# Copyright 2022 The Knative Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: v1
kind: ConfigMap
metadata:
  name: config-kafka-source-defaults
  namespace: knative-eventing
  labels:
    kafka.eventing.knative.dev/release: devel
  annotations:
    knative.dev/example-checksum: "b6ed351d"
data:
  _example: |
    ################################
    #                              #
    #    EXAMPLE CONFIGURATION     #
    #                              #
    ################################

    # This block is not actually functional configuration,
    # but serves to illustrate the available configuration
    # options and document them in a way that is accessible
    # to users that `kubectl edit` this config map.
    #
    # These sample configuration options may be copied out of
    # this example block and unindented to be in the data block
    # to actually change the configuration.

    # autoscalingClass is the autoscaler class name to use.
    # valid value: keda.autoscaling.knative.dev
    # autoscalingClass: ""

    # minScale is the minimum number of replicas to scale down to.
    # minScale: "1"

    # maxScale is the maximum number of replicas to scale up to.
    # maxScale: "1"

    # pollingInterval is the interval in seconds KEDA uses to poll metrics.
    # pollingInterval: "30"

    # cooldownPeriod is the period of time in seconds KEDA waits until it scales down.
    # cooldownPeriod: "300"

    # kafkaLagThreshold is the lag (ie. number of messages in a partition) threshold for KEDA to scale up sources.
    # kafkaLagThreshold: "10"
