Introduction

Through the latest OpenTelemetry integration, you can seamlessly incorporate telemetry data types such as logs into OpsRamp, ingest these data streams directly from the pre‑configured OpenTelemetry collector, and enable comprehensive monitoring and analysis within your operational environment.

To get started with the OpenTelemetry Integration:

Instrument your application using the OpenTelemetry SDK.

Configure the OpenTelemetry Collector

Modify your config.yaml file for the OpenTelemetry Collector to include the OpsRamp OTLP exporter.

Exporter Configuration

Add the OpsRamp OTLP exporter configuration:

exporters:
  otlp/opsramp_logs:
    endpoint: <endpoint>
    headers:
      "tenantId": <tenantId>
      "X-OpsRamp-Token": <Token>
      "source": "OpenTelemetry"
    compression: "gzip"
    tls:
      insecure: false
      insecure_skip_verify: true

Batch Processor Configuration

Enable batch processing to improve data compression and reduce outgoing connections:

processors:
  batch:
    timeout: 1s
    send_batch_size: 1000
    send_batch_max_size: 2000

Optional: Kubernetes Attributes Processor

Add Kubernetes attribute extraction if you’re running in a Kubernetes environment:

k8sattributes:
  extract:
    metadata:
      - k8s.namespace.name
      - k8s.deployment.name
      - k8s.statefulset.name
      - k8s.daemonset.name
      - k8s.cronjob.name
      - k8s.job.name
      - k8s.node.name
      - k8s.pod.name
      - k8s.pod.uid
      - k8s.pod.start_time
  passthrough: false
  pod_association:
    - sources:
        - from: resource_attribute
          name: k8s.pod.ip
    - sources:
        - from: resource_attribute
          name: k8s.pod.uid
    - sources:
        - from: connection

Service Pipeline Configuration

Configure the service block to include the exporter, processor:

service:
  pipelines:
    logs:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp/opsramp_logs]