Method and system to monitor the operation of an application

1 . A method for monitoring operation of an application, the method comprising:

acquiring data, said data comprising a plurality of key performance indicators related to a current operation of the application;

determining, based on the data that is acquired, forecasted data comprising a plurality of key performance indicators related to a future operation of the application;

automatically scheduling one or more monitoring sessions targeting at least one component of the application corresponding to a group of key performance indicators, the group of key performance indicators comprising each key performance indicator of the plurality of key performance indicators related to the future operation of the application of the forecasted data having a value moving away from a corresponding predefined value range being associated with a normal operation of the application, wherein each of said one or more monitoring sessions targeting said at least one component of the application is associated with a list of keywords linked to a corresponding targeted component of the at least one component;

obtaining, from a user, using a conversational agent, information related to an anomalous behavior of the application;

analyzing the information that is obtained from said user to get said list of keywords and identifying a monitoring session from said one or more monitoring sessions comprising a most keywords in common with said information;

modifying said monitoring session that is identified as comprising the most keywords in common with said information based on the information.

2 . The method according to claim 1 , wherein the monitoring session that is scheduled is associated with one or more of

a scheduled monitoring date, by which the monitoring session has to be completed;

each component of said at least one component of the application that is targeted by the monitoring session that is scheduled;

wherein the modifying the monitoring session comprises modifying one or more of

the scheduled monitoring date,

at least one of said each component associated with the monitoring session.

3 . The method according to claim 1 , wherein the obtaining the information comprises asking by the conversational agent, at least one question to the user and receiving by the conversational agent, at least one answer from the user to each question of said at least one question that is asked, the information being extracted from each answer of said at least one answer that is received from the user.

4 . The method according to claim 1 , wherein the obtaining the information comprises detecting, using the conversational agent, a mood of the user, and the modifying the monitoring session is further based on the mood that is detected.

5 . The method according to claim 1 , wherein the forecasted data is determined over a predetermined period of time.

6 . The method according to claim 1 , wherein the forecasted data is determined by a machine learning algorithm trained to predict data related to the operation of the application at a given instant from data related to the operation of the application at an instant preceding the given instant.

7 . The method according to claim 6 , wherein the machine learning algorithm is trained in a supervised way using a training database, the training database comprising a history of data related to the operation of the application.

8 . A system comprising:

a microcontroller, and

a conversational agent;

wherein said system, via said microcontroller and said conversational agent, is configured to execute instructions for monitoring an operation of an application, comprising

acquiring data, said data comprising a plurality of key performance indicators related to a current operation of the application;

determining, based on the data that is acquired, forecasted data comprising a plurality of key performance indicators related to a future operation of the application;

automatically scheduling one or more monitoring sessions targeting at least one component of the application corresponding to a group of key performance indicators, the group of key performance indicators comprising each key performance indicator of the plurality of key performance indicators related to the future operation of the application of the forecasted data having a value moving away from a corresponding predefined value range being associated with a normal operation of the application, wherein each of said one or more monitoring sessions targeting said at least one component of the application is associated with a list of keywords linked to a corresponding targeted component of the at least one component;

obtaining, from a user, using said conversational agent, information related to an anomalous behavior of the application;

analyzing the information that is obtained from said user to get said list of keywords and identifying a monitoring session from said one or more monitoring sessions comprising a most keywords in common with said information;

modifying said monitoring session that is identified as comprising the most keywords in common with said information based on the information.

9 . The system of claim 8 , wherein said system further comprises a non-transitory computer program comprising said instructions.

10 . A non-transitory computer-readable medium comprising instructions which, when executed by a system, cause the system to carry out a method for monitoring operation of an application;

wherein said system comprises

a non-transitory computer program,

a microcontroller, and

a conversational agent; and

wherein said method comprises:

acquiring data, said data comprising a plurality of key performance indicators related to a current operation of the application;

determining, based on the data that is acquired, forecasted data comprising a plurality of key performance indicators related to a future operation of the application;

automatically scheduling one or more monitoring sessions targeting at least one component of the application corresponding to a group of key performance indicators, the group of key performance indicators comprising each key performance indicator of the plurality of key performance indicators related to the future operation of the application of the forecasted data having a value moving away from a corresponding predefined value range being associated with a normal operation of the application, wherein each of said one or more monitoring sessions targeting said at least one component of the application is associated with a list of keywords linked to a corresponding targeted component of the at least one component;

obtaining, from a user, using said conversational agent, information related to an anomalous behavior of the application;

analyzing the information to get said list of keywords and identifying a monitoring session from said one or more monitoring sessions comprising a most keywords in common with said information;

modifying said monitoring session that is identified as comprising the most keywords in common with said information based on the information.