Sending OpenTelemetry to ClickHouse Observability with Odigos

TL;DRThis guide shows you how to export Odigos telemetry to ClickHouse Observability. You’ll learn how to:

Deploy Odigos on Kubernetes with Helm
Add sources in the Odigos UI
Add an OTLP HTTP destination pointed at ClickHouse Observability
Verify logs, metrics, and traces in ClickHouse Observability

Odigos auto-instruments applications without code changes or restarts; ClickHouse Observability stores and queries the data in ClickHouse.Time required: 10–20 minutes

What is Odigos?

Odigos is an instrumentation control plane for Kubernetes and VMs that instruments applications from the kernel using eBPF. Because collection runs in the kernel, app overhead stays low while visibility stays high. You get production-grade OpenTelemetry traces, metrics, logs, and profiles without shipping new agents in application code or waiting on library upgrades across every service. That eBPF layer is what makes deep, consistent telemetry possible at scale. Odigos can automatically turn on and off deeper instrumentation when needed to help debug or troubleshoot problems:

Code-level context — attributes tied to functions and runtime behavior
HTTP traffic — requests and responses across your services
Messaging systems — payloads and messages from Kafka and similar brokers
Errors in detail — stack traces when things fail
Custom instrumentation — extend coverage where auto-instrumentation stops without requiring code changes or restarts

Behind the scenes, Odigos creates and manages a full OpenTelemetry pipeline for your cluster: collectors that scale with load, routing to the backends you choose, and pipeline logic you control in the UI. Define sampling to manage volume, PII masking to keep sensitive data out of exports, and OTTL rules to filter, transform, or enrich telemetry before it leaves the cluster.

Why Odigos + ClickHouse Observability?

Rolling out OpenTelemetry across many services is often time consuming and only provides surface-level visibility in applications. Odigos handles eBPF instrumentation for deeper telemetry and collector operations on Kubernetes; ClickHouse Observability provides ClickHouse-backed storage and the ClickStack UI for querying telemetry at scale.

Key takeaways

Odigos auto-instruments any Kubernetes workload without requiring restarts and manages OpenTelemetry pipelines automatically.
ClickHouse Observability stores logs, metrics, and traces in ClickHouse and surfaces them in the ClickStack UI.

Prerequisites

A ClickHouse Observability service reachable from your Kubernetes cluster. See Getting started. For self-managed deployments, see Self-managed setup.
Your OTLP HTTP endpoint and ingestion API key from Team Settings → Data → Managed Telemetry. For self-managed deployments, use your standalone collector endpoint and OTLP_AUTH_TOKEN.
A Kubernetes cluster (Linux nodes with kernel 4.18 or later for eBPF instrumentation)
Helm, kubectl, and cluster credentials to install into odigos-system namespace
An Odigos Enterprise on-prem token — contact the Odigos team for access

Integrate ClickHouse Observability with Odigos

Deploy Odigos with Helm

Odigos Enterprise requires an on-prem license token. Export it in your shell:

export ODIGOS_ONPREM_TOKEN="<your-enterprise-token>"

Alternatively, you can store the token in a Kubernetes Secret named odigos-pro before installing. See Odigos Enterprise documentation (requires access).Add the Odigos Helm repository and install the chart into odigos-system:

helm repo add odigos https://odigos-io.github.io/odigos/
helm repo update

helm upgrade --install odigos odigos/odigos \
  --namespace odigos-system \
  --create-namespace \
  --set onPremToken=$ODIGOS_ONPREM_TOKEN

You can pass additional configuration overrides with --set flags or a custom values file (-f). To inspect the chart’s default values, run helm show values odigos/odigos.Verify Odigos pods are running:

kubectl get pods -n odigos-system

Add sources in the Odigos UI

Port-forward the Odigos UI service:

kubectl port-forward svc/ui -n odigos-system 3000:3000

Open http://localhost:3000 in your browser.
Go to Sources and select the namespaces or workloads you want to instrument.
Click done at the bottom, once you have marked all workloads for instrumentation.
Verify workloads have been instrumented successfully in the sources column.

