OpenTelemetry Collector configuration guide
Expert guidance for configuring and deploying the OpenTelemetry Collector to receive, process, and export telemetry.
Rules
| Rule | Description |
|---|---|
| receivers | Receivers — OTLP, Prometheus, filelog, hostmetrics |
| exporters | Exporters — OTLP/gRPC to Dash0, debug, authentication |
| processors | Processors — memory limiter, resource detection, ordering, sending queue |
| pipelines | Pipelines — service section, per-signal configuration, connectors |
| deployment | Deployment — agent vs gateway patterns, deployment method selection |
| dash0-operator | Dash0 Kubernetes Operator — automated instrumentation, Collector management, Dash0 export |
| collector-helm-chart | Collector Helm chart — presets, modes, image selection |
| opentelemetry-operator | OpenTelemetry Operator — Collector CRD, auto-instrumentation, sidecar |
| raw-manifests | Raw Kubernetes manifests — DaemonSet, Deployment, RBAC, Docker Compose |
| sampling | Sampling — head, tail, load balancing |
| red-metrics | RED metrics — span-derived request rate, error rate, duration histograms |
| custom-distributions | Custom distributions — building a stripped-down Collector binary with OCB |
Key principles
- Processor ordering matters. Place
memory_limiterfirst in every pipeline. Use the exporter'ssending_queuewithfile_storageinstead of thebatchprocessor. Incorrect ordering causes memory exhaustion or data loss. - One pipeline per signal type. Define separate pipelines for traces, metrics, and logs. Mixing signals in a single pipeline breaks processing and causes runtime errors.
- Every declared component must appear in a pipeline. The Collector rejects configurations that declare receivers, processors, or exporters not referenced by any pipeline.
- Consistent resource enrichment across pipelines. Apply processors that enrich resource attributes like
resourcedetectionandk8sattributesto every signal pipeline (traces, metrics, and logs), not just one. If one pipeline enriches telemetry withk8s.namespace.nameorhost.namebut another does not, correlation between signals is compromised by incomplete metadata. - Memory safety is non-negotiable. Always configure
memory_limiterin production. Without it, a burst of telemetry can cause the Collector to OOM and crash.
Quick start
Minimal working configuration: OTLP receiver → memory limiter → OTLP/gRPC exporter to Dash0.
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
processors:
memory_limiter:
check_interval: 1s
limit_mib: 400
spike_limit_mib: 100
exporters:
otlp:
endpoint: ingress.eu-west-1.aws.dash0.com:4317
headers:
Authorization: "Bearer ${env:DASH0_TOKEN}"
sending_queue:
enabled: true
storage: file_storage
service:
pipelines:
traces:
receivers: [otlp]
processors: [memory_limiter]
exporters: [otlp]
metrics:
receivers: [otlp]
processors: [memory_limiter]
exporters: [otlp]
logs:
receivers: [otlp]
processors: [memory_limiter]
exporters: [otlp]See exporters for full authentication and queue configuration, and processors for adding resource detection.
Configuration workflow
- Write config — define receivers, processors, and exporters; wire them in
service.pipelines. - Validate locally — run
otelcol validate --config=config.yamlto catch structural errors before deployment. - Deploy — choose a deployment method from the deployment rule (Helm, Operator, raw manifests, or Docker Compose).
- Verify — add the
debugexporter to a pipeline temporarily and inspect stdout to confirm telemetry is flowing; then remove it before going to production.
Quick reference
| What do you need? | Rule |
|---|---|
| Accept OTLP telemetry from applications | receivers |
| Scrape Prometheus endpoints | receivers |
| Collect log files or host metrics | receivers |
| Send telemetry to Dash0 | exporters |
| Configure retry, queue, or compression | exporters |
| Set processor ordering | processors |
| Add Kubernetes or cloud metadata | processors |
| Wire receivers → processors → exporters | pipelines |
| Complete working configuration | pipelines |
| Validate the pipeline with the debug exporter | collector-helm-chart, opentelemetry-operator, raw-manifests, or dash0-operator |
| Deploy as DaemonSet or Deployment | raw-manifests |
| Deploy with Helm | collector-helm-chart |
| Deploy with the OTel Operator | opentelemetry-operator |
| Deploy with the Dash0 Operator | dash0-operator |
| Auto-instrument applications in Kubernetes | opentelemetry-operator or dash0-operator |
| Local development with Docker Compose | raw-manifests |
| Reduce trace volume | sampling |
| Keep errors and slow traces, drop the rest | sampling |
| Redact sensitive data in the pipeline | processors |
| Generate RED metrics from traces | red-metrics |
| Build a custom Collector binary | custom-distributions |