Warning
You are currently viewing v"2.6" of the documentation and it is not the latest. For the most recent documentation, kindly click here.
Apache Kafka Click here for latest
Scale applications based on an Apache Kafka topic or other services that support Kafka protocol.
Notice:
By default, the number of replicas will not exceed:
- The number of partitions on a topic when a topic is specified;
- The number of partitions of all topics in the consumer group when no topic is specified;
maxReplicaCount
specified inScaledObject
/ScaledJob
. If not specifed, then the default value ofmaxReplicaCount
is taken into account;That is, if
maxReplicaCount
is set more than number of partitions, the scaler won’t scale up to target maxReplicaCount. SeeallowIdleConsumers
below to disable this default behavior.This is so because if there are more number of consumers than the number of partitions in a topic, then extra consumer will have to sit idle.
This specification describes the kafka
trigger for an Apache Kafka topic.
triggers:
- type: kafka
metadata:
bootstrapServers: kafka.svc:9092
consumerGroup: my-group
topic: test-topic
lagThreshold: '5'
offsetResetPolicy: latest
allowIdleConsumers: false
version: 1.0.0
Parameter list:
bootstrapServers
- Comma separated list of Kafka brokers “hostname:port” to connect to for bootstrap.consumerGroup
- Name of the consumer group used for checking the offset on the topic and processing the related lag.topic
- Name of the topic on which processing the offset lag. (Optional, see note below)lagThreshold
- Average target value to trigger scaling actions. (Default: 5
, Optional)offsetResetPolicy
- The offset reset policy for the consumer. (Values: latest
, earliest
, Default: latest
, Optional)allowIdleConsumers
- When set to true
, the number of replicas can exceed the number of
partitions on a topic, allowing for idle consumers. (Default: false
, Optional)version
- Version of your Kafka brokers. See samara version (Default: 1.0.0
, Optional)Note:
When
topic
is unspecified, total offset lag will be calculated with all topics within the consumer group.
- When there are active consumer instances, all topics includes:
- Topics the consumer is currently subscribing to;
- Topics that the consumer group had prior commit history (up to retention period for
__consumer_offset
, default to 7 days, see KIP-186);- When there are no active consumer instances, all topics only includes topics that the consumer group had prior commit history;
An edge case exists where scaling could be effectively disabled:
- Consumer never makes a commit (no record in
__consumer_offset
);- and
ScaledObject
hadminReplicaCount
as 0;In such case, KEDA could scale the consumer down to 0 when there is no lag and won’t be able scale up due to the topic could not be auto discovered.
Fix for such case:
- Set
minReplicaCount
> 0;- or use multiple triggers where one supplies
topic
to ensure lag for that topic will always be detected;
You can use TriggerAuthentication
CRD to configure the authenticate by providing sasl
, username
and password
, in case your Kafka cluster has SASL authentication turned on. If TLS is required you should set tls
to enable
. If required for your Kafka configuration, you may also provide a ca
, cert
and key
. cert
and key
must be specified together.
Credential based authentication:
SASL:
sasl
- Kafka SASL auth mode. (Values: plaintext
, scram_sha256
or scram_sha512
, none
, Default: none
, Optional)username
- Username used for sasl authentication. (Optional)password
- Password used for sasl authentication. (Optional)TLS:
tls
- To enable SSL auth for Kafka, set this to enable
. If not set, TLS for Kafka is not used. (Values: enable
, disable
, Default: disable
, Optional)ca
- Certificate authority file for TLS client authentication. (Optional)cert
- Certificate for client authentication. (Optional)key
- Key for client authentication. (Optional)When a new Kafka consumer is created, it must determine its consumer group initial position, i.e. the offset it will start to read from. The position is decided in Kafka consumers via a parameter auto.offset.reset
and the possible values to set are latest
(Kafka default), and earliest
. This parameter in KEDA should be set accordingly. In this initial status, no offset has been committed to Kafka for the consumer group and any request for offset metadata will return an INVALID_OFFSET
; so KEDA has to manage the consumer pod’s autoscaling in relation to the offset reset policy that has been specified in the parameters:
earliest
(a new consumer wants to replay everything in the topic from its beginning) and no offset is committed, the scaler will return a lag value equal to the last offset in the topic. In the case of a new topic the last offset will be 0, so it will scale the deployment to 0 replicas. If a new message is produced to the topic, KEDA will return the new value of the offset (1), and will scale the deployments to consume the message.latest
(so the new consumer will only consume new messages) and no offset is committed, the scaler will return a negative lag value, and will also tell the HPA to remain active
, hence the deployment should have the minimum number of replicas running. This is to allow the consumer to read any new message on the topic, and commit its offset.Your kafka cluster no SASL/TLS auth:
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: kafka-scaledobject
namespace: default
spec:
scaleTargetRef:
name: azure-functions-deployment
pollingInterval: 30
triggers:
- type: kafka
metadata:
bootstrapServers: localhost:9092
consumerGroup: my-group # Make sure that this consumer group name is the same one as the one that is consuming topics
topic: test-topic
# Optional
lagThreshold: "50"
offsetResetPolicy: latest
Your kafka cluster turn on SASL/TLS auth:
apiVersion: v1
kind: Secret
metadata:
name: keda-kafka-secrets
namespace: default
data:
sasl: "plaintext"
username: "admin"
password: "admin"
tls: "enable"
ca: <your ca>
cert: <your cert>
key: <your key>
---
apiVersion: keda.sh/v1alpha1
kind: TriggerAuthentication
metadata:
name: keda-trigger-auth-kafka-credential
namespace: default
spec:
secretTargetRef:
- parameter: sasl
name: keda-kafka-secrets
key: sasl
- parameter: username
name: keda-kafka-secrets
key: username
- parameter: password
name: keda-kafka-secrets
key: password
- parameter: tls
name: keda-kafka-secrets
key: tls
- parameter: ca
name: keda-kafka-secrets
key: ca
- parameter: cert
name: keda-kafka-secrets
key: cert
- parameter: key
name: keda-kafka-secrets
key: key
---
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: kafka-scaledobject
namespace: default
spec:
scaleTargetRef:
name: azure-functions-deployment
pollingInterval: 30
triggers:
- type: kafka
metadata:
bootstrapServers: localhost:9092
consumerGroup: my-group # Make sure that this consumer group name is the same one as the one that is consuming topics
topic: test-topic
# Optional
lagThreshold: "50"
offsetResetPolicy: latest
authenticationRef:
name: keda-trigger-auth-kafka-credential