Add ClickHouse Observability as a destination in the Odigos UI

To send telemetry, add an OTLP HTTP destination in Odigos. Select your deployment below.

Fully managed
Self-managed

ClickHouse Observability gives you an OTLP endpoint. ClickHouse handles ingestion, schemas, and compute. Point Odigos at that endpoint. You do not deploy a collector.

In the Odigos UI, click Add Destination and select OTLP HTTP.
Set OTLP HTTP Endpoint to the HTTPS endpoint from ClickHouse Cloud, including port 4318. For example, https://<service-id>.otel.<region>.aws.clickhouse.com:4318.
In Headers, add:
- Key: Authorization
- Value: Bearer <YOUR_INGESTION_API_KEY>
Enable Logs, Metrics, and Traces.
Save the destination.

Alternative: write directly to ClickHouseFor self-managed deployments, you can use Odigos’s native ClickHouse destination instead of running an OTLP collector, provided your ClickHouse service is reachable from your Kubernetes cluster. Fully managed deployments must use the managed OTLP endpoint.

For a self-managed deployment, run the ClickStack distribution of the collector in standalone mode yourself and set the authentication token via the OTLP_AUTH_TOKEN environment variable when starting the container. Odigos then sends OTLP HTTP traffic to that collector with the same token in the Authorization header.

Start the ClickStack collector in standalone mode, pointing it at your ClickHouse Cloud service and securing it with an OTLP_AUTH_TOKEN of your choice:

export CLICKHOUSE_ENDPOINT=<HTTPS_ENDPOINT>
export CLICKHOUSE_USER=<CLICKHOUSE_USER>
export CLICKHOUSE_PASSWORD=<CLICKHOUSE_PASSWORD>
export OTLP_AUTH_TOKEN="a_very_secure_string"

docker run \
  -e OTLP_AUTH_TOKEN=${OTLP_AUTH_TOKEN} \
  -e CLICKHOUSE_ENDPOINT=${CLICKHOUSE_ENDPOINT} \
  -e CLICKHOUSE_USER=${CLICKHOUSE_USER} \
  -e CLICKHOUSE_PASSWORD=${CLICKHOUSE_PASSWORD} \
  -p 4317:4317 \
  -p 4318:4318 \
  clickhouse/clickstack-otel-collector:latest

For TLS, dedicated ingestion users, and other production recommendations, see Securing the collector.

In the Odigos UI, click Add Destination and select OTLP HTTP.
Set OTLP HTTP Endpoint to the standalone collector you just started (for example, http://my-collector.example.com:4318).
In Headers, add:
- Key: Authorization
- Value: the OTLP_AUTH_TOKEN value you set on the collector
Enable Logs, Metrics, and Traces.
Save the destination.

Optional: Kubernetes manifestYou can configure the same destination with a Destination manifest instead of the UI. See Configure destinations with Kubernetes manifests in Advanced configuration.

Verify telemetry in ClickHouse Observability

Open the ClickStack UI:
- Self-managed: open your service in the ClickHouse Cloud console, then click Launch ClickStack. See Navigate to the ClickStack UI for details.
- Fully managed: open the observability view for your ClickHouse Cloud service.
Check Logs, Metrics, and Traces for data from your instrumented services.
Filter traces by odigos.version to validate end-to-end export.

If data is missing, check collector logs: kubectl logs deploy/odigos-gateway -n odigos-system

Advanced configuration

Native ClickHouse destination

The native ClickHouse destination is available only for self-managed deployments. For fully managed deployments, use the OTLP HTTP destination with your managed endpoint.

Self-managed

When ClickHouse is directly reachable from your cluster, you can use Odigos’s native ClickHouse destination instead of OTLP HTTP. Configure the ClickHouse endpoint, database name, and schema options in the UI or with a manifest — see Odigos ClickHouse destination.

Production schema: Set CLICKHOUSE_CREATE_SCHEME to false and apply your own DDL.
TLS / auth: Use CLICKHOUSE_TLS_ENABLED, CLICKHOUSE_USERNAME, and a Kubernetes Secret for the password.

