Kubernetes

How to Deploy Jaeger on Vultr Kubernetes Engine

Introduction

Jaeger is a distributed tracing platform used to monitor and troubleshoot a complex microservices environment. Implementing distributed tracing is essential for modern software applications when troubleshooting and tracking performance issues, especially in the micro-services architecture.

Jaeger monitors and analyzes the requests flow between different microservices in distributed systems and helps developers identify bottlenecks, latency issues, and errors within the system.

Jaeger is made up of several components that work together to offer distributed tracing capabilities. Below are the major components responsible for the different aspects of trace collection, storage, and visualization.

  • Agent: Retrieves the incoming trace data, processes it, and forwards the processed version to the appropriate backends
  • Query: Offers a web-based that allows you to search, retrieve, view trace data, and analyze the flow of requests in your applications
  • Collector: Collects incoming traces from the Jaeger agent, runs validations, and sends them to the backend storage

This article explains how you can deploy Jaeger on a Vultr Kubernetes Engine (VKE) cluster. You will set up Jaeger to trace a Golang application within the cluster.

Prerequisites

Before you start:

  • Deploy a Vultr Kubernetes Engine cluster with at least 3 nodes
  • Deploy a Vultr Debian server to use as the management machine
  • Using SSH, access the server
  • Install and Configure Kubectl to access the cluster
  • Install the Helm package manager $ snap install helm --classic

Install the Jaeger Operator

  1. Using Helm, add the Jaeger Tracing repository to your charts $ helm repo add jaegertracing https://jaegertracing.github.io/helm-charts
  2. Update the Helm repository index $ helm repo update
  3. Install Jaeger Operator to your cluster $ helm install jaeger-operator jaegertracing/jaeger-operator --namespace observability --create-namespace --set rbac.clusterRole=trueOutput: NAME: jaeger-operator LAST DEPLOYED: Sun Oct 29 20:11:39 2023 NAMESPACE: observability STATUS: deployed REVISION: 1 TEST SUITE: None NOTES: jaeger-operator is installed. Check the jaeger-operator logs export POD=$(kubectl get pods -l app.kubernetes.io/instance=jaeger-operator -l app.kubernetes.io/name=jaeger-operator --namespace observability --output name) kubectl logs $POD --namespace=observability
  4. Verify the list of installed Helm packages in your VKE cluster $ helm list -AOutput: NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION jaeger-operator observability 1 2023-10-25 14:17:40.390191139 +0530 IST deployed jaeger-operator-2.49.0 1.49.0
  5. Verify that the Jaeger Operator pod is ready and running in your cluster $ kubectl get pod -n observabilityOutput: NAME READY STATUS RESTARTS AGE jaeger-operator-b89c6b9b-9x65d 1/1 Running 0 53m

Deploy the Jaeger All-In-One image

The Jaeger Operator is installed and available in your cluster, but it cannot function without supporting Jaeger resources. Install the Jaeger All-In-One image to deploy the necessary instances to develop and test cluster operations.

  1. Using a text editor such as Nano, create a new jaeger.yml file to define the Jaeger instance $ nano jaeger.yml
  2. Add the following configurations to the file apiVersion: jaegertracing.io/v1 kind: Jaeger metadata: name: jaeger spec: query: serviceType: LoadBalancerSave and close the file
  3. Apply the Jaeger resource to your clusterabove resources to the Kubernetes. $ kubectl apply -f jaeger.yml
  4. Verify that Jaeger is running with an allinone strategy $ kubectl get jaegersOutput: NAME STATUS VERSION STRATEGY STORAGE AGE jaeger Running 1.49.0 allinone memory 8s
  5. Verify the running Jaeger pod name $ kubectl get pods -l app.kubernetes.io/instance=jaegerOutput: NAME READY STATUS RESTARTS AGE jaeger-8b48f49db-tjq6v 1/1 Running 0 55m
  6. View the Jaeger pod logs to verify the background activity $ kubectl logs -l app.kubernetes.io/instance=jaegerOutput: {"level":"info","ts":1697896855.8030396,"caller":"grpc@v1.57.0/clientconn.go:565","msg":"[core][Channel #10] Channel Connectivity change to READY","system":"grpc","grpc_log":true} {"level":"info","ts":1697896855.8032107,"caller":"grpc@v1.57.0/clientconn.go:1301","msg":"[core][Channel #6 SubChannel #8] Subchannel Connectivity change to READY","system":"grpc","grpc_log":true} {"level":"info","ts":1697896855.803359,"caller":"base/balancer.go:177","msg":"[roundrobin]roundrobinPicker: Build called with info: {map[SubConn(id:8):{{Addr: \":14250\", ServerName: \"\", }}]}","system":"grpc","grpc_log":true} {"level":"info","ts":1697896855.8034499,"caller":"grpc@v1.57.0/clientconn.go:565","msg":"[core][Channel #6] Channel Connectivity change to READY","system":"grpc","grpc_log":true} {"level":"info","ts":1697896855.803539,"caller":"grpc/builder.go:124","msg":"Agent collector connection state change","dialTarget":":14250","status":"READY"} {"level":"info","ts":1697896856.7546606,"caller":"grpc@v1.57.0/clientconn.go:1303","msg":"[core][Channel #1 SubChannel #2] Subchannel Connectivity change to IDLE, last error: connection error: desc = \"transport: Error while dialing: dial tcp [::1]:4317: connect: connection refused\"","system":"grpc","grpc_log":true} {"level":"info","ts":1697896856.7552433,"caller":"grpc@v1.57.0/clientconn.go:1301","msg":"[core][Channel #1 SubChannel #2] Subchannel Connectivity change to CONNECTING","system":"grpc","grpc_log":true} {"level":"info","ts":1697896856.7554233,"caller":"grpc@v1.57.0/clientconn.go:1414","msg":"[core][Channel #1 SubChannel #2] Subchannel picks a new address \"localhost:4317\" to connect","system":"grpc","grpc_log":true} {"level":"info","ts":1697896856.7570865,"caller":"grpc@v1.57.0/clientconn.go:1301","msg":"[core][Channel #1 SubChannel #2] Subchannel Connectivity change to READY","system":"grpc","grpc_log":true} {"level":"info","ts":1697896856.7573693,"caller":"grpc@v1.57.0/clientconn.go:565","msg":"[core][Channel #1] Channel Connectivity change to READY","system":"grpc","grpc_log":true}
  7. Verify the list of available Jaeger services $ kubectl get svc -l app=jaegerOutput: NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE jaeger-agent ClusterIP None <none> 5775/UDP,5778/TCP,6831/UDP,6832/UDP,14271/TCP 55m jaeger-collector ClusterIP 10.108.94.104 <none> 9411/TCP,14250/TCP,14267/TCP,14268/TCP,14269/TCP,4317/TCP,4318/TCP 55m jaeger-collector-headless ClusterIP None <none> 9411/TCP,14250/TCP,14267/TCP,14268/TCP,14269/TCP,4317/TCP,4318/TCP 55m jaeger-query LoadBalancer 10.98.215.158 192.0.2.1 16686:32086/TCP,16685:32707/TCP,16687:32697/TCP 55mVerify and copy the Load Balancer public IP address included in the jaeger-query EXTERNAL-IP field.
  8. Using a web browser such as Firefox, load the Jaeger web interface on port 16686 using your external IP address. Replace the example IP 192.0.2.1 with your actual public IP http://192.0.2.1:16686Access the Jaeger web UI

