Nodejs Application

4min
This document explains how to instrument the node js application with KloudMate, using OpenTelemetry.
This instrumentation can be done using the OpenTelemetry operator, which supports injecting and configuring auto-instrumentation libraries for .NET, Java, Node.js, Python, and Go service.
Pre-requisites:
Running a Kubernetes cluster.
The cert-manager must be installed. If you use the helm chart, there is an option to generate a self-signed cert instead.
Step 1: First, install the OpenTelemetry Operator into your cluster.
You can do this with the Operator release manifest, the Operator helm chart, or with Operator Hub.
BASH
kubectl apply -f https://github.com/open-telemetry/opentelemetry-operator/releases/latest/download/opentelemetry-operator.yaml  
kubectl apply -f https://github.com/open-telemetry/opentelemetry-operator/releases/latest/download/opentelemetry-operator.yaml  
﻿
Step 2: Create an OpenTelemetry collector to send telemetry from containers to a collector instead of directly to a backend. 
For example, here is a demo collector used 
YAML
kubectl apply -f - <<EOF

apiVersion: opentelemetry.io/v1alpha1
kind: OpenTelemetryCollector
metadata:
  name: demo
  namespace: kloudmate-backend #change namespace
spec:
  config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: 0.0.0.0:4317
          http:
            endpoint: 0.0.0.0:4318
    processors:
      memory_limiter:
        check_interval: 1s
        limit_percentage: 75
        spike_limit_percentage: 15
      batch:
        send_batch_size: 10000
        timeout: 10s

    exporters:
      debug:
      otlphttp:
        endpoint: 'https://otel.kloudmate.com:4318'
        headers:
          Authorization: KLOUDMATE-API-KEY 	

    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [debug, otlphttp]
        metrics:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [debug, otlphttp]
        logs:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [debug, otlphttp]

EOF
kubectl apply -f - <<EOF

apiVersion: opentelemetry.io/v1alpha1
kind: OpenTelemetryCollector
metadata:
  name: demo
  namespace: kloudmate-backend #change namespace
spec:
  config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: 0.0.0.0:4317
          http:
            endpoint: 0.0.0.0:4318
    processors:
      memory_limiter:
        check_interval: 1s
        limit_percentage: 75
        spike_limit_percentage: 15
      batch:
        send_batch_size: 10000
        timeout: 10s

    exporters:
      debug:
      otlphttp:
        endpoint: 'https://otel.kloudmate.com:4318'
        headers:
          Authorization: KLOUDMATE-API-KEY 	

    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [debug, otlphttp]
        metrics:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [debug, otlphttp]
        logs:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [debug, otlphttp]

EOF
﻿
Change your Kloudmate organization API key to configure the collector to export data to Kloudmate.
Step 3: Configure automatic instrumentation
To be able to manage automatic instrumentation, the Operator needs to be configured to know what pods to instrument and which automatic instrumentation to use for those pods. This is done via the Instrumentation CRD﻿
For our example, we used node js SDK auto instrumentation.
The following command creates a basic Instrumentation resource that is configured for instrumenting Node.js services.
YAML
kubectl apply -f - <<EOF
apiVersion: opentelemetry.io/v1alpha1
kind: Instrumentation
metadata:
  name: demo-instrumentation
  namespace: kloudmate-backend  #change namespace
spec:
  exporter:
    endpoint: http://demo-collector:4317
  propagators:
    - tracecontext
    - baggage
  sampler:
    type: parentbased_traceidratio
    argument: "1"
EOF
kubectl apply -f - <<EOF
apiVersion: opentelemetry.io/v1alpha1
kind: Instrumentation
metadata:
  name: demo-instrumentation
  namespace: kloudmate-backend  #change namespace
spec:
  exporter:
    endpoint: http://demo-collector:4317
  propagators:
    - tracecontext
    - baggage
  sampler:
    type: parentbased_traceidratio
    argument: "1"
EOF
﻿
The endpoint used under exporter must be the same as the service name of the collector created in Step 2.
Step 4:
Now to opt in your services to automatic instrumentation. This is done by updating your service’s spec.template.metadata.annotations to include a language-specific annotation 
Node.js:instrumentation.opentelemetry.io/inject-nodejs:﻿ "true"﻿
To patch your existing node js application with the necessary annotation use the below command
BASH
kubectl  patch deployment otlp-http-deployment -n kloudmate-backend -p '{"spec":{"template":{"metadata":{"annotations":{"instrumentation.opentelemetry.io/inject-nodejs": "true"}}}}}'    
kubectl  patch deployment otlp-http-deployment -n kloudmate-backend -p '{"spec":{"template":{"metadata":{"annotations":{"instrumentation.opentelemetry.io/inject-nodejs": "true"}}}}}'    
﻿
Following the above steps, you can get the necessary telemetry data on KloudMate.
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