Deletion Policy V1.0¶

S1: CLUSTER_DEL_NODES¶

This is the simplest case. A action of CLUSTER_DEL_NODES carries a list of UUIDs for the nodes to be removed from the cluster. The deletion policy steps in before the actual deletion happens so to help determine the following details:

• whether the nodes should be destroyed after being removed from the cluster;
• whether the nodes should be granted a grace period before being destroyed;
• whether the desired_capacity of the cluster in question should be reduced after node removal.

After the policy check, the data field is updated with contents similar to the following example:

{
  "status": "OK",
  "reason": "Candidates generated",
  "deletion": {
     "count": 2,
     "candidates": ["<node-id-1>", "<node-id-2"],
     "destroy_after_deletion": true,
     "grace_period": 0
  }
}

S2: CLUSTER_SCALE_IN without Scaling Policy¶

When the request is about scaling in the target cluster, the Senlin engine expects that the action carries a count key in its inputs. If the count key doesn’t exist, it means the requester has no idea (or he/she doesn’t care) the number of nodes to remove. The decision is left to the scaling policy (if any) or to the Senlin engine.

When there is no scaling policy attached to the cluster, Senlin engine takes the liberty to assume that the expectation is to remove 1 node from the cluster. This is equivalent to the case when count is specified as 1.

The policy then continues evaluate the cluster nodes to select count victim node(s) based on the criteria property of the policy. Finally it updates the action’s data field with the list of node candidates along with other properties, as described in scenario S1.

S3: CLUSTER_SCALE_IN with Scaling Policy¶

If there is a scaling policy attached to the cluster, that policy will yield into the action’s data property some contents similar to the following example:

{
  "deletion": {
     "count": 2
  }
}

The senlin engine will use value from the deletion.count field in the data property as the number of nodes to remove from cluster. It selects victim nodes from the cluster based on the criteria specified and then updates the action’s data property along with other properties, as described in scenario S1.

S4: CLUSTER_RESIZE without Scaling Policy¶

If there is no scaling policy attached to the cluster, the deletion policy won’t be able to find a deletion.count field in the action’s data property. It then checks the inputs property of the action directly and generates a deletion.count field if the request turns out to be a scaling-in operation. If the request is not a scaling-in operation, the policy check aborts immediately.

After having determined the number of nodes to remove, the policy proceeds to select victim nodes based on its criteria property value. Finally it updates the action’s data field with the list of node candidates along with other properties, as described in scenario S1.

S5: CLUSTER_RESIZE with Scaling Policy¶

In the case there is already a scaling policy attached to the cluster, the scaling policy will be evaluated before the deletion policy, so the policy works in the same way as described in scenario S3.

S6: Deletion across Multiple Availability Zones¶

When you have a zone placement policy attached to a cluster, the zone placement policy will decide in which availability zone(s) new nodes will be placed and from which availability zone(s) old nodes should be deleted to maintain an expected node distribution. Such a zone placement policy will be evaluated before this deletion policy, according to its builtin priority value.

When scaling in a cluster, a zone placement policy yields a decision into the action’s data property that looks like:

{
  "deletion": {
     "count": 3,
     "zones": {
         "AZ-1": 2,
         "AZ-2": 1
     }
  }
}

The above data indicate how many nodes should be deleted globally and how many nodes should be removed from each availability zone. The deletion policy then evaluates nodes from each availability zone to select specified number of nodes as candidates. This selection process is also based on the criteria property of the deletion policy.

After the evaluation, the deletion policy completes by modifying the data property to something like:

{
  "status": "OK",
  "reason": "Candidates generated",
  "deletion": {
     "count": 3,
     "candidates": ["node-id-1", "node-id-2", "node-id-3"]
     "destroy_after_deletion": true,
     "grace_period": 0
  }
}

In the deletion.candidates list, two of the nodes are from availability zone AZ-1, one of the nodes is from availability zone AZ-2.

S6: Deletion across Multiple Regions¶

When you have a region placement policy attached to a cluster, the region placement policy will decide to which region(s) new nodes will be placed and from which region(s) old nodes should be deleted to maintain an expected node distribution. Such a region placement policy will be evaluated before this deletion policy, according to its builtin priority value.

When scaling in a cluster, a region placement policy yields a decision into the action’s data property that looks like:

{
  "deletion": {
     "count": 3,
     "region": {
         "R-1": 2,
         "R-2": 1
     }
  }
}

The above data indicate how many nodes should be deleted globally and how many nodes should be removed from each region. The deletion policy then evaluates nodes from each region to select specified number of nodes as candidates. This selection process is also based on the criteria property of the deletion policy.

After the evaluation, the deletion policy completes by modifying the data property to something like:

{
  "status": "OK",
  "reason": "Candidates generated",
  "deletion": {
     "count": 3,
     "candidates": ["node-id-1", "node-id-2", "node-id-3"]
     "destroy_after_deletion": true,
     "grace_period": 0
  }
}

In the deletion.candidates list, two of the nodes are from region R-1, one of the nodes is from region R-2.