Deploy a Sample Golang Application to Trace

In this section, you will deploy a Golang Application on Kubernetes using an image ovhplatform/what-is-my-pod-with-tracing:1.0.2 hosted on the Docker Hub. This application will send traces to the Jaeger collector for distributed tracing and monitoring.

  1. Create a new deployment YAML file to define the Golang application $ nano deployment.yml
  2. Add the following configurations to the file apiVersion: apps/v1 kind: Deployment metadata: name: tracing-deployment labels: app: tracing-deployment spec: replicas: 3 selector: matchLabels: app: tracing-deployment template: metadata: labels: app: tracing-deployment spec: containers: - name: tracing-deployment image: ovhplatform/what-is-my-pod-with-tracing:1.0.2 ports: - containerPort: 8080 env: - name: MY_POD_NAME valueFrom: fieldRef: fieldPath: metadata.nameSave and close the file.The above configuration creates a new Golang application deployment using the ovhplatform/what-is-my-pod-with-tracing:1.0.2 and the custom pods name MY_POD_NAME. Replace these values with your desired source image and pods name for smooth cluster operations.
  3. Deploy the application to your cluster $ kubectl apply -f deployment.yml
  4. Verify that your Golang application is available and running $ kubectl get pod -l app=tracing-deploymentOutput: NAME READY STATUS RESTARTS AGE tracing-deployment-7f94fffb89-5c2zn 1/1 Running 0 24m tracing-deployment-7f94fffb89-nsx56 1/1 Running 0 24m tracing-deployment-7f94fffb89-wz25d 1/1 Running 0 24m
  5. Create a service manifest to expose the Golang application on port 8080 $ nano service.yml
  6. Add the following configuration to the file. apiVersion: v1 kind: Service metadata: labels: app: tracing-deployment name: tracing-deployment spec: ports: - port: 8080 selector: app: tracing-deployment type: LoadBalancerSave and close the file.
  7. Apply the configuration to your cluster $ kubectl apply -f svc.yml
  8. View the new load balancer IP address assignment to the Golang application $ kubectl get svc -l app=tracing-deploymentOutput: NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE tracing-deployment LoadBalancer 10.96.48.102 192.0.2.2 8080:31733/TCP 24mVerify and keep note of the EXTERNAL-IP value to use when accessing the application.

Visualize Traces using the Jaeger UI

The sample Golang application is deployed to your cluster and able to send traces to Jaeger. Test and visualize all active traces using the Jaeger web interface as described below.

  1. Using Curl, access the Golang application on the service port 8080 using the application’s external IP to start tracing curl http://203.0.113.2:8080When successful, your output should look like the one below: Hello "tracing-deployment-7f94fffb89-nsx56"!
  2. In your web browser session, access the Jaeger web interface again http://192.0.2.1:16686
  3. Navigate to go-what-is-my-pod-with-tracing in the service menu and click the Find Traces button to view the available tracesView trace data
  4. Click any of the traces and visualize useful informationVisualize TracesTo send more traces, access your Golang application again and keep track of the available traces in your Jaeger interface

Conclusion

You have deployed Jaeger on a Vultr Kubernetes Engine (VKE) cluster and set up a sample Golang application to send traces for visualization within the cluster

Introduction Jaeger is a distributed tracing platform used to monitor and troubleshoot a complex microservices environment. Implementing distributed tracing is essential for modern software applications when troubleshooting and tracking performance issues, especially in the micro-services architecture. Jaeger monitors and analyzes the requests flow between different microservices in distributed systems and…

Introduction Jaeger is a distributed tracing platform used to monitor and troubleshoot a complex microservices environment. Implementing distributed tracing is essential for modern software applications when troubleshooting and tracking performance issues, especially in the micro-services architecture. Jaeger monitors and analyzes the requests flow between different microservices in distributed systems and…

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