Integration testing has to this point relied on patching serving codecs for built-in APIs. The
test-only patching is removed and replaced by feature gated checks at runtime.
The media type application/cbor describes exactly one encoded item. As a new (to Kubernetes) format
with no existing clients, streaming/watch responses will use the application/cbor-seq media
type. CBOR watch responses conform to the specification of CBOR Sequences and are encoded as the
concatenation of zero or more items with no additional framing.
This is meant to make it easier to remove the v1alpha3 because it won't be used
in clusters that started with DRA as beta in Kubernetes 1.32 when all clients
support v1beta1.
Setting AllAlpha=true in integration tests changes the dynamic client request encoding and the
custom resource storage encoding to CBOR. The etcd storage path is updated to accept either JSON or
CBOR as storage encoding. The client feature gate controlling the dynamic client request encoding is
temporarily disabled until the serving codecs for builtin APIs are wired to the CBOR apiserver
feature gate.
For alpha, there is one apiserver feature gate and two client-go feature gates controlling
CBOR. They were initially wired to separate test-only feature gate instances in order to prevent
them from being configurable at runtime via command-line flags or environment variables (for
client-go feature gates outside of Kubernetes components). All of the integration tests required by
the KEP as alpha criteria have been implemented. This adds the feature gates to the usual feature
gate instances and removes the temporary code to support separate test-only feature gate instances.
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.
A better place is the cel package because a) the name can become shorter
and b) it is tightly coupled with the compiler there.
Moving the compilation into the cache simplifies the callers.
This is closely aligned with ValidatingAdmissionPolicy
except that instead of validations that can fail with
messages, there are mutations, which can be defined
either with as an ApplyConfiguration or JSONPatch.
Co-authored-by: cici37 <cicih@google.com>
If a client is configured to encode request bodies to CBOR, but the server does not support CBOR,
the server will respond with HTTP 415 (Unsupported Media Type). By feeding this response back to the
RESTClient, subsequent requests can fall back to JSON, which is assumed to be acceptable.
DeviceClasses and different requests are very likely to contain the same
expression string. We don't need to compile that over and over again.
To avoid hanging onto that cache longer than necessary, it's currently tied to
each PreFilter/Filter combination. It might make sense to move this up into the
scheduler plugin and thus reuse compiled expressions for different pods.
goos: linux
goarch: amd64
pkg: k8s.io/kubernetes/test/integration/scheduler_perf
cpu: Intel(R) Core(TM) i9-7980XE CPU @ 2.60GHz
│ before │ after │
│ SchedulingThroughput/Average │ SchedulingThroughput/Average vs base │
PerfScheduling/SchedulingWithResourceClaimTemplateStructured/5000pods_500nodes-36 33.95 ± 4% 36.65 ± 2% +7.95% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/empty_100nodes-36 105.8 ± 2% 106.7 ± 3% ~ (p=0.177 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/empty_500nodes-36 100.7 ± 1% 119.7 ± 3% +18.82% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/half_100nodes-36 90.78 ± 1% 121.10 ± 4% +33.40% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/half_500nodes-36 50.51 ± 7% 63.72 ± 3% +26.17% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/full_100nodes-36 103.7 ± 5% 110.2 ± 2% +6.32% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/full_500nodes-36 28.50 ± 2% 28.16 ± 5% ~ (p=0.102 n=6)
geomean 64.99 73.15 +12.56%
Using unique strings instead of normal strings speeds up allocation with
structured parameters because maps that use those strings as key no longer need
to build hashes of the string content. However, care must be taken to call
unique.Make as little as possible because it is costly.
Pre-allocating the map of allocated devices reduces the need to grow the map
when adding devices.
goos: linux
goarch: amd64
pkg: k8s.io/kubernetes/test/integration/scheduler_perf
cpu: Intel(R) Core(TM) i9-7980XE CPU @ 2.60GHz
│ before │ after │
│ SchedulingThroughput/Average │ SchedulingThroughput/Average vs base │
PerfScheduling/SchedulingWithResourceClaimTemplateStructured/5000pods_500nodes-36 18.06 ± 2% 33.30 ± 2% +84.31% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/empty_100nodes-36 104.7 ± 2% 105.3 ± 2% ~ (p=0.818 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/empty_500nodes-36 96.62 ± 1% 100.75 ± 1% +4.28% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/half_100nodes-36 83.00 ± 2% 90.96 ± 2% +9.59% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/half_500nodes-36 32.45 ± 7% 49.84 ± 4% +53.60% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/full_100nodes-36 95.22 ± 7% 103.80 ± 1% +9.00% (p=0.002 n=6)
PerfScheduling/SteadyStateClusterResourceClaimTemplateStructured/full_500nodes-36 9.111 ± 10% 27.215 ± 7% +198.69% (p=0.002 n=6)
geomean 45.86 64.26 +40.12%
