprising:
obtaining, by a message resolution manager, a plurality of error messages;
performing an error message consecutive deduplication on the plurality of error messages to obtain a plurality of deduplicated error messages;
generating a plurality of message sequences using the plurality deduplicated error messages;
applying a message sequence frequency algorithm to the plurality of message sequences to obtain a high severity message sequence list, wherein applying the message sequence frequency algorithm comprises:
generating a sequence frequency track mapping based on the plurality of message sequences;
generating, using the frequency track mapping, a severity score for each message code specified in each message sequence in the plurality of message sequences;
performing, using the severity scores, a k-means clustering evaluation for each message sequence to obtain a list of sequence clusters, wherein each sequence cluster specifies at least a portion of the plurality of message sequences; and
generating, based on the k-means clustering evaluation, the high severity message sequence list by specifying a message sequence in each sequence cluster in the list of sequence clusters; and
initiating an error message resolution on at least one message sequence specified in the high severity message sequence list.
7. The non-transitory computer readable medium of claim 6 , further comprising:
updating an error-resolution mapping based on the high severity error message list.
8. The non-transitory computer readable medium of claim 7 , wherein initiating the error resolution comprises using, after the updating, the error-resolution mapping to identify a resolution to an error message specified in the high severity message sequence list.
9. The non-transitory computer readable medium of claim 6 , wherein an error message in the plurality of error messages comprises an error message identifier, a device identifier, an error message code, and a timestamp.
10. The non-transitory computer readable medium of claim 6 , wherein the plurality of error messages is obtained from at least one selected from a group consisting of a client, a backup storage, and a production host.
11. A system, comprising:
a processor; and
memory comprising instructions which, when executed by the processor, perform a method, the method comprising:
obtaining, by a message resolution manager, a plurality of error messages;
performing an error message consecutive deduplication on the plurality of error messages to obtain a plurality of deduplicated error messages;
generating a plurality of message sequences using the plurality deduplicated error messages;
applying a message sequence frequency algorithm to the plurality of message sequences to obtain a high severity message sequence list, wherein applying the message sequence frequency algorithm comprises:
generating a sequence frequency track mapping based on the plurality of message sequences;
generating, using the frequency track mapping, a severity score for each message code specified in each message sequence in the plurality of message sequences;
performing, using the severity scores, a k-means clustering evaluation for each message sequence to obtain a list of sequence clusters, wherein each sequence cluster specifies at least a portion of the plurality of message sequences; and
generating, based on the k-means clustering evaluation, the high severity message sequence list by specifying a message sequence in each sequence cluster in the list of sequence clusters; and
initiating an error message resolution on at least one message sequence specified in the high severity message sequence list.
12. The system of claim 11 , further comprising:
updating an error-resolution mapping based on the high severity error message list.
13. The system of claim 12 , wherein initiating the error resolution comprises using, after the updating, the error-resolution mapping to identify a resolution to an error message specified in the high severity message sequence list.
14. The system of claim 11 , wherein an error message in the plurality of error messages comprises an error message identifier, a device identifier, an error message code, and a timestamp.