In the API, the effect of the feature gate is that alpha fields get dropped on
create. They get preserved during updates if already set. The
PodSchedulingContext registration is *not* restricted by the feature gate.
This enables deleting stale PodSchedulingContext objects after disabling
the feature gate.
The scheduler checks the new feature gate before setting up an informer for
PodSchedulingContext objects and when deciding whether it can schedule a
pod. If any claim depends on a control plane controller, the scheduler bails
out, leading to:
Status: Pending
...
Warning FailedScheduling 73s default-scheduler 0/1 nodes are available: resourceclaim depends on disabled DRAControlPlaneController feature. no new claims to deallocate, preemption: 0/1 nodes are available: 1 Preemption is not helpful for scheduling.
The rest of the changes prepare for testing the new feature separately from
"structured parameters". The goal is to have base "dra" jobs which just enable
and test those, then "classic-dra" jobs which add DRAControlPlaneController.
The structured parameter allocation logic was written from scratch in
staging/src/k8s.io/dynamic-resource-allocation/structured where it might be
useful for out-of-tree components.
Besides the new features (amount, admin access) and API it now supports
backtracking when the initial device selection doesn't lead to a complete
allocation of all claims.
Co-authored-by: Ed Bartosh <eduard.bartosh@intel.com>
Co-authored-by: John Belamaric <jbelamaric@google.com>
This is a complete revamp of the original API. Some of the key
differences:
- refocused on structured parameters and allocating devices
- support for constraints across devices
- support for allocating "all" or a fixed amount
of similar devices in a single request
- no class for ResourceClaims, instead individual
device requests are associated with a mandatory
DeviceClass
For the sake of simplicity, optional basic types (ints, strings) where the null
value is the default are represented as values in the API types. This makes Go
code simpler because it doesn't have to check for nil (consumers) and values
can be set directly (producers). The effect is that in protobuf, these fields
always get encoded because `opt` only has an effect for pointers.
The roundtrip test data for v1.29.0 and v1.30.0 changes because of the new
"request" field. This is considered acceptable because the entire `claims`
field in the pod spec is still alpha.
The implementation is complete enough to bring up the apiserver.
Adapting other components follows.
As agreed in https://github.com/kubernetes/enhancements/pull/4709, immediate
allocation is one of those features which can be removed because it makes no
sense for structured parameters and the justification for classic DRA is weak.
This is in preparation for revamping the resource.k8s.io completely. Because
there will be no support for transitioning from v1alpha2 to v1alpha3, the
roundtrip test data for that API in 1.29 and 1.30 gets removed.
Repeating the version in the import name of the API packages is not really
required. It was done for a while to support simpler grepping for usage of
alpha APIs, but there are better ways for that now. So during this transition,
"resourceapi" gets used instead of "resourcev1alpha3" and the version gets
dropped from informer and lister imports. The advantage is that the next bump
to v1beta1 will affect fewer source code lines.
Only source code where the version really matters (like API registration)
retains the versioned import.
This makes the API nicer:
resourceClaims:
- name: with-template
resourceClaimTemplateName: test-inline-claim-template
- name: with-claim
resourceClaimName: test-shared-claim
Previously, this was:
resourceClaims:
- name: with-template
source:
resourceClaimTemplateName: test-inline-claim-template
- name: with-claim
source:
resourceClaimName: test-shared-claim
A more long-term benefit is that other, future alternatives
might not make sense under the "source" umbrella.
This is a breaking change. It's justified because DRA is still
alpha and will have several other API breaks in 1.31.
The JSON patch approach works, but it is complex. A retry loop is easier to
understand (detect conflict, get new claim, try again). There is one additional
API call (the get), but in practice this scenario is unlikely.
There was a race caused by having to update claim finalizer and status in two
different operations:
- Resource claim controller removes allocation, does not yet
get to remove the finalizer.
- Scheduler prepares an allocation, without adding the finalizer
because it's there.
- Controller removes finalizer.
- Scheduler adds allocation.
This is an invalid state. Automatic checking found this during the execution of
the "with translated parameters on single node.*supports sharing a claim
sequentially" E2E test, but only when run stand-alone. When running in
parallel (as in the CI), the bad outcome of the race did not occur.
The fix is to check that the finalizer is still set when adding the
allocation. The apiserver doesn't check that because it doesn't know which
finalizer goes with the allocation result. It could check for "some finalizer",
but that is not guaranteed to be correct (could be some unrelated one).
Checking the finalizer can only be done with a JSON patch. Despite the
complications, having the ability to add multiple pods concurrently to
ReservedFor seems worth it (avoids expensive rescheduling or a local retry
loop).
The resource claim controller doesn't need this, it can do a normal update
which implicitly checks ResourceVersion.
This finishes the transition to the assume cache as source of truth for the
current set of claims.
The tests have to be adapted. It's not enough anymore to directly put objects
into the informer store because that doesn't change the assume cache
content. Instead, normal Create/Update calls and waiting for the cache update
are needed.
This enables connecting the event handler for ResourceClaim to the assume
cache, which addresses a theoretic race condition.
It may also be useful for implementing the autoscaler support, because now
the autoscaler can modify the content of the cache.
