Automatic analysis of log entries through use of clustering
First Claim
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1. A method in a computerized environment, said method comprising:
- obtaining a training set of log entries, wherein the log entries describe an operation of a system, wherein the log entries comprise at least one log entry which is indicative of a non-erroneous operation of the system;
automatically determining an approximated matching function between a log entry and at least one cluster based on the training set of the log entries, wherein said automatically determining the approximated matching function is performed using a machine learning process;
obtaining another set of log entries describing operation of the system;
associating the other set of log entries with the at least one cluster, based on the approximated matching function; and
providing an indication referring to the at least one cluster associated with the training set of the log entries and the other set of the log entries.
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Abstract
A set of log entries is automatically inspected to determine a bug. A training set is utilized to determine clustering of log identifications. Log entries are examined in real-time or retroactively and matched to clusters. Timeframe may also be matched to a cluster based on log entries associated with the timeframe. Error indications may be outputted to a user of the system in respect to a log entry or a timeframe.
40 Citations
18 Claims
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1. A method in a computerized environment, said method comprising:
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obtaining a training set of log entries, wherein the log entries describe an operation of a system, wherein the log entries comprise at least one log entry which is indicative of a non-erroneous operation of the system; automatically determining an approximated matching function between a log entry and at least one cluster based on the training set of the log entries, wherein said automatically determining the approximated matching function is performed using a machine learning process; obtaining another set of log entries describing operation of the system; associating the other set of log entries with the at least one cluster, based on the approximated matching function; and providing an indication referring to the at least one cluster associated with the training set of the log entries and the other set of the log entries. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computerized apparatus, the apparatus comprising a hardware processor which is arranged to:
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obtain a training set of log entries, wherein the log entries describe an operation of a system, wherein the log entries comprise at least one log entry which is indicative of a non-erroneous operation of the system; automatically determine an approximated matching function between a log entry and at least one cluster based on the training set of the log entries, wherein said automatically determining the approximated matching function is performed using a machine learning process; obtain another set of log entries describing operation of the system; associate the other set of log entries with the at least one cluster, based on the approximated matching function; and provide an indication referring to the at least one cluster associated with the training set of the log entries and the other set of the log entries. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A computer program product, said computer program product comprising a non-transitory computer readable medium, in which computer instructions are stored, which instructions, when read by a computer, cause the computer to:
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obtain a training set of log entries, wherein the log entries describe an operation of a system, wherein the log entries comprise at least one log entry which is indicative of a non-erroneous operation of the system; automatically determine an approximated matching function between a log entry and at least one cluster based on the training set of the log entries, wherein said automatically determining the approximated matching function is performed using a machine learning process; obtain another set of log entries describing operation of the system; associate the other set of log entries with the at least one cluster, based on the approximated matching function; and provide an indication referring to the at least one cluster associated with the training set of the log entries and the other set of the log entries. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification