CARBON-AWARE PREDICTIVE WORKLOAD SCHEDULING AND SCALING
Example techniques and devices are described for scheduling workloads. An example computing device is configured to predict an occurrence of a scale event for a first service. The computing device is configured to determine, based on the predicted occurrence of the scale event for the first service, a predicted level of greenness for the first service, the predicted level of greenness being based on a current level of greenness for the first service and a predicted scale up factor. The computing device is configured to determine whether the predicted level of greenness for the first service satisfies a first threshold. The computing device is configured to perform, based on whether the predicted level of greenness for the first service satisfies the first threshold, a first action on a first workload of the first service.
1 . A computing device comprising:
one or more memories;
one or more processors communicatively coupled to the one or more memories, the one or more processors being configured to:
predict an occurrence of a scale event for a first service;
determine, based on the predicted occurrence of the scale event for the first service, a predicted level of greenness for the first service, the predicted level of greenness being based on a current level of greenness for the first service and a predicted scale up factor;
determine whether the predicted level of greenness for the first service satisfies a first threshold; and
perform, based on whether the predicted level of greenness for the first service satisfies the first threshold, a first action on a first workload of the first service.
2 . The computing device of claim 1 , wherein the predicted level of greenness for the first service satisfies the first threshold, and wherein the first action comprises rescheduling the first workload to a non-green node.
3 . The computing device of claim 1 , wherein the predicted level of greenness for the first service does not satisfy the first threshold, and wherein the first action comprises rescheduling the first workload to a green node.
4 . The computing device of claim 1 , wherein to predict the occurrence of the scale event for the first service, the one or more processors are configured to execute a machine learning model.
5 . The computing device of claim 1 , wherein to predict the occurrence of the scale event for the first service, the one or more processors are configured to:
predict a workload replica count for the first service; and
determine that the predicted workload replica count for the first service is higher than a current workload replica count for the first service.
6 . The computing device of claim 5 , wherein the predicted scale up factor is based on the predicted workload replica count for the first service and the current workload replica count for the first service.
7 . The computing device of claim 1 , wherein the first threshold is based on a service level agreement requirement applicable to the first service.
8 . The computing device of claim 1 , wherein the one or more processors are further configured to:
predict an absence of a scale event for a second service;
determine, based on the predicted absence of the scale event for the second service, a current level of greenness of the second service;
determine whether the current level of greenness satisfies a second threshold; and
perform, based on whether the current level of greenness satisfies the second threshold, a second action on a second workload of the second service.
9 . The computing device of claim 8 , wherein the current level of greenness satisfies the second threshold, and wherein the second action comprises rescheduling the second workload to a non-green node.
10 . The computing device of claim 8 , wherein the current level of greenness does not satisfy the second threshold, and wherein the second action comprises allowing the second workload to continue to run on a current node.
11 . The computing device of claim 1 , wherein the one or more processors are further configured to:
predict an occurrence of a scale event for a second service;
determine, based on the predicted occurrence of the scale event for the second service, a predicted level of greenness for the second service, the predicted level of greenness for the second service being based on a current level of greenness for the second service and a predicted scale up factor for the second service;
compare, the predicted level of greenness for the first service to the predicted level of greenness for the second service; and
assign a first priority to the first service and a second priority to the second service for use in scaling based on the comparison.
12 . The computing device of claim 11 , wherein the first priority is lower than the second priority, and wherein the one or more processors are further configured to reserve, based on the first priority and the second priority, one or more non-green or less-green resources for one or more replicas of the first service.
13 . The computing device of claim 11 , wherein the first priority is lower than the second priority, and wherein the one or more processors are further configured to move the first workload to non-green or less-green resources and reserve vacated green resources for one or more replicas of a second workload of the second service.
14 . A method comprising:
predicting, by one or more processors, an occurrence of a scale event for a first service;
determining, by the one or more processors and based on the predicted occurrence of the scale event for the first service, a predicted level of greenness for the first service, the predicted level of greenness being based on a current level of greenness for the first service and a predicted scale up factor;
determining, by the one or more processors, whether the predicted level of greenness for the first service satisfies a first threshold; and
performing, by the one or more processors and based on whether the predicted level of greenness for the first service satisfies the first threshold, a first action on a first workload of the first service.
15 . The method of claim 14 , wherein the predicted level of greenness for the first service satisfies the first threshold, and wherein the first action comprises rescheduling the first workload to a non-green node.
16 . The method of claim 14 , wherein the predicted level of greenness for the first service does not satisfy the first threshold, and wherein the first action comprises rescheduling the first workload to a green node.
17 . The method of claim 14 , wherein predicting the occurrence of the scale event for the first service comprises:
predicting a workload replica count for the first service; and
determining that the predicted workload replica count for the first service is higher than a current workload replica count for the first service.
18 . The method of claim 17 , wherein the predicted scale up factor is based on the predicted workload replica count for the first service and the current workload replica count for the first service.
19 . The method of claim 14 , further comprising:
predicting, by the one or more processors, the absence of a scale event for a second service;
determining, by the one or more processors and based on the predicted absence of the scale event for the second service, a current level of greenness of the second service;
determining, by the one or more processors, whether the current level of greenness satisfies a second threshold; and
performing, by the one or more processors and based on whether the current level of greenness satisfies the second threshold, a second action on a second workload of the second service.
20 . Non-transitory computer-readable media, storing instructions which, when executed, cause one or more processors to:
predict an occurrence of a scale event for a first service;
determine, based on the predicted occurrence of the scale event for the first service, a predicted level of greenness for the first service, the predicted level of greenness being based on a current level of greenness for the first service and a predicted scale up factor;
determine whether the predicted level of greenness for the first service satisfies a first threshold; and
perform, based on whether the predicted level of greenness for the first service satisfies the first threshold, a first action on a first workload of the first service.