Detecting cloud service latency issues through analysis of tenant latency signals

A system comprising:

• a processing system;
• and
• a computer-readable medium storing instructions that, when executed by the processing system, cause the system to perform operations comprising:
• generating a tenant-specific model for a latency signal by analyzing a training dataset for a tenant over a training time period, wherein:
• the training dataset includes respective percentile latency values, per a defined time bin, for each percentile in a defined set of percentiles;
• the respective latency values are associated with a service offered by a cloud provider;
• the tenant-specific model defines a distribution based on a mean and a standard deviation of the respective percentile latency values for each percentile in the defined set of percentiles;
• accessing current percentile latency values associated with the tenant for a current time bin, wherein the current percentile latency values are respectively associated with percentiles in the defined set of percentiles;
• generating a latency health score vector for the tenant and for the current time bin by determining percentile health scores for each percentile in the defined set of percentiles via a comparison of a current percentile latency value to the distribution;
• calculating an overall latency health score based on a plurality of latency health scores in the latency health score vector;
• determining that the overall latency health score is less than a latency health score threshold;
• in response to determining that the overall latency health score is less than the latency health score threshold, designating the tenant as an unhealthy tenant due to abnormal latency;
• determining that a total number of unhealthy tenants for the current time bin is greater than a predefined threshold number of unhealthy tenants;
• and
• sending, to an owner of the service and based on the total number of unhealthy tenants being greater than the predefined threshold number of unhealthy tenants, a notification indicating a potential latency issue associated with the service.

A non-transitory computer-readable storage medium storing instructions that, when executed by a processing system, cause a system to perform operations comprising:

• generating a tenant-specific model for a latency signal by analyzing a training dataset for a tenant over a training time period, wherein:
• the training dataset includes respective percentile latency values, per a defined time bin, for each percentile in a defined set of percentiles;
• the respective latency values are associated with a service offered by a cloud provider;
• the tenant-specific model defines a distribution based on a mean and a standard deviation of the respective percentile latency values for each percentile in the defined set of percentiles;
• accessing current percentile latency values associated with the tenant for a current time bin, wherein the current percentile latency values are respectively associated with percentiles in the defined set of percentiles;
• generating a latency health score vector for the tenant and for the current time bin by determining percentile health scores for each percentile in the defined set of percentiles via a comparison of a current percentile latency value to the distribution;
• calculating an overall latency health score based on a plurality of latency health scores in the latency health score vector;
• determining that the overall latency health score is less than a latency health score threshold;
• in response to determining that the overall latency health score is less than the latency health score threshold, designating the tenant as an unhealthy tenant due to abnormal latency;
• determining that a total number of unhealthy tenants for the current time bin is greater than a predefined threshold number of unhealthy tenants;
• and
• sending, to an owner of the service and based on the total number of unhealthy tenants being greater than the predefined threshold number of unhealthy tenants, a notification indicating a potential latency issue associated with the service.