1. Keeping the description consistent - Memory not RAM when referring to
overcommit
2. getters And setters grouped, provided right casing.
3. Removed wildcard imports
Signed-off-by: Prasanna Santhanam <tsp@apache.org>
- Changes merged from planner_reserve branch
- Exposing deploymentplanner as an optional parameter while creating a service offering
- changes to DeploymentPlanningManagerImpl to make sure host reserve-release happens between conflicting planner usages.
Adding the zone, cluster, account level parameters
The parameters at scope (zone/cluster/pool/account) can be updated by updateConfiguration API with additional parameter zoneid/clusterid/accountid/storagepoolid
Whenever these scoped parameters are used in CS they get value from the corresponding details table if not defined get value from global parameter.
Same with the listConfiguration API with additional parameter zoneid/clusterid/accountid/storagepoolid
Changes:
- Use of class variable of type GenericSearchBuilder causes issues when multiple threads invoke this method to findCapacity
- Changing the scope of the variable to be local to these methods.
Changes:
- Added a two new deployment planners 'UserDispersingPlanner' and 'UserConcentratedPodPlanner' to the DeploymentPlanners
- Planner can be chosen by setting the global config variable 'vm.allocation.algorithm' to either of the following values:
('random', 'firstfit', 'userdispersing', 'userconcentratedpod')
- By default, the value is 'random'. When the value is 'random', FirstFitPlanner is invoked as before that shuffles the resource lists.
- Now Admin can choose whether the deployment heuristic should be applied starting at cluster or pod level. This can be done by using the
global config variable 'apply.allocation.algorithm.to.pods' which is false by default. Thus by default as earlier, planner starts at clusters directly.
'UserConcentratedPodPlanner' changes:
- Earlier to 3.0, FirstFitPlanner used to reorder the clusters in case this heuristic was chosen.
- Now this is done by a separate planner and is applied only when 'vm.allocation.algorithm' is set to this planner
- It reorders the capacity based clusters/pods such that those pods having more number of Running Vms for the given account are tried first.
- Note that this userconcentration is applied only to pods and clusters. Not to hosts or storagepools within a cluster.
'UserDispersingPlanner' changes:
- 'UserDispersingPlanner' reorders the capacity ordered pods and clusters based on number of 'Running' VMs for the given account in ascending order. Aim is to choose thodes pods/clusters first which have less number of Running VMs for the given account
- Admin can provide weights to capacity and user dispersion so that both parameters get considered in reordering the pods/clusters. This can be done by setting
the global config parameter 'vm.user.dispersion.weight'. Default value is 1. Thus if this planner is chosen, by default, ordering will be done only by number of Running Vms, unless the weight is changed.
- HostAlllocators and StoragePoolAllocators also reorder the hosts and pools by ascending order of number of Running VMS/ Ready Volumes respectively for the given account. Thus try to choose that host or pool within a cluster with less number of VMs for the account.
Wei Zhou
Min Chen
Prasanna Santhanam
Edison Su
Prachi Damle
Kishan Kavala
Mice Xia
Nitin Mehta
Alex Huang
Harikrishna Patnala
Edison Su
Bharat Kumar
Kelven Yang
Alex Huang
Mice Xia
Chip Childers
Alena Prokharchyk
David Nalley
frank
Nitin