Kubernetes manifest

apiVersion: odigos.io/v1alpha1
kind: Destination
metadata:
  name: clickhouse
  namespace: odigos-system
spec:
  type: clickhouse
  destinationName: clickhouse
  signals:
    - TRACES
    - METRICS
    - LOGS
  data:
    CLICKHOUSE_ENDPOINT: 'http://clickstack.example.com:8123'
    CLICKHOUSE_DATABASE_NAME: 'otel'
    CLICKHOUSE_CREATE_SCHEME: 'true'

Save the manifest as destination.yaml and apply it:

kubectl apply -f destination.yaml

HyperDX log normalizer

For self-managed deployments that export directly to ClickHouse with Odigos’s native ClickHouse destination, enable HyperDX log normalizer (HYPERDX_LOG_NORMALIZER: true). It parses JSON log bodies and normalizes attributes for better querying in the ClickStack UI. This setting does not apply to the fully managed OTLP destination.

Configure destinations with Kubernetes manifests

OTLP HTTP (ClickStack)

apiVersion: odigos.io/v1alpha1
kind: Destination
metadata:
  name: clickstack
  namespace: odigos-system
spec:
  type: otlphttp
  destinationName: otlphttp
  signals:
    - TRACES
    - METRICS
    - LOGS
  data:
    OTLP_HTTP_ENDPOINT: 'http://clickstack.example.com:4318'
    # Self-managed: OTLP_AUTH_TOKEN
    # ClickHouse Observability: Bearer <YOUR_INGESTION_API_KEY>
    OTLP_HTTP_HEADERS: 'Authorization:<YOUR_AUTHORIZATION_VALUE>'

Apply the manifest:

kubectl apply -f destination.yaml

Odigos VM Agent

The Odigos VM Agent instruments Linux processes, systemd services, and/or docker containers using eBPF. Telemetry exports to the same destinations as cluster-based Odigos, including ClickHouse Observability over OTLP HTTP. The VM Agent is part of Odigos Pro. See the VM Agent overview for setup, sources, and destination configuration.

Odigos Central

Odigos Central is a centralized control plane for managing instrumentation, destinations, and pipeline configuration across multiple Kubernetes clusters from one UI - instead of configuring each cluster separately. Odigos Central is available in Odigos Enterprise. See the Central overview for multi-cluster management, SSO, and unified sampling rules.

Next steps

Explore traces across instrumented services in ClickHouse Observability
Build dashboards for metrics Odigos exports
For self-managed deployments, tune ClickHouse schema and TTL for your retention and query patterns

Example destination configuration

The following screenshot shows an OTLP HTTP destination with logs, metrics, and traces enabled and a bearer token in the Authorization header. Replace the example endpoint and token with your service’s OTLP HTTP endpoint and ingestion API key.

Introduction

Features

Administration

Guides

Integration partners

Self-managed

Sending OpenTelemetry to ClickHouse Observability with Odigos

What is Odigos?

Why Odigos + ClickHouse Observability?

Prerequisites

Integrate ClickHouse Observability with Odigos

Advanced configuration

Native ClickHouse destination

HyperDX log normalizer

Configure destinations with Kubernetes manifests

Odigos VM Agent

Odigos Central

Next steps

Read more

Example destination configuration

​What is Odigos?

​Why Odigos + ClickHouse Observability?

​Prerequisites

​Integrate ClickHouse Observability with Odigos

​Advanced configuration

​Native ClickHouse destination

​HyperDX log normalizer

​Configure destinations with Kubernetes manifests

​Odigos VM Agent

​Odigos Central

​Next steps

​Read more

​Example destination configuration

What is Odigos?

Why Odigos + ClickHouse Observability?

Prerequisites

Integrate ClickHouse Observability with Odigos

Advanced configuration

Native ClickHouse destination

HyperDX log normalizer

Configure destinations with Kubernetes manifests

Odigos VM Agent

Odigos Central

Next steps

Read more

Example destination configuration