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Autoscale Sample

A demonstration of the autoscaling capabilities of a Knative Serving Revision.

Prerequisites

  1. A Kubernetes cluster with Knative Serving installed.

  2. A metrics installation for viewing scaling graphs (optional).

  3. Install Docker.

  4. Clone this repository, and move into the sample directory:

    git clone https://github.com/knative/docs knative-docs
cd knative-docs

Deploy the Service

  1. Deploy the sample Knative Service:

    kubectl apply --filename serving/samples/autoscale-go/service.yaml

  2. Find the ingress hostname and IP and export as an environment variable:

    export IP_ADDRESS=`kubectl get svc knative-ingressgateway --namespace istio-system --output jsonpath="{.status.loadBalancer.ingress[*].ip}"`

View the Autoscaling Capabilities

  1. Make a request to the autoscale app to see it consume some resources.

    curl --header "Host: autoscale-go.default.example.com" "http://${IP_ADDRESS?}?sleep=100&prime=10000&bloat=5"

    Allocated 5 Mb of memory.
The largest prime less than 10000 is 9973.
Slept for 100.13 milliseconds.

  2. Ramp up traffic to maintain 10 in-flight requests.

    docker run --rm -i -t --entrypoint /load-generator -e IP_ADDRESS="${IP_ADDRESS}" \
  gcr.io/knative-samples/autoscale-go:0.1 \
  -sleep 100 -prime 10000 -bloat 5 -qps 9999 -concurrency 300

    REQUEST STATS:
Total: 439      Inflight: 299   Done: 439       Success Rate: 100.00%   Avg Latency: 0.4655 sec
Total: 1151     Inflight: 245   Done: 712       Success Rate: 100.00%   Avg Latency: 0.4178 sec
Total: 1706     Inflight: 300   Done: 555       Success Rate: 100.00%   Avg Latency: 0.4794 sec
Total: 2334     Inflight: 264   Done: 628       Success Rate: 100.00%   Avg Latency: 0.5207 sec
Total: 2911     Inflight: 300   Done: 577       Success Rate: 100.00%   Avg Latency: 0.4401 sec
...

    Note: Use CTRL+C to exit the load test.

  3. Watch the Knative Serving deployment pod count increase.

    kubectl get deploy --watch

    Note: Use CTRL+C to exit watch mode.

Analysis

Algorithm

Knative Serving autoscaling is based on the average number of in-flight requests per pod (concurrency). The system has a default target concurrency of 100.0.

For example, if a Revision is receiving 350 requests per second, each of which takes about .5 seconds, Knative Serving will determine the Revision needs about 2 pods

350 * .5 = 175
175 / 100 = 1.75
ceil(1.75) = 2 pods

Tuning

By default Knative Serving does not limit concurrency in Revision containers. A limit can be set per-Configuration using the ContainerConcurrency field. The autoscaler will target a percentage of ContainerConcurrency instead of the default 100.0.

Dashboards

View the Knative Serving Scaling and Request dashboards (if configured).

kubectl port-forward --namespace knative-monitoring $(kubectl get pods --namespace knative-monitoring --selector=app=grafana --output=jsonpath="{.items..metadata.name}") 3000

scale dashboard

request dashboard

Other Experiments

  1. Maintain 1000 concurrent requests.

    docker run --rm -i -t --entrypoint /load-generator -e IP_ADDRESS="${IP_ADDRESS}" \
  gcr.io/knative-samples/autoscale-go:0.1 \
  -qps 9999 -concurrency 1000

  2. Maintain 100 qps with fast requests.

    docker run --rm -i -t --entrypoint /load-generator -e IP_ADDRESS="${IP_ADDRESS}" \
  gcr.io/knative-samples/autoscale-go:0.1 \
  -qps 100 -concurrency 9999

  3. Maintain 100 qps with slow requests.

    docker run --rm -i -t --entrypoint /load-generator -e IP_ADDRESS="${IP_ADDRESS}" \
  gcr.io/knative-samples/autoscale-go:0.1 \
  -qps 100 -concurrency 9999 -sleep 500

  4. Heavy CPU usage.

    docker run --rm -i -t --entrypoint /load-generator -e IP_ADDRESS="${IP_ADDRESS}" \
  gcr.io/knative-samples/autoscale-go:0.1 \
  -qps 9999 -concurrency 10 -prime 40000000

  5. Heavy memory usage.

    docker run --rm -i -t --entrypoint /load-generator -e IP_ADDRESS="${IP_ADDRESS}" \
  gcr.io/knative-samples/autoscale-go:0.1 \
  -qps 9999 -concurrency 5 -bloat 1000

Cleanup

kubectl delete --filename serving/samples/autoscale-go/service.yaml

Further reading

  1. Autoscaling Developer Documentation