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  • Sensor
  • Sensor
  • Custom Metrics
  • OpenTelemetry Collector
  • Vector
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  1. Architecture

Service endpoints inside the cluster

Last updated 7 months ago

Some of the integrations available in groundcover require finding our services' endpoints. In this section, we list these services and provide instructions on how to find the required configuration.

The endpoints depend on the namespace and release name that were used when installing groundcover. By default, both of these values are groundcover - make sure to adjust them if needed. Need help? Contact us !

Sensor

Sensor

The DaemonSet which is responsible for most of the data collection inside a k8s cluster is called sensor. It exposes several ingestion endpoints:

  • DataDog Traces

  • OpenTelemetry Traces & Logs

  • Zipkin Traces

Ingesting the above using Sensor is the preferred method, if possible, as it allows groundcover to enrich the ingested data with relevant Kubernetes metadata.

Finding the endpoint

<release_name>-sensor.<namespace>.svc.cluster.local

// For default installation values:
groundcover-sensor.groundcover.svc.cluster.local

Custom Metrics

Custom Metrics is a deployment which is responsible for and also serves as an endpoint for pushing metrics, for example

Finding the endpoint

<release_name>-custom-metrics.<namespace>.svc.cluster.local

// For default installation values:
groundcover-custom-metrics.groundcover.svc.cluster.local

OpenTelemetry Collector

Depending on your installation type, follow the instructions below

Finding the endpoint

<release_name>-opentelemetry-collector.<namespace>.svc.cluster.local

// For default installation values:
groundcover-opentelemetry-collector.groundcover.svc.cluster.local

Vector

Finding the endpoint

<release_name>-vector.<namespace>.svc.cluster.local

// For default installation values:
groundcover-vector.groundcover.svc.cluster.local

groundcover includes an out-of-the-box, enabling integration with every receiver, processor and exporter supported by the Open Telemetry stack.

groundcover uses as a key component in the ingestion pipeline. In addition, it's used for supporting several integrations such as .

on slack
VMAgent
scraping custom metrics
in the OTLP format.
open telemetry collector
Vector
DogStatsD ingestion