A simple Docker container written in .NET that will receive messages from a Service Bus queue and scale via KEDA.
The message processor will receive a single message at a time (per instance), and sleep for 2 second to simulate performing work. When adding a massive amount of queue messages, KEDA will drive the container to scale out according to the event source (Service Bus Queue).
The sample can also be ran locally on Docker without KEDA, read our documentation here.
This is defined via the ScaledObject which is deployed along with our application.
apiVersion: keda.k8s.io/v1alpha1
kind: ScaledObject
metadata:
name: order-processor-scaler
labels:
app: order-processor
deploymentName: order-processor
spec:
scaleTargetRef:
deploymentName: order-processor
# minReplicaCount: 0 Change to define how many minimum replicas you want
maxReplicaCount: 10
triggers:
- type: azure-servicebus
metadata:
queueName: orders
connection: KEDA_SERVICEBUS_QUEUE_CONNECTIONSTRING
queueLength: '5'It defines the type of scale trigger we'd like to use, in our case azure-servicebus, and the scaling criteria. For our scenario we'd like to scale out if there are 5 or more messages in the orders queue with a maximum of 10 concurrent replicas which is defined via maxReplicaCount.
KEDA will use the KEDA_SERVICEBUS_QUEUE_CONNECTIONSTRING environment variable on our order-processor Kubernetes Deployment to connect to Azure Service Bus. This allows us to avoid duplication of configuration.
Note - If we were to use a sidecar, we would need to define containerName which contains this environment variable.
- Azure CLI
- Azure Subscription
- .NET Core 3.0 Preview 5
- Kubernetes cluster with KEDA installed
This setup will go through creating an Azure Service Bus queue and deploying this consumer with the ScaledObject to scale via KEDA. If you already have an Azure Service Bus namespace you can use your existing queues.
We will start by creating a new Azure Service Bus namespace:
❯ az servicebus namespace create --name <namespace-name> --resource-group <resource-group-name> --sku basic
After that, we create an orders queue in our namespace:
❯ az servicebus queue create --namespace-name <namespace-name> --name orders --resource-group <resource-group-name>
We need to be able to connect to our queue, so we create a new authorization rule with Management permissions which KEDA requires.
❯ az servicebus queue authorization-rule create --resource-group keda-sandbox --namespace-name keda-sandbox --queue-name orders --name order-consumer --rights Manage Send Listen
Once the authorization rule is created, we can list the connection string as following:
❯ az servicebus queue authorization-rule keys list --resource-group keda-sandbox --namespace-name keda-sandbox --queue-name orders --name order-consumer
{
"aliasPrimaryConnectionString": null,
"aliasSecondaryConnectionString": null,
"keyName": "order-consumer",
"primaryConnectionString": "Endpoint=sb://keda.servicebus.windows.net/;SharedAccessKeyName=order-consumer;SharedAccessKey=<redacted>;EntityPath=orders",
"primaryKey": "<redacted>",
"secondaryConnectionString": "Endpoint=sb://keda.servicebus.windows.net/;SharedAccessKeyName=order-consumer;SharedAccessKey=<redacted>;EntityPath=orders",
"secondaryKey": "<redacted>"
}
Create a base64 representation of the connection string and update our Kubernetes secret in deploy/deploy-secret.yaml:
❯ echo "<connection string>" | base64
We will start by creating a new Kubernetes namespace to run our order processor in:
❯ kubectl create namespace keda-dotnet-sample
namespace "keda-dotnet-sample" created
Before we can connect to our queue, we need to create a secret which contains the Service Bus connection string to the queue.
❯ kubectl apply -f deploy/deploy-secret.yaml --namespace keda-dotnet-sample
secret "order-secrets" created
Once created, you should be able to retrieve the secret:
❯ kubectl get secrets --namespace keda-dotnet-sample
NAME TYPE DATA AGE
order-secrets Opaque 1 24s
We are ready to go! Now easily install the order processor along with its ScaledObject:
❯ kubectl apply -f deploy/deploy-queue-processor.yaml --namespace keda-dotnet-sample
deployment.apps "order-processor" created
scaledobject.keda.k8s.io "order-processor-scaler" created
Once created, you will see that our deployment shows up with no pods created:
❯ kubectl get deployments --namespace keda-dotnet-sample -o wide
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
order-processor 0 0 0 0 49s order-processor tomkerkhove/keda-sample-dotnet-worker-servicebus-queue app=order-processor
This is because our queue is empty and KEDA scaled it down until there is work to do.
In that case, let's give generate some!
The following job will send messages to the "orders" queue on which the order processor is listening to. As the queue builds up, KEDA will help the horizontal pod autoscaler add more and more pods until the queue is drained. The order generator will allow you to specify how many messages you want to queue.
