bakdata / rebalancing-demo Goto Github PK

Create clean Kubernetes Cluster (for example with docker-desktop)

Afterward, install tiller:

helm init

If helm init fails and cannot find the requested resource/tiller please try this instead:

helm init --service-account tiller --output yaml | sed 's@apiVersion: extensions/v1beta1@apiVersion: apps/v1@' | sed 's@  replicas: 1@  replicas: 1\n  selector: {"matchLabels": {"app": "helm", "name": "tiller"}}@' | kubectl apply -f -

You can add the confluent helm charts easily via:

helm repo add confluentinc https://confluentinc.github.io/cp-helm-charts/
helm repo update
helm install confluentinc/cp-helm-charts --name demo

This will create a small Kafka cluster of 3 brokers and other necessary applications like ZooKeeper or the schema registry. This may take a few minutes. Also do not worry if some applications are crashing and restarting at the beginning - The pods are waiting for each other (e.g. brokers are waiting for a running ZooKeeper instance; schema registry is waiting for the brokers).

helm repo add bakdata-common https://raw.githubusercontent.com/bakdata/common-kafka-streams/master/charts/

We use k9s to access the shell of a broker (and more) but you can also connect to the broker via command line:

kubectl exec -it demo-cp-kafka-0 -c cp-kafka-broker -- bash

In the shell you can create or delete topics.
Create:

kafka-topics --bootstrap-server localhost:9092 --create --topic input-topic --partitions 3 --replication-factor 1
kafka-topics --bootstrap-server localhost:9092 --create --topic output-topic --partitions 3 --replication-factor 1

Delete:

kafka-topics --bootstrap-server localhost:9092 --delete --topic input-topic
kafka-topics --bootstrap-server localhost:9092 --delete --topic output-topic

First we need to build our java application with jib:

gradlew jibDockerBuild --info --image=demo-consumer

You can than upload the consumer to your docker registry. If you do not have one you can create one locally. More info here.

docker run -d -p 5000:5000 --restart=always --name registry registry:2
docker tag demo-consumer:latest localhost:5000/demo-consumer
docker push localhost:5000/demo-consumer

Now you can finally deploy the application to our local Kubernetes cluster using the bakdata-common/streams-app helm chart:

helm upgrade --debug --install --recreate-pods --wait --timeout=300 --force --values consumer/values.yaml demo-consumer bakdata-common/streams-app

To deploy the test with static membership we only have to add two values:

helm upgrade --debug --install --recreate-pods --wait --timeout=300 --force --values consumer/values.yaml --set streams.staticMembership=true,streams.config."session\.timeout\.ms"=60000 demo-consumer bakdata-common/streams-app

You can always delete the release via helm delete demo-consumer.

This is nice but does basically nothing because we do not send any data to the stream. So back to our shell connected to the Kafka broker.
Kafka added an application called console-producer that can send data to a topic. This is exactly the apllication we need:

kafka-console-producer --topic input-topic --broker-list localhost:9092

To read messages from the output topic use:

kafka-console-consumer --topic output-topic --bootstrap-server localhost:9092

Now you can write simple text messages to the consumers. There are two special messages:

• crash - crashes the consumer and the pod restarts
• wait - blocks the consumer for 15 minutes

Setup:

• Create topics: input-topic and output-topic
• Start non-static deployment
• Start kafka-console-producer and kafka-console-consumer
• Write random strings into the kafka-console-producer and see if the messages arrive at the kafka-console-consumer. (You will also see them in the logs of the Kubernetes pods)

Test:

• Write wait into the kafka-console-producer. The message blocks one consumer for 15 minutes.
• Spam some random messages to the kafka-console-producer. You should see, that some of them do not arrive in the output topic because they are stuck in the blocked consumer.
• Write crash into the kafka-console-producer. If no pod restarts please wait a few seconds. It could be that the crash message was sent to the blocked consumer.
• Spam some random messages to the kafka-console-producer.

At this point, no messages should arrive at the output because the consumer group is stuck in a rebalance until the blocked consumer finishes processing the wait message.

Setup:

• Delete old helm deployment
• Delete topics: input-topic and output-topic
• Create topics: input-topic and output-topic
• Start static deployment
• Start kafka-console-producer and kafka-console-consumer
• Write random strings into the kafka-console-producer and see if the messages arrive at the kafka-console-consumer. (This may take a minute now - After this minute al messages will arrive immediately)

Test:

• Write wait into the kafka-console-producer. One consumer is now blocked for 15 minutes.
• Spam some random messages to the kafka-console-producer. You should see that some of them do not arrive in the output topic because they are stuck in the blocked consumer.
• Write crash into the kafka-console-producer. If no pod restarts please wait a few seconds. It could be that the crash message was sent to the blocked consumer.
• Spam some random messages to the kafka-console-producer.

Since the consumer group is not rebalancing, the crashing consumer reads the crash message again and again and restarts multiple times. At this point, roughly a third of all messages should arrive in the output topic. One third arrives at the blocked consumer, and the other third arrives at the crash-looping consumer.