Create a cluster":
kind create clusterInstall Dapr:
helm repo add dapr https://dapr.github.io/helm-charts/
helm repo update
helm upgrade --install dapr dapr/dapr \
--version=1.16.0 \
--namespace dapr-system \
--create-namespace \
--waitInstall Kafka (replace for pulsar)
helm install kafka oci://registry-1.docker.io/bitnamicharts/kafka --version 22.1.5 --set "provisioning.topics[0].name=events-topic" --set "provisioning.topics[0].partitions=1" --set "persistence.size=1Gi" --set "image.repository=bitnamilegacy/kafka"We will be using OpenTelemetry for collecting telemetry. This demo has support for a couple of different exports, e.g. jaeger tracing or dash0.
Let's start by installing Jaeger into our cluster:
helm repo add jaegertracing https://jaegertracing.github.io/helm-charts
helm repo update
helm install jaeger jaegertracing/jaeger -f jaeger/values.yaml --version 3.4.1Verify that Jaeger is running:
kubectl port-forward svc/jaeger-query 16686Go to localhost:16686 and you should see Jaeger running.
Next, we create a new namespace for the opentelemetry services:
kubectl create namespace opentelemetryNext, install the OpenTelemetry Collector:
helm install otel-collector open-telemetry/opentelemetry-collector \
--namespace opentelemetry \
-f collector/config.yamlOnce installed, install the OpenTelemetry Operator:
helm repo add open-telemetry https://open-telemetry.github.io/opentelemetry-helm-charts
helm upgrade --install opentelemetry-operator open-telemetry/opentelemetry-operator --namespace opentelemetryWe can now start to configure, how our auto-instrumentation should work by applying the Instrumentation resource:
kubectl apply -f instrumentation/instrumentation.yamlhelm install redis bitnami/redis --namespace dapr-tests --set global.redis.password=Daprio7p --set master.disableCommands=nullkubectl apply -f k8s/Port Forward to send requests:
kubectl port-forward svc/app-publisher-svc 8080:80send the following request:
curl -X POST localhost:8080/send/hello