First you should clone the project:
❯ git clone https://github.com/tomkerkhove/sample-dotnet-worker-servicebus-queue
❯ cd sample-dotnet-worker-servicebus-queue
Configure the connection string in the tool via your favorite text editor, in this case via Visual Studio Code:
❯ code .\src\Keda.Samples.Dotnet.OrderGenerator\Program.cs
Next, you can run the order generator via the CLI:
❯ dotnet run --project .\src\Keda.Samples.Dotnet.OrderGenerator\Keda.Samples.Dotnet.OrderGenerator.csproj
Let's queue some orders, how many do you want?
300
Queuing order 719a7b19-f1f7-4f46-a543-8da9bfaf843d - A Hat for Reilly Davis
Queuing order 5c3a954c-c356-4cc9-b1d8-e31cd2c04a5a - A Salad for Savanna Rowe
[...]
That's it, see you later!
Now that the messages are generated, you'll see that KEDA starts automatically scaling out your deployment:
❯ kubectl get deployments --namespace keda-dotnet-sample -o wide
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
order-processor 8 8 8 4 4m order-processor tomkerkhove/keda-sample-dotnet-worker-servicebus-queue app=order-processor
Eventually we will have 10 pods running processing messages in parallel:
❯ kubectl get pods --namespace keda-dotnet-sample
NAME READY STATUS RESTARTS AGE
order-processor-65d5dd564-9wbph 1/1 Running 0 54s
order-processor-65d5dd564-czlqb 1/1 Running 0 39s
order-processor-65d5dd564-h2l5l 1/1 Running 0 54s
order-processor-65d5dd564-h6fcl 1/1 Running 0 24s
order-processor-65d5dd564-httnf 1/1 Running 0 1m
order-processor-65d5dd564-j64wq 1/1 Running 0 54s
order-processor-65d5dd564-ncwfd 1/1 Running 0 39s
order-processor-65d5dd564-q7tkt 1/1 Running 0 39s
order-processor-65d5dd564-t2g6x 1/1 Running 0 24s
order-processor-65d5dd564-v79x6 1/1 Running 0 39s
You can look at the logs for a given processor as following:
❯ kubectl logs order-processor-65d5dd564-httnf --namespace keda-dotnet-sample
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Starting message pump at: 06/03/2019 12:32:14 +00:00
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Message pump started at: 06/03/2019 12:32:14 +00:00
info: Microsoft.Hosting.Lifetime[0]
Application started. Press Ctrl+C to shut down.
info: Microsoft.Hosting.Lifetime[0]
Hosting environment: Production
info: Microsoft.Hosting.Lifetime[0]
Content root path: /app
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Received message 513b896fbe3b4085ad274d9c23e01842 with body {"Id":"7ff54254-a370-4697-8115-134e55ebdc65","Amount":1741776525,"ArticleNumber":"Chicken","Customer":{"FirstName":"Myrtis","LastName":"Balistreri"}}
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Processing order 7ff54254-a370-4697-8115-134e55ebdc65 for 1741776525 units of Chicken bought by Myrtis Balistreri at: 06/03/2019 12:32:15 +00:00
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Order 7ff54254-a370-4697-8115-134e55ebdc65 processed at: 06/03/2019 12:32:17 +00:00
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Message 513b896fbe3b4085ad274d9c23e01842 processed at: 06/03/2019 12:32:17 +00:00
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Received message 9d24f13cd5ec44e884efdc9ed4a8842d with body {"Id":"cd9fe9e4-f421-432d-9b19-b94dbf9090f5","Amount":-186606051,"ArticleNumber":"Shoes","Customer":{"FirstName":"Valerie","LastName":"Schaefer"}}
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Processing order cd9fe9e4-f421-432d-9b19-b94dbf9090f5 for -186606051 units of Shoes bought by Valerie Schaefer at: 06/03/2019 12:32:17 +00:00
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Order cd9fe9e4-f421-432d-9b19-b94dbf9090f5 processed at: 06/03/2019 12:32:19 +00:00
info: Keda.Samples.Dotnet.OrderProcessor.OrdersQueueProcessor[0]
Message 9d24f13cd5ec44e884efdc9ed4a8842d processed at: 06/03/2019 12:32:19 +00:00
❯ kubectl delete -f deploy/deploy-queue-processor.yaml --namespace keda-dotnet-sample
❯ kubectl delete -f deploy/deploy-secret.yaml --namespace keda-dotnet-sample
❯ kubectl delete namespace keda-dotnet-sample
❯ az servicebus namespace delete --name <namespace-name> --resource-group <resource-group-name>
❯ helm delete --purge keda
❯ kubectl delete customresourcedefinition scaledobjects.keda.k8s.io
❯ kubectl delete namespace keda