The pod template is embedded inside the deployment. So if
the pod annotation contains instance-id, the deployment
will get updated and thus triggers a rolling update whenever
a new executor starts which is unwanted.
After this PR, poolmanager will patches instance-id when a
pod is chosen for a function.
For newdeploy, unlike poolmanager manages the lifecycle
of function pod directly, newdeploy is only responsible
to create the deployment so we append instance-id to top-
level controller (deployment) only.
Previously, once the executor is deleted for reasons (like upgrade or cluster scale-in),
the new executor deletes all existing resources created by the old executor and creates
new one. This mechanism becomes a problem when there are requests connecting to the
existing pods. Also in the worst case, the cluster may not have enough resources to create
new pods and cause service downtime.
This PR let each executor type adopts existing resources before starting the executor
API services, and so the alive connections won't experience failure. However, the requests
send to the function that doesn't have alive function pods will still fail due to the
executor is in bootstrapping.
The pool manager keeps terminating function pod periodically even there are
traffic to the function. The root cause is that executor, poolmgr, newdeploy
manage their own functionServiceCache separately. And when router taps a
function, executor updates the access time of the function service entry in its
own cache without notifying executor types to do the update as well. Hence,
the access time of function service entry in poolmanager cache never gets updated.
Due to the access time never gets updated, the idle pod reaper in poolmanager
then thinks the function pod is in idle state and recycle it.
This PR removes the cache in executor itself, and when router tries to tap a function,
executor will call executor type to tap the function and update access time.
* Config and secret change to invoke function update
* Added recycle function for pool manager as well - where it recycles the specialized pods
* Switched to rolling update of pods and env variable based change instead of deleting pods in new deploy executor
