CLOUD-BASED COMMITMENT BALANCING

1 . A method for optimizing cloud computing resource utilization in a Kubernetes environment, comprising:

allocating different types of cloud resources to different clusters in the Kubernetes environment based on priorities of the clusters, the different types of cloud resources including pre-committed instances and dynamic instances provided by one or more cloud service providers;

tracking utilization of the pre-committed instances by the clusters to determine whether the pre-committed instances are underutilized; and

responsive to determining that the pre-committed instances are underutilized, rebalancing the clusters between the pre-committed instances and the dynamic instances based on the priorities of the clusters, wherein rebalancing the clusters includes migrating at least one cluster from the dynamic instances to underutilized pre-committed instances, thereby releasing at least a portion of previously allocated dynamic instances.

2 . The method of claim 1 , wherein the dynamic instances comprise one or more of on-demand instances and spot instances.

3 . The method of claim 1 , further comprising assigning a priority to each of the clusters, wherein a first cluster with a higher priority is allocated to the pre-committed instances, and a second cluster with a lower priority is allocated to the dynamic instances.

4 . The method of claim 3 , wherein assigning a priority to each of the clusters comprises:

receiving a user input, indicating a priority of a cluster; and

assigning the cluster the priority indicated by the user input.

5 . The method of claim 1 , wherein rebalancing the clusters includes migrating a lower-priority cluster from the dynamic instances to the underutilized pre-committed instances.

6 . The method of claim 1 , further comprising:

responsive to determining to scaling up or scaling down the cluster, rebalancing the clusters between the pre-committed instances and the dynamic instances based on the priorities of the clusters.

7 . The method of claim 6 , wherein automatically scaling down a cluster allocated in the pre-committed instances based on reduced workload demands of the cluster includes:

responsive to determining to scaling down the cluster,

migrating at least one cluster in the dynamic instances to the pre-committed instances.

8 . The method of claim 6 , wherein automatically scaling up a first cluster allocated in the pre-committed instances based on increased workload demands of the cluster comprises:

responsive to determining to scaling up the cluster, migrating a second cluster from the pre-committed instances to dynamic instances to free up compute resource in the pre-committed instances; and

scaling up the cluster in the pre-committed instances.

9 . The method of claim 8 , wherein the first cluster has a higher priority than a priority of the second cluster.

10 . The method of claim 6 , wherein automatically scaling up a cluster allocated in the dynamic instances based on increased workload demands of the cluster comprises:

rebalancing the clusters between the pre-committed instances and dynamic instances by migrating the cluster from the dynamic instances to the underutilized pre-committed instances; and

scaling up the cluster in pre-committed instances.

11 . The method of claim 10 , wherein the cluster has a lower priority than another cluster in the pre-committed instances.

12 . The method of claim 1 , further comprising:

determining to scale up a cluster in the dynamic instances based on increased workload demands of the cluster; and

allocating additional cloud resources from the underutilized pre-committed instances to scaling up the cluster.

13 . A non-transitory computer readable storage medium having instructions encoded thereon that, when executed by one or more processors, cause the one or more processors to perform steps including:

allocating different types of cloud resources to different clusters in a Kubernetes environment based on priorities of the clusters, the different types of cloud resources including pre-committed instances and dynamic instances provided by one or more cloud service providers;

tracking utilization of the pre-committed instances by the clusters to determine whether the pre-committed instances are underutilized; and

responsive to determining that the pre-committed instances are underutilized, rebalancing the clusters between the pre-committed instances and the dynamic instances based on the priorities of the clusters, wherein rebalancing the clusters includes migrating at least one cluster from the dynamic instances to underutilized pre-committed instances, thereby releasing at least a portion of previously allocated dynamic instances.

14 . The non-transitory computer readable storage medium of claim 13 , wherein dynamic instances include on-demand instances and spot instances.

15 . The non-transitory computer readable storage medium of claim 13 , wherein the different clusters are Kubernetes clusters in a Kubernetes environment.

16 . The non-transitory computer readable storage medium of claim 13 , wherein the one or more processors are further caused to:

assign a priority to each of the clusters, wherein a first cluster with a higher priority is allocated to the pre-committed instances, and a second cluster with a lower priority is allocated to dynamic instances.

17 . The non-transitory computer readable storage medium of claim 16 , wherein assigning a priority to each of the clusters comprises:

receiving a user input, indicating a priority of a cluster; and

assigning the cluster the priority indicated by the user input.

18 . The non-transitory computer readable storage medium of claim 13 , wherein rebalancing clusters includes migrating a lower-priority cluster from the dynamic instances to the underutilized pre-committed instances.

19 . The non-transitory computer readable storage medium of claim 18 , wherein the one or more processors are further caused to:

responsive to determining to scaling up or scaling down the cluster, rebalancing the clusters between the pre-committed instances and the dynamic instances based on the priorities of the clusters.

20 . A computing system, comprising:

one or more processors; and

a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by the one or more processors, cause the one or more processors to perform steps including:

allocating different types of cloud resources to different clusters in a Kubernetes environment based on priorities of the clusters, the different types of cloud resources including pre-committed instances and dynamic instances provided by one or more cloud service providers;

tracking utilization of the pre-committed instances by the clusters to determine whether the pre-committed instances are underutilized; and

responsive to determining that the pre-committed instances are underutilized, rebalancing the clusters between the pre-committed instances and the dynamic instances based on the priorities of the clusters, wherein rebalancing the clusters includes migrating at least one cluster from the dynamic instances to underutilized pre-committed instances, thereby releasing at least a portion of previously allocated dynamic instances.