All logic related to obtaining DRA objects and tracking modifications
to ResourceClaims in-memory is extracted to DefaultDRAManager, which
implements framework.SharedDRAManager.
This is intended to be a no-op in terms of the DRA plugin behavior.
Using the "normal" logic for a feature gated field simplifies the
implementation of the feature gate.
There is one (entirely theoretic!) problem with updating from 1.31: if a claim
was allocated in 1.31 with admin access, the status field was not set because
it didn't exist yet. If a driver now follows the current definition of "unset =
off", then it will not grant admin access even though it should. This is
theoretic because drivers are starting to support admin access with 1.32, so
there shouldn't be any claim where this problem could occur.
Drivers need to know that because admin access may also grant additional
permissions. The allocator needs to ignore such results when determining which
devices are considered as allocated.
In both cases it is conceptually cleaner to not rely on the content of the
ClaimSpec.
This removes the DRAControlPlaneController feature gate, the fields controlled
by it (claim.spec.controller, claim.status.deallocationRequested,
claim.status.allocation.controller, class.spec.suitableNodes), the
PodSchedulingContext type, and all code related to the feature.
The feature gets removed because there is no path towards beta and GA and DRA
with "structured parameters" should be able to replace it.
Having a dedicated ActionType which only gets used when the scheduler itself
already detects some change in the list of generated ResourceClaims of a pod
avoids calling the DRA plugin for unrelated Pod changes.
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.
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.
The claim parameter key didn't include the namespace of the claim. In the case
where two namespaces used the exact same parameter reference, the "too many
generated parameters" case got triggered incorrectly and lookup could have
returned an object from the wrong namespace.
Found while running the E2E tests in parallel:
message: 'running PreFilter plugin "DynamicResources": multiple generated claim
parameters for ConfigMap. dra-8794/parameters-3 found: [dra-4729/parameters-4
dra-7328/parameters-4 dra-8794/parameters-4 dra-3402/parameters-4 dra-6156/parameters-4
dra-1839/parameters-4 dra-7434/parameters-4 dra-6504/parameters-4]'
Clearing some irrelevant fields in objects caused a flaky data race alert
because in some cases, the objects were pointers into a shared cache. A better
solution is to treat the objects as read-only and ignore the irrelevant fields.
Coverage was checked with a cover profile. The biggest remaining gap is for
isSchedulableAfterClaimParametersChange and
isSchedulableAfterClassParametersChange which will get handled when refactoring
the
foreachPodResourceClaim (https://github.com/kubernetes/kubernetes/issues/123697).
When a claim uses structured parameters, as indicated by the resource class
flag, the scheduler is responsible for allocating it. To do this it needs to
gather information about available node resources by watching
NodeResourceSlices and then match the in-tree claim parameters against those
resources.
Blocking API calls during a scheduling cycle like the DRA plugin is doing slow
down overall scheduling, i.e. also affecting pods which don't use DRA.
It is easy to move the blocking calls into a goroutine while the scheduling
cycle ends with "pod unschedulable". The hard part is handling an error when
those API calls then fail in the background. There is a solution for that
(see https://github.com/kubernetes/kubernetes/pull/120963), but it's complex.
Instead, publishing the modified PodSchedulingContext can also be done
later. In the more common case of a pod which is ready for binding except for
its claims, that'll be in PreBind, which runs in a separate goroutine already.
In the less common case that a pod cannot be scheduled, that'll be in
Unreserve which is still blocking.
This moves adding a pod to ReservedFor out of the main scheduling cycle into
PreBind. There it is done concurrently in different goroutines. For claims
which were specifically allocated for a pod (the most common case), that
usually makes no difference because the claim is already reserved.
It starts to matter when that pod then cannot be scheduled for other reasons,
because then the claim gets unreserved to allow deallocating it. It also
matters for claims that are created separately and then get used multiple times
by different pods.
Because multiple pods might get added to the same claim rapidly independently
from each other, it makes sense to do all claim status updates via patching:
then it is no longer necessary to have an up-to-date copy of the claim because
the patch operation will succeed if (and only if) the patched claim is valid.
Server-side-apply cannot be used for this because a client always has to send
the full list of all entries that it wants to be set, i.e. it cannot add one
entry unless it knows the full list.
When filtering fails because a ResourceClass is missing, we can treat the pod
as "unschedulable" as long as we then also register a cluster event that wakes
up the pod. This is more efficient than periodically retrying.
This is a combination of two related enhancements:
- By implementing a PreEnqueue check, the initial pod scheduling
attempt for a pod with a claim template gets avoided when the claim
does not exist yet.
- By implementing cluster event checks, only those pods get
scheduled for which something changed, and they get scheduled
immediately without delay.
Generating the name avoids all potential name collisions. It's not clear how
much of a problem that was because users can avoid them and the deterministic
names for generic ephemeral volumes have not led to reports from users. But
using generated names is not too hard either.
What makes it relatively easy is that the new pod.status.resourceClaimStatus
map stores the generated name for kubelet and node authorizer, i.e. the
information in the pod is sufficient to determine the name of the
ResourceClaim.
The resource claim controller becomes a bit more complex and now needs
permission to modify the pod status. The new failure scenario of "ResourceClaim
created, updating pod status fails" is handled with the help of a new special
"resource.kubernetes.io/pod-claim-name" annotation that together with the owner
reference identifies exactly for what a ResourceClaim was generated, so
updating the pod status can be retried for existing ResourceClaims.
The transition from deterministic names is handled with a special case for that
recovery code path: a ResourceClaim with no annotation and a name that follows
the Kubernetes <= 1.27 naming pattern is assumed to be generated for that pod
claim and gets added to the pod status.
There's no immediate need for it, but just in case that it may become relevant,
the name of the generated ResourceClaim may also be left unset to record that
no claim was needed. Components processing such a pod can skip whatever they
normally would do for the claim. To ensure that they do and also cover other
cases properly ("no known field is set", "must check ownership"),
resourceclaim.Name gets extended.
The `listAll` function returned a slice where all pointers referred to the same
instance. That instance had the value of the last list entry. As a result, unit
tests only compared that element.
During the reserve phase, the first claim gets reserved in two test
cases. Those two tests must expect that change. That hadn't been noticed before
because that first claim didn't get compared.
The name "PodScheduling" was unusual because in contrast to most other names,
it was impossible to put an article in front of it. Now PodSchedulingContext is
used instead.
