CHT Project Progress Report 10/07 Simon

CHT Project Develop a resource management scheduling algorithm for CHT datacenter. ◦ Two types of jobs, interactive/latency- sensitive and batch/computation-intensive. ◦ Minimize SLA violation with limited resources.  # of servers ◦ Based on Red Hat Openshift

Current Plan Two components ◦ Scheduler  Deploy container/pod to server  Inside Kubernetes ◦ Rule Engine  Decide the number of container/pod for each service.  Output the results in JSON  Input of the scheduler

Scheduler Implement a new scheduler as plug-in and replace the original one. Use the original scheduler, but change the policy. ◦ “Provide a JSON file that specifies the predicates and priority functions to configure the scheduler”. ◦ Change the weight of the (built-in) priority function to meet our score function.

Rule Engine Decide the number of container/pod for each service according to the monitoring data. Add/adjust rules to make better decisions. However, ◦ Rule Engine is another Red Hat product. ◦ Creating and adjusting new rules requires experiences.

Alternative Way Build our own Resource Allocator. ◦ Decides the number of container/pod for each service according to the monitoring data. ◦ Basic rules  Rules about the critical resources such as CPU, memory …etc.

Possible future extension Apply machine learning to add/adjust the rules.(CHT) Apply machine learning to minimize the size of a container/pod.(Prof. Lin)

Next Study the current predicates and priority functions inside Kubernetes. Keep working.