Scaling network functions

A non-transitory computer-readable storage medium comprising a set of computer-readable instructions stored thereon, which, when executed by a processor of a computing system, cause the computing system to perform operations comprising:

• receiving metrics data associated with usage of an instance of a scalable unit of a network function, the metrics indicative of usage characteristics associated with the instance;
• identifying a primary set of the metrics as a primary indicator of occurrence of a load state of the instance;
• determining, based on the received metrics data, usage points where the primary indicator indicates that the load state occurs;
• deriving, from the received metrics data:
• a secondary set of the metrics, different from the primary set, as a secondary indicator of occurrence of the load state of the instance at a group of the usage points where the primary indicator indicates that the load state occurs;
• and
• measured data corresponding to values of the metrics in the secondary set of the metrics at the group of the usage points;
• determining at least one criterion for predicting future values of the secondary set of metrics, based on a current value of the secondary set of the metrics and historical data relating to a pattern of usage of the scalable unit of the network function;
• and
• storing a secondary trigger condition for scaling the scalable unit based on the predicted values of the secondary set and the measured data.

A system configured to determine trigger conditions for scaling a network function of a virtual computing environment, the system comprising a processor and computer-executable instructions that when executed by the processor, cause the system to perform operations comprising:

• receiving metrics data associated with usage of an instance of a scalable unit of the network function, the metrics indicative of usage characteristics associated with the instance;
• identifying a primary set of the metrics as a primary indicator of occurrence of a load state of the instance;
• determining, based on the received metrics data, usage points where the primary indicator indicates that the load state occurs;
• deriving, from the received metrics data:
• a secondary set of the metrics, different from the primary set, as a secondary indicator of occurrence of the load state of the instance at a group of the usage points where the primary indicator indicates that the load state occurs;
• and
• measured data corresponding to values of the metrics in the secondary set of the metrics at the group of the usage points;
• determining at least one criterion for predicting future values of the secondary set of metrics, based on a current value of the secondary set of the metrics and historical data relating to a pattern of usage of the scalable unit of the network function;
• and
• storing a secondary trigger condition for scaling the scalable unit based on the predicted values of the secondary set and the measured data.