Expert guidance for configuring and deploying the OpenTelemetry Collector. Use when setting up a Collector pipeline, configuring receivers, exporters, or processors, deploying a Collector to Kubernetes or Docker, or forwarding telemetry to Dash0. Triggers on requests involving collector, pipeline, O

OpenTelemetry Collector configuration guide Expert guidance for configuring and deploying the OpenTelemetry Collector to receive, process, and export telemetry. Rules Rule Description [receivers](./rules/receivers.md) Receivers — OTLP, Prometheus, filelog, hostmetrics [exporters](./rules/exporters.md) Exporters — OTLP/gRPC to Dash0, debug, authentication [processors](./rules/processors.md) Processors — memory limiter, resource detection, ordering, sending queue [pipelines](./rules/pipelines.md) Pipelines — service section, per signal configuration, connectors [deployment](./rules/deployment.md) Deployment — agent vs gateway patterns, deployment method selection [dash0 operator](./rules/deployment/dash0 operator.md) Dash0 Kubernetes Operator — automated instrumentation, Collector management, Dash0 export [collector helm chart](./rules/deployment/collector helm chart.md) Collector Helm chart — presets, modes, image selection [opentelemetry operator](./rules/deployment/opentelemetry operator.md) OpenTelemetry Operator — Collector CRD, auto instrumentation, sidecar [raw manifests](./rules/deployment/raw manifests.md) Raw Kubernetes manifests — DaemonSet, Deployment, RBAC, Docker Compose [sampling](./rules/sampling.md) Sampling — head, tail, load balancing [red metrics](./rules/red metrics.md) RED metrics — span derived request rate, error rate, duration histograms [custom distributions](./rules/custom distributions.md) Custom distributions — building a stripped down Collector binary with OCB Key principles Processor ordering matters. Place memory limiter first in every pipeline. Enable exporter batching with sending queue: { batch: {} } and persist the queue with file storage instead of using the batch processor. 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 ignores components that no pipeline references, without an error or warning, so an unwired component does nothing. Consistent resource enrichment across pipelines. Apply processors that enrich resource attributes like resource detection and k8s attributes to every signal pipeline (traces, metrics, and logs), not just one. If one pipeline enriches telemetry with k8s.namespace.name or host.name but another does not, correlation between signals is compromised by incomplete metadata. Use canonical component names. Write otlp grpc , otlp http , load balancing , span metrics , log dedup , signal to metrics , k8s attributes , and resource detection as config keys. The older names otlp (exporter only), otlphttp , loadbalancing , spanmetrics , logdedup , signaltometrics , k8sattributes , and resourcedetection still work as deprecated aliases and log a deprecation warning at startup. Run Collector v0.153.0 or later. The configs in this skill need it: load balancing and resource detection exist only from v0.153.0, and sending queue.batch: {} only from v0.138.0. An older Collector rejects them at startup: unknown type for a new name, and for batch: {} either 'sending queue' has invalid keys: batch or batch supports only items or bytes sizer . When you pin an image, pin the version the examples are written against, v0.163.1. Memory safety is non negotiable. Always configure memory limiter in 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. The Collector user must be able to write to the file storage directory; in a container, mount a persistent volume at /var/lib/otelcol . See [exporters](./rules/exporters.md) for full authentication and queue configuration, and [processors](./rules/processors.md) for adding resource detection. Configuration workflow 1. Write config — define receivers, processors, and exporters; wire them in service.pipelines . 2. Validate locally — run otelcol validate config=config.yaml to catch structural errors before deployment. 3. Deploy — choose a deployment method from the [deployment](./rules/deployment.md) rule (Helm, Operator, raw manifests, or Docker Compose). 4. Verify — add the debug exporter 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](./rules/receivers.md) Scrape Prometheus endpoints [receivers](./rules/receivers.md) Collect log files or host metrics [receivers](./rules/receivers.md) Send telemetry to Dash0 [exporters](./rules/exporters.md) Configure retry, queue, or compression [exporters](./rules/exporters.md) Set processor ordering [processors](./rules/processors.md) Add Kubernetes or cloud metadata [processors](./rules/processors.md) Wire receivers → processors → exporters [pipelines](./rules/pipelines.md) Complete working configuration [pipelines](./rules/pipelines.md) Validate the pipeline with the debug exporter [collector helm chart](./rules/deployment/collector helm chart.md), [opentelemetry operator](./rules/deployment/opentelemetry operator.md), [raw manifests](./rules/deployment/raw manifests.md), or [dash0 operator](./rules/deployment/dash0 operator.md) Deploy as DaemonSet or Deployment [raw manifests](./rules/deployment/raw manifests.md) Deploy with Helm [collector helm chart](./rules/deployment/collector helm chart.md) Deploy with the OTel Operator [opentelemetry operator](./rules/deployment/opentelemetry operator.md) Deploy with the Dash0 Operator [dash0 operator](./rules/deployment/dash0 operator.md) Auto instrument applications in Kubernetes [opentelemetry operator](./rules/deployment/opentelemetry operator.md) or [dash0 operator](./rules/deployment/dash0 operator.md) Local development with Docker Compose [raw manifests](./rules/deployment/raw manifests.md) Reduce trace volume [sampling](./rules/sampling.md) Keep errors and slow traces, drop the rest [sampling](./rules/sampling.md) Redact sensitive data in the pipeline [processors](./rules/processors.md sensitive data redaction) Generate RED metrics from traces [red metrics](./rules/red metrics.md) Build a custom Collector binary [custom distributions](./rules/custom distributions.md) Official documentation [OpenTelemetry Collector documentation](https://opentelemetry.io/docs/collector/) [Collector configuration](https://opentelemetry.io/docs/collector/configuration/) [Collector contrib components](https://github.com/open telemetry/opentelemetry collector contrib) [Dash0 Integration Hub](https://www.dash0.com/hub/integrations)

otel-collector