And maybe the webhook authorizer cache.
This cache has two primary advantages over the LRU cache used currently:
- Cache hits don't acquire an exclusive lock.
- More importantly, performance doesn't fallover when the access pattern
scans a key space larger than an arbitrary size (e.g. the LRU
capacity).
The downside of using an expiring cache here is that it doesn't have a
maximum size so it's suspectible to DoS when the input is user
controlled. This is not the case for successful authentications, and
successful authentications have a natural expiry so it might be a good
fit here.
It has some a few differences compared to:
3d7318f29d/staging/src/k8s.io/client-go/tools/cache/expiration_cache.go
- Expiration is not entirely lazy so keys that are never accessed again
are still released from the cache.
- It does not acquire an exclusive lock on cache hits.
- It supports per entry ttls specified on Set.
The expiring cache (without striping) does somewhere in between the
simple cache and striped cache in the very contrived contention test
where every iteration acquires a write lock:
```
$ benchstat simple.log expiring.log
name old time/op new time/op delta
Cache-12 2.74µs ± 2% 2.02µs ± 3% -26.37% (p=0.000 n=9+9)
name old alloc/op new alloc/op delta
Cache-12 182B ± 0% 107B ± 4% -41.21% (p=0.000 n=8+9)
name old allocs/op new allocs/op delta
Cache-12 5.00 ± 0% 2.00 ± 0% -60.00% (p=0.000 n=10+10)
$ benchstat striped.log expiring.log
name old time/op new time/op delta
Cache-12 1.58µs ± 5% 2.02µs ± 3% +27.34% (p=0.000 n=10+9)
name old alloc/op new alloc/op delta
Cache-12 288B ± 0% 107B ± 4% -62.85% (p=0.000 n=10+9)
name old allocs/op new allocs/op delta
Cache-12 9.00 ± 0% 2.00 ± 0% -77.78% (p=0.000 n=10+10)
$ benchstat simple.log striped.log expiring.log
name \ time/op simple.log striped.log expiring.log
Cache-12 2.74µs ± 2% 1.58µs ± 5% 2.02µs ± 3%
name \ alloc/op simple.log striped.log expiring.log
Cache-12 182B ± 0% 288B ± 0% 107B ± 4%
name \ allocs/op simple.log striped.log expiring.log
Cache-12 5.00 ± 0% 9.00 ± 0% 2.00 ± 0%
```
I also naively replacemed the LRU cache with the expiring cache in the
more realisitc CachedTokenAuthenticator benchmarks:
https://gist.github.com/mikedanese/41192b6eb62106c0758a4f4885bdad53
For token counts that fit in the LRU, expiring cache does better because
it does not require acquiring an exclusive lock for cache hits.
For token counts that exceed the size of the LRU, the LRU has a massive
performance drop off. The LRU cache is around 5x slower (with lookups
taking 1 milisecond and throttled to max 40 lookups in flight).
```
$ benchstat before.log after.log
name old time/op new time/op delta
CachedTokenAuthenticator/tokens=100_threads=256-12 3.60µs ±22% 1.08µs ± 4% -69.91% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=500_threads=256-12 3.94µs ±19% 1.20µs ± 3% -69.57% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=2500_threads=256-12 3.07µs ± 6% 1.17µs ± 1% -61.87% (p=0.000 n=9+10)
CachedTokenAuthenticator/tokens=12500_threads=256-12 3.16µs ±17% 1.38µs ± 1% -56.23% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=62500_threads=256-12 15.0µs ± 1% 2.9µs ± 3% -80.71% (p=0.000 n=10+10)
name old alloc/op new alloc/op delta
CachedTokenAuthenticator/tokens=100_threads=256-12 337B ± 1% 300B ± 0% -11.06% (p=0.000 n=10+8)
CachedTokenAuthenticator/tokens=500_threads=256-12 307B ± 1% 304B ± 0% -0.96% (p=0.000 n=9+10)
CachedTokenAuthenticator/tokens=2500_threads=256-12 337B ± 1% 304B ± 0% -9.79% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=12500_threads=256-12 343B ± 1% 276B ± 0% -19.58% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=62500_threads=256-12 493B ± 0% 334B ± 0% -32.12% (p=0.000 n=10+10)
name old allocs/op new allocs/op delta
CachedTokenAuthenticator/tokens=100_threads=256-12 13.0 ± 0% 11.0 ± 0% -15.38% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=500_threads=256-12 12.0 ± 0% 11.0 ± 0% -8.33% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=2500_threads=256-12 13.0 ± 0% 11.0 ± 0% -15.38% (p=0.000 n=10+10)
CachedTokenAuthenticator/tokens=12500_threads=256-12 13.0 ± 0% 10.0 ± 0% -23.08% (p=0.000 n=9+10)
CachedTokenAuthenticator/tokens=62500_threads=256-12 17.0 ± 0% 12.0 ± 0% -29.41% (p=0.000 n=10+10)
```
Benchmarked with changes in #84423
Bugs: #83259 #83375
Kubernetes

Kubernetes is an open source system for managing containerized applications across multiple hosts. It provides basic mechanisms for deployment, maintenance, and scaling of applications.
Kubernetes builds upon a decade and a half of experience at Google running production workloads at scale using a system called Borg, combined with best-of-breed ideas and practices from the community.
Kubernetes is hosted by the Cloud Native Computing Foundation (CNCF). If your company wants to help shape the evolution of technologies that are container-packaged, dynamically scheduled, and microservices-oriented, consider joining the CNCF. For details about who's involved and how Kubernetes plays a role, read the CNCF announcement.
To start using Kubernetes
See our documentation on kubernetes.io.
Try our interactive tutorial.
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Use of the k8s.io/kubernetes
module or k8s.io/kubernetes/...
packages as libraries is not supported.
To start developing Kubernetes
The community repository hosts all information about building Kubernetes from source, how to contribute code and documentation, who to contact about what, etc.
If you want to build Kubernetes right away there are two options:
You have a working Go environment.
mkdir -p $GOPATH/src/k8s.io
cd $GOPATH/src/k8s.io
git clone https://github.com/kubernetes/kubernetes
cd kubernetes
make
You have a working Docker environment.
git clone https://github.com/kubernetes/kubernetes
cd kubernetes
make quick-release
For the full story, head over to the developer's documentation.
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If you need support, start with the troubleshooting guide, and work your way through the process that we've outlined.
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