AUTOMATIC SCALING OF COMPUTING RESOURCES USING AGGREGATED METRICS

摘要

A computing resource monitoring service receives a plurality of measurements for a metric associated with an auto-scale group. Each measurement is associated with metadata for the measurement, which specifies attributes for the measurement. The computing resource monitoring service determines, for each measurement and based at least in part on the metadata, a fully qualified metric identifier for the measurement. The service partitions the plurality of measurements into a plurality of logical partitions associated with one or more in-memory datastores. The service transmits the measurements from the plurality of logical partitions to the one or more datastores for storage of the measurements. These measurements are provided to one or more computing resource managers for the auto-scale group to enable automatic scaling of computing resources of the group based at least in part on the measurements.

主权项

1. A computer-implemented method, comprising:
under the control of one or more computer systems configured with executable instructions,
receiving, from one or more load balancers for one or more virtual machine instances of an auto-scale group, a plurality of measurements for a metric including metadata specifying attributes of measurements of the plurality of measurements;utilizing a hash function and the metadata to generate a fully qualified metric identifier for the measurements;partitioning the measurements based at least in part on the fully qualified metric identifier and a timestamp for the measurements, resulting in a plurality of logical partitions;transmitting the plurality of measurements from the plurality of logical partitions to one or more aggregator sub-systems for storage within one or more datastores of the one or more aggregator sub-systems;obtaining, at one or more instance managers for the one or more virtual machine instances, the measurements from the one or more datastores; andperforming automatic scaling of the auto-scale group based at least in part on the obtained measurements by at least changing a number of virtual machine instances in the auto-scale group.