Microsoft patents AI tool that adjusts data logging based on service health

1. A method comprising: accessing historical data values in a dataset associated with a service; accessing text-based information describing at least one of normal content or abnormal content in the dataset associated with the service; providing the historical data values in the dataset associated with the service and the text-based information to one or more artificial intelligence agents, wherein the one or more artificial intelligence agents are tuned to: interpret service owner requirements based on the text-based information; recognize data patterns in the historical data values in the dataset associated with the service; determine, based on the service owner requirements, one or more data value thresholds useable to detect the abnormal content in the dataset associated with the service, wherein the one or more data value thresholds adjust based on the patterns recognized in the historical data values in the dataset associated with the service; define sampling rates in accordance with normal content and abnormal content; and generate program code useable to monitor current data values in the dataset associated with the service, to determine if any one of the current data values violates the one or more data value thresholds, and to adjust the sampling rates in accordance with the normal content and the abnormal content; receiving, from the one or more artificial intelligence agents, the program code useable to monitor the current data values in the dataset associated with the service and to determine any of the current data values violates the one or more data value thresholds; monitoring, via execution of the program code, the current data values in the dataset associated with the service; sampling, via execution of the program code, a first group of the current data values in the dataset associated with the service at a first rate in response to the monitoring indicating normal content in the dataset associated with the service, wherein the normal content is indicated by each current data value in the first group of the current values not violating the one or more data value thresholds; logging, via execution of the program code, sampled data values from the first group of the current data values in a sampling cache that is made available to issue identification and mitigation components deployed for the service; sampling, via execution of the program code, a second group of the current data values in the dataset associated with the service at a second rate in response to the monitoring indicating abnormal content in the dataset associated with the service, wherein the abnormal content is indicated by a current data value in the second group of the current values violating the one or more data value thresholds and the second rate is greater than the first rate; and logging, via execution of the program code, sampled data values from the second group of the current data values in the sampling cache made available to the issue identification and mitigation components deployed for the service.