Persistent and self-learning debug process for server failure analysis
A method, computer system, and a computer program product are provided for debugging and determining root cause analysis of a server error. Resource data is obtained as relating to a server with error or debugging needs and grouped based on learned and programmed context specific components to determine a root cause analysis for the error or debugging need. An overall solution is then provided to address the server error or debugging need by evaluation a root cause analysis. The overall solution analyzes a plurality of disparate reasons causing the server error or debugging need and providing a single coherent solution based on interconnectivity of the plurality of disparate reasons. The overall solution is updated by obtaining historical data. A recommendation is then provided for the server to resolve the error or the debugging need based on the updated overall solution.
1 . A method for debugging and providing root cause analysis of server errors, comprising:
obtaining a plurality of resource data related to a server, wherein said server either has a debugging need or has a server error;
grouping said plurality of resource data based on learned and programmed context specific to said server;
generating a root cause analysis by determining and evaluating a plurality of issues causing said debugging need or said server error, wherein said plurality of issues are disparate and said root cause analysis determines interconnectivity of said plurality of issues;
providing an overall solution based on said root cause analysis; wherein said overall solution provides said overall solution based on interconnectivity of said plurality of issues;
updating said overall solution by obtaining a plurality of historical data, wherein said historical data relates to previous debugging needs or server errors related to said server;
analyzing a plurality of debugging steps iteratively to find a root causes reason before providing a feedback;
providing a recommendation to a user based on said feedback, for resolving said server error or debugging need based on said updated overall solution; and
restoring server based on recommendation for resolving said server error and debugging it based on any need for said updated overall solution.
2 . The method of claim 1 , wherein said recommendation and historical data are stored in a database.
3 . The method of claim 2 , wherein said historical data also relates to solutions provided for similar server errors or debugging needs on other servers.
4 . The method of claim 1 , wherein said recommendation is provided by a self-learning artificial intelligence (AI) engine.
5 . The method of claim 4 , wherein recommendation and historical data are stored in a database and used by the AI engine to reiteratively automate providing a future solution to other debugging and/or server errors.
6 . The method of claim 1 , further comprising generating a report to a user relating to said recommendation.
7 . The method of claim 6 , herein user provided feedback and received and incorporated in an updated recommendation.
8 . The method of claim 1 , wherein said recommendation is performed by said server.
9 . The method of claim 1 , wherein said server is a part of a computer network having a plurality of other servers and resource data is grouped based on server family.
10 . The method of claim 1 , wherein said server errors can be extensive or persistent.
11 . A computer system for debugging and providing root cause analysis of server errors, comprising:
one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is enabled to perform following steps:
obtaining a plurality of resource data related to a server, wherein said server either has a debugging need or has a server error;
grouping said plurality of resource data based on learned and programmed context specific to said server;
generating a root cause analysis by determining and evaluating a plurality of issues causing said debugging need or said server error, wherein said plurality of issues are disparate and said root cause analysis determines interconnectivity of said plurality of issues;
providing an overall solution based on said root cause analysis; wherein said overall solution provides said overall solution based on interconnectivity of said plurality of issues;
updating said overall solution by obtaining a plurality of historical data, wherein said historical data relates to previous debugging needs or server errors related to said server;
analyzing a plurality of debugging steps iteratively to find a root causes reason before providing a feedback;
providing a recommendation to a user based on said feedback, for resolving said server error or debugging need based on said updated overall solution; and
restoring server based on recommendation for resolving said server error and debugging it based on any need for said updated overall solution.
12 . The computer system of claim 11 , wherein said recommendation is provided by a self-learning artificial intelligence (AI) engine.
13 . The computer system of claim 12 , wherein said recommendation and historical data are stored in a database and used by the AI engine to reiteratively automate providing a future solution to other debugging and/or server errors.
14 . The computer system of claim 11 , further comprising generating a report to a user including said recommendation.
15 . The computer system of claim 14 , wherein user provided feedback and received is incorporated in an updated recommendation.
16 . The computer system of claim 11 , wherein said recommendation is performed by said server.
17 . The computer system of claim 11 , wherein said server errors can be extensive or persistent.
18 . A computer program product for debugging and providing root cause analysis of server errors, comprising:
one or more computer-readable storage medium and program instructions stored on at least one or more tangible storage medium, the program instructions executable by a processor, the program instructions comprising:
program instructions to obtain a plurality of resource data related to a server, wherein said server either has a debugging need or has a server error;
program instructions to group said plurality of resource data based on learned and programmed context specific components related to said server;
program instructions to generate a root cause analysis by determining and evaluating a plurality of issues causing said debugging need or said server error, wherein said plurality of issues are disparate and said root cause analysis determines interconnectivity of said plurality of issues;
program instructions to provide an overall solution based on said root cause analysis; wherein said overall solution provides said overall solution based on interconnectivity of said plurality of issues;
program instructions to update said overall solution by obtaining a plurality of historical data, wherein said historical data relates to previous debugging needs or server errors related to said server;
program instructions to analyze a plurality of debugging steps iteratively to find a root causes reason before providing a feedback;
program instructions to provide providing a recommendation to a user based on said feedback, for resolving said server error or debugging need based on said updated overall solution; and
program instructions to restore server based on recommendation for resolving said server error and debugging it based on any need for said updated overall solution.
19 . The computer program product of claim 18 , wherein said recommendation is provided by a self-learning artificial intelligence (AI) engine.
20 . The computer program product of claim 19 , wherein said recommendation and historical data are stored in a database and used by the AI engine to reiteratively automate providing a future solution to other debugging and/or server errors.