Real-time collaboration dynamic logging level control
User activity pertaining to a product is automatically analyzed. Based, at least in part, on the analyzing the user activity pertaining to the product, a temporal logging level model can be derived. The temporal logging level model can determine a first logging level to be applied to the product. The temporal logging level model also can determine a duration of time for which the first logging level is to be applied to the product. Application of the first logging level to the product for the determined duration of time can be initiated.
1. A method, comprising:
automatically analyzing user activity pertaining to a product, the analyzing the user activity pertaining to the product comprising identifying keywords in electronic messages exchanged between users and inferring the keywords in the electronic messages as trigger statements;
based, at least in part, on the analyzing the user activity pertaining to the product, deriving, using a processor, a temporal logging level model, the temporal logging level model determining a first logging level to be applied to the product and the temporal logging level model determining a duration of time for which the first logging level is to be applied to the product; and
automatically initiating the first logging level to be applied to the product for the determined duration of time.
2. The method of claim 1 , wherein, responsive to the determined duration of time expiring, a second logging level is automatically applied to the product.
3. The method of claim 1 , wherein the analyzing the user activity pertaining to the product further comprises determining inter-arrival times between the electronic messages exchanged between the users.
4. The method of claim 1 , wherein the analyzing the user activity pertaining to the product further comprises determining a relevancy of the trigger statements inferred from the keywords in the electronic messages to at least one log entry.
5. The method of claim 1 , further comprising:
automatically analyzing log entries generated for the product;
wherein the deriving the temporal logging level model further is based on the analyzing the log entries generated for the product.
6. The method of claim 1 , wherein deriving the temporal logging level model comprises:
creating a neural network, the neural network comprising artificial neurons and connections between the artificial neurons, the connections between the artificial neurons assigned variable connection weights that adjust as learning is applied to the neural network; and
deriving the temporal logging level model from the neural network using a temporal logging level model matrix representing data in the electronic messages.
7. A system, comprising:
a processor programmed to initiate executable operations comprising:
automatically analyzing user activity pertaining to a product, the analyzing the user activity pertaining to the product comprising identifying keywords in electronic messages exchanged between users and inferring the keywords in the electronic messages as trigger statements;
based, at least in part, on the analyzing the user activity pertaining to the product, deriving a temporal logging level model, the temporal logging level model determining a first logging level to be applied to the product and the temporal logging level model determining a duration of time for which the first logging level is to be applied to the product; and
automatically initiating the first logging level to be applied to the product for the determined duration of time.
8. The system of claim 7 , wherein, responsive to the determined duration of time expiring, a second logging level is automatically applied to the product.
9. The system of claim 7 , wherein the analyzing the user activity pertaining to the product further comprises determining inter-arrival times between the electronic messages exchanged between the users.
10. The system of claim 7 , wherein the analyzing the user activity pertaining to the product further comprises determining a relevancy of the trigger statements inferred from the keywords in the electronic messages to at least one log entry.
11. The system of claim 7 , the executable operations further comprising:
automatically analyzing log entries generated for the product;
wherein the deriving the temporal logging level model further is based on the analyzing the log entries generated for the product.
12. The system of claim 7 , wherein deriving the temporal logging level model comprises:
creating a neural network, the neural network comprising artificial neurons and connections between the artificial neurons, the connections between the artificial neurons assigned variable connection weights that adjust as learning is applied to the neural network; and
deriving the temporal logging level model from the neural network using a temporal logging level model matrix representing data in the electronic messages.
13. A computer program product, comprising:
a computer readable storage medium having program code stored thereon, the program code executable by a data processing system to initiate operations including:
automatically analyzing user activity pertaining to a product, the analyzing the user activity pertaining to the product comprising identifying keywords in electronic messages exchanged between users and inferring the keywords in the electronic messages as trigger statements;
based, at least in part, on the analyzing the user activity pertaining to the product, deriving a temporal logging level model, the temporal logging level model determining a first logging level to be applied to the product and the temporal logging level model determining a duration of time for which the first logging level is to be applied to the product; and
automatically initiating the first logging level to be applied to the product for the determined duration of time.
14. The computer program product of claim 13 , wherein, responsive to the determined duration of time expiring, a second logging level is automatically applied to the product.
15. The computer program product of claim 13 , wherein the analyzing the user activity pertaining to the product further comprises determining inter-arrival times between the electronic messages exchanged between the users.
16. The computer program product of claim 13 , wherein the analyzing the user activity pertaining to the product further comprises determining a relevancy of the trigger statements inferred from the keywords in the electronic messages to at least one log entry.
17. The computer program product of claim 13 , wherein the program code is executable by the data processing system to initiate operations further comprising:
automatically analyzing log entries generated for the product;
wherein the deriving the temporal logging level model further is based on the analyzing the log entries generated for the product.
18. The computer program product of claim 13 , wherein deriving the temporal logging level model comprises:
creating a neural network, the neural network comprising artificial neurons and connections between the artificial neurons, the connections between the artificial neurons assigned variable connection weights that adjust as learning is applied to the neural network; and
deriving the temporal logging level model from the neural network using a temporal logging level model matrix representing data in the electronic messages.