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public static final String TASKRACK_AWARE_ASSIGNMENT_RACK_AWARENESSTAGS_CONFIG = "taskrack.aware.assignment.rack.awarenesstags";
public static final String TASKRACK_AWARE_ASSIGNMENT_RACK_AWARENESSTAGS_DOC = "List of client tag keys used to distribute standby replicas across Kafka Streams instances." +                                                                
                                                                " When configured, Kafka Streams will make a best-effort to distribute" +
                    											" the standby tasks over each client tag dimension.";

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# Kafka Streams Client 1
client.tag.zone: eu-central-1a
client.tag.cluster: k8s-cluster1
taskrack.aware.assignment.rack.awarenesstags: zone,cluster

# Kafka Streams Client 2
client.tag.zone: eu-central-1b
client.tag.cluster: k8s-cluster1
taskrack.aware.assignment.rack.awarenesstags: zone,cluster

# Kafka Streams Client 3
client.tag.zone: eu-central-1a
client.tag.cluster: k8s-cluster2
taskrack.aware.assignment.rack.awarenesstags: zone,cluster

# Kafka Streams Client 4
client.tag.zone: eu-central-1b
client.tag.cluster: k8s-cluster2
taskrack.aware.assignment.rack.awarenesstags: zone,cluster

When client.tag.* dimensions are configured, Kafka Streams will read this information from the configuration and encode it into SubscriptionInfoData as key-value pairs. SubscriptionInfoData will be bumped to version 10

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ClientTag => Key Value
 
  Version => Int32
   Key     => ShortBytes
   Value   => Bytes

Key of the ClientTag struct will be encoded in a deterministic way based on task.assignment.rack.awareness configuration. For instance, if we have task.assignment.rack.awareness: zone,cluster - zone will be encoded as 0 and cluster as 1.

Kafka Streams's Task Assignor will make a decision on how to distribute standby tasks over the available clients based on encoded clientTags within the subscription info and configured taskrack.aware.assignment.rack.awarenesstags

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Node-1:
client.tag.cluster: K8s_Cluster1
client.tag.zone: eu-central-1a
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-2:
client.tag.cluster: K8s_Cluster1
client.tag.zone: eu-central-1b
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-3:
client.tag.cluster: K8s_Cluster1
client.tag.zone: eu-central-1c
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-4:
client.tag.cluster: K8s_Cluster2
client.tag.zone: eu-central-1a
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-5:
client.tag.cluster: K8s_Cluster2
client.tag.zone: eu-central-1b
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-6:
client.tag.cluster: K8s_Cluster2
client.tag.zone: eu-central-1c
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-7:
client.tag.cluster: K8s_Cluster3
client.tag.zone: eu-central-1a
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-8:
client.tag.cluster: K8s_Cluster3
client.tag.zone: eu-central-1b
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

Node-9:
client.tag.cluster: K8s_Cluster3
client.tag.zone: eu-central-1c
taskrack.aware.assignment.rack.awarenesstags: zone,cluster
num.standby.replicas: 2

...

• The initial idea was to introduce two configurations in StreamsConfig, rack.id, which defines the rack of the Kafka Streams instance and standby.task.assignor - class that implements RackAwareStandbyTaskAssignor interface. 

  The signature of RackAwareStandbyTaskAssignor was the following:

  Code Block
  language java
  public interface RackAwareStandbyTaskAssignor { /** * Computes desired standby task distribution for a different {@link StreamsConfig#RACK_ID_CONFIG}s. * @param sourceTasks - Source {@link TaskId}s with a corresponding rack IDs that are eligible for standby task creation. * @param clientRackIds - Client rack IDs that were received during assignment. * @return - Map of the rack IDs to set of {@link TaskId}s. The return value can be used by {@link TaskAssignor} * implementation to decide if the {@link TaskId} can be assigned to a client that is located in a given rack. */ Map<String, Set<TaskId>> computeStandbyTaskDistribution(final Map<TaskId, String> sourceTasks, final Set<String> clientRackIds); }

  By injecting custom implementation of RackAwareStandbyTaskAssignor interface, users could hint Kafka Streams where to allocate certain standby tasks when more complex processing logic was required — for example, parsing rack.id, which can be a combination of multiple identifiers (as seen in the previous examples where we have cluster and zone tags).

  The above mentioned idea was abandoned because it's easier and more user-friendly to let users control standby task allocation with just configuration options instead of forcing them to implement a custom interface. 
  
  

  Defining multiple client.tag with combination of taskrack.aware.assignment.rack.awarenesstags gives more flexibility, which, as already mentioned above, could have been only possible with pluggable custom logic Kafka Streams's user must provide.

  For instance, if we append multiple tags to form a single rack, it may not give desired distribution to the user if the infrastructure topology is more complex. Let us consider the following example with appending multiple tags to form the single rack.

  
  

  Code Block

  Node-1: rack.id: K8s_Cluster1-eu-central-1a num.standby.replicas: 1 Node-2: rack.id: K8s_Cluster1-eu-central-1b num.standby.replicas: 1 Node-3: rack.id: K8s_Cluster1-eu-central-1c num.standby.replicas: 1 Node-4: rack.id: K8s_Cluster2-eu-central-1a num.standby.replicas: 1 Node-5: rack.id: K8s_Cluster2-eu-central-1b num.standby.replicas: 1 Node-6: rack.id: K8s_Cluster2-eu-central-1c num.standby.replicas: 1

  
  

  In the example mentioned above, we have three AZs and two Kubernetes clusters. Our use-case is to distribute standby task in the different Kubernetes cluster and different availability zone. For instance, if the active task is in Node-1 (K8s_Cluster1-eu-central-1a), the corresponding standby task should be in either on Node-5 (K8s_Cluster2-eu-central-1b) or on Node-6 (K8s_Cluster2-eu-central-1c).

  Unfortunately, without custom logic provided by the user, this would be very hard to achieve with a single rack.id configuration. Because without any input from the user, Kafka Streams might as well allocate standby task for the active task either:

  • In the same Kubernetes cluster and different AZ (Node-2, Node-3)
  • In the different Kubernetes cluster but the same AZ (Node-4)

  On the other hand, with the combination of the new "client.tag.*" and "taskrack.aware.assignment.rack.awarenesstags" configurations, standby task distribution algorithm will be able to figure out what will be the most optimal distribution by balancing the standby tasks over each client.tag dimension individually. And it can be achieved by simply providing necessary configurations to Kafka Streams.

  
  

• The second approach was to refactor TaskAssignor interface to be more user-friendly and expose it as a public interface. Users then could implement custom TaskAssignor logic and set it via StreamsConfig. With this, Kafka Streams users would effectively be in control of Active and Standby task allocation.
  Similarly to the point above, this approach also was rejected because it's more complex.
  Even though it's more-or-less agreed on the pluggable TaskAssignor interface's usefulness, it was decided to cut it out of this KIP's scope and prepare a separate one for that feature.

...