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Knative Serving provides automatic scaling, or autoscaling, for applications to match incoming demand. For example, if an application is receiving no traffic, and scale-to-zero is enabled, Knative Serving scales the application down to zero replicas. If scale-to-zero is disabled, the application is scaled down to the minimum number of replicas configured for applications on the cluster. Replicas can also be scaled up to meet demand if traffic to the application increases.

Autoscaling settings for Knative services can be global settings that are configured by cluster or dedicated administrators, or per-revision settings that are configured for individual services.

You can modify per-revision settings for your services by using the Red Hat OpenShift Service on AWS web console, by modifying the YAML file for your service, or by using the Knative (kn) CLI.

Any limits or targets that you set for a service are measured against a single instance of your application. For example, setting the target annotation to 50 configures the autoscaler to scale the application so that each revision handles 50 requests at a time.

Scale bounds

Scale bounds determine the minimum and maximum numbers of replicas that can serve an application at any given time. You can set scale bounds for an application to help prevent cold starts or control computing costs.

Minimum scale bounds

The minimum number of replicas that can serve an application is determined by the min-scale annotation. If scale to zero is not enabled, the min-scale value defaults to 1.

The min-scale value defaults to 0 replicas if the following conditions are met:

  • The min-scale annotation is not set

  • Scaling to zero is enabled

  • The class KPA is used

Example service spec with min-scale annotation
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: example-service
  namespace: default
spec:
  template:
    metadata:
      annotations:
        autoscaling.knative.dev/min-scale: "0"
...

Setting the min-scale annotation by using the Knative CLI

Using the Knative (kn) CLI to set the min-scale annotation provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn service command with the --scale-min flag to create or modify the min-scale value for a service.

Prerequisites
  • Knative Serving is installed on the cluster.

  • You have installed the Knative (kn) CLI.

Procedure
  • Set the minimum number of replicas for the service by using the --scale-min flag:

    $ kn service create <service_name> --image <image_uri> --scale-min <integer>
    Example command
    $ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --scale-min 2

Maximum scale bounds

The maximum number of replicas that can serve an application is determined by the max-scale annotation. If the max-scale annotation is not set, there is no upper limit for the number of replicas created.

Example service spec with max-scale annotation
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: example-service
  namespace: default
spec:
  template:
    metadata:
      annotations:
        autoscaling.knative.dev/max-scale: "10"
...

Setting the max-scale annotation by using the Knative CLI

Using the Knative (kn) CLI to set the max-scale annotation provides a more streamlined and intuitive user interface over modifying YAML files directly. You can use the kn service command with the --scale-max flag to create or modify the max-scale value for a service.

Prerequisites
  • Knative Serving is installed on the cluster.

  • You have installed the Knative (kn) CLI.

Procedure
  • Set the maximum number of replicas for the service by using the --scale-max flag:

    $ kn service create <service_name> --image <image_uri> --scale-max <integer>
    Example command
    $ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --scale-max 10

Concurrency

Concurrency determines the number of simultaneous requests that can be processed by each replica of an application at any given time. Concurrency can be configured as a soft limit or a hard limit:

  • A soft limit is a targeted requests limit, rather than a strictly enforced bound. For example, if there is a sudden burst of traffic, the soft limit target can be exceeded.

  • A hard limit is a strictly enforced upper bound requests limit. If concurrency reaches the hard limit, surplus requests are buffered and must wait until there is enough free capacity to execute the requests.

    Using a hard limit configuration is only recommended if there is a clear use case for it with your application. Having a low, hard limit specified may have a negative impact on the throughput and latency of an application, and might cause cold starts.

Adding a soft target and a hard limit means that the autoscaler targets the soft target number of concurrent requests, but imposes a hard limit of the hard limit value for the maximum number of requests.

If the hard limit value is less than the soft limit value, the soft limit value is tuned down, because there is no need to target more requests than the number that can actually be handled.

Configuring a soft concurrency target

A soft limit is a targeted requests limit, rather than a strictly enforced bound. For example, if there is a sudden burst of traffic, the soft limit target can be exceeded. You can specify a soft concurrency target for your Knative service by setting the autoscaling.knative.dev/target annotation in the spec, or by using the kn service command with the correct flags.

Procedure
  • Optional: Set the autoscaling.knative.dev/target annotation for your Knative service in the spec of the Service custom resource:

    Example service spec
    apiVersion: serving.knative.dev/v1
    kind: Service
    metadata:
      name: example-service
      namespace: default
    spec:
      template:
        metadata:
          annotations:
            autoscaling.knative.dev/target: "200"
  • Optional: Use the kn service command to specify the --concurrency-target flag:

    $ kn service create <service_name> --image <image_uri> --concurrency-target <integer>
    Example command to create a service with a concurrency target of 50 requests
    $ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --concurrency-target 50

Configuring a hard concurrency limit

A hard concurrency limit is a strictly enforced upper bound requests limit. If concurrency reaches the hard limit, surplus requests are buffered and must wait until there is enough free capacity to execute the requests. You can specify a hard concurrency limit for your Knative service by modifying the containerConcurrency spec, or by using the kn service command with the correct flags.

Procedure
  • Optional: Set the containerConcurrency spec for your Knative service in the spec of the Service custom resource:

    Example service spec
    apiVersion: serving.knative.dev/v1
    kind: Service
    metadata:
      name: example-service
      namespace: default
    spec:
      template:
        spec:
          containerConcurrency: 50

    The default value is 0, which means that there is no limit on the number of simultaneous requests that are permitted to flow into one replica of the service at a time.

    A value greater than 0 specifies the exact number of requests that are permitted to flow into one replica of the service at a time. This example would enable a hard concurrency limit of 50 requests.

  • Optional: Use the kn service command to specify the --concurrency-limit flag:

    $ kn service create <service_name> --image <image_uri> --concurrency-limit <integer>
    Example command to create a service with a concurrency limit of 50 requests
    $ kn service create example-service --image quay.io/openshift-knative/knative-eventing-sources-event-display:latest --concurrency-limit 50

Concurrency target utilization

This value specifies the percentage of the concurrency limit that is actually targeted by the autoscaler. This is also known as specifying the hotness at which a replica runs, which enables the autoscaler to scale up before the defined hard limit is reached.

For example, if the containerConcurrency value is set to 10, and the target-utilization-percentage value is set to 70 percent, the autoscaler creates a new replica when the average number of concurrent requests across all existing replicas reaches 7. Requests numbered 7 to 10 are still sent to the existing replicas, but additional replicas are started in anticipation of being required after the containerConcurrency value is reached.

Example service configured using the target-utilization-percentage annotation
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: example-service
  namespace: default
spec:
  template:
    metadata:
      annotations:
        autoscaling.knative.dev/target-utilization-percentage: "70"
...