OpenTelemetry

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Overview

Icelake speaks OTLP/HTTP protobuf natively for logs and metrics. Ship observability data from any OTel-instrumented application or from the OpenTelemetry Collector — no adapters in between.

Traces are not supported yet. Keep traces in your existing tracing backend for now; logs that carry a trace_id / span_id keep them, so you can correlate.

All OTLP endpoints authenticate via HTTP Basic auth — username is your client ID, password is your API key (ilk_ + 64 hex characters).

Getting started

1. Configure the OpenTelemetry Collector

Point your OTel Collector’s otlphttp exporter at Icelake:

otel-collector-config.yaml

exporters:
  otlphttp:
    # The exporter appends /v1/logs and /v1/metrics to this base URL
    endpoint: "https://api.icelake.eu/otlp"
    auth:
      authenticator: basicauth/icelake

extensions:
  basicauth/icelake:
    client_auth:
      username: "your-client-id"
      password: "ilk_your-api-key-here"

service:
  extensions: [basicauth/icelake]
  pipelines:
    logs:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlphttp]
    metrics:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlphttp]

2. Verify ingestion

Check that the service is up and that data is arriving. OTLP data is stored with your service.name resource attribute as its source_id (or otlp when it’s not set):

# Health check
curl https://api.icelake.eu/healthz

# Latest OTel logs of one service, via the PostgreSQL wire protocol
psql "postgresql://your-client-id:ilk_your-api-key-here@sql.icelake.eu:5432/icelake?sslmode=require" \
  -c "SELECT timestamp, log_level, message FROM logs WHERE source_id = 'my-service' ORDER BY timestamp DESC LIMIT 10"

The service also appears under Data → Data Sets in the admin UI.

OTLP endpoints

Both endpoints accept OTLP/HTTP protobuf payloads with Basic auth.

Logs

POST https://api.icelake.eu/otlp/v1/logs
Content-Type: application/x-protobuf
Authorization: Basic <base64("client_id:api_key")>

OTel log records are mapped to Icelake’s log storage with:

• body → log message
• resource.attributes → labels
• timestamp → nanosecond precision timestamp
• severity → log level label

Metrics

POST https://api.icelake.eu/otlp/v1/metrics
Content-Type: application/x-protobuf
Authorization: Basic <base64("client_id:api_key")>

OTel metrics are converted to Prometheus-compatible format:

• Gauge → Prometheus gauge
• Sum (monotonic) → Prometheus counter
• Histogram → Prometheus histogram
• Attributes → Prometheus labels

Traces

Not supported yet — see the note at the top of this page.

Application instrumentation

Direct OTLP export (no Collector)

For simple setups, export directly from your application:

Python Example

import base64
from opentelemetry.exporter.otlp.proto.http.log_exporter import OTLPLogExporter

creds = base64.b64encode(b"your-client-id:ilk_your-api-key-here").decode()
exporter = OTLPLogExporter(
    endpoint="https://api.icelake.eu/otlp/v1/logs",
    headers={"Authorization": f"Basic {creds}"},
)

Node.js Example

const { OTLPLogExporter } = require('@opentelemetry/exporter-logs-otlp-http');

const creds = Buffer.from('your-client-id:ilk_your-api-key-here').toString('base64');
const exporter = new OTLPLogExporter({
  url: 'https://api.icelake.eu/otlp/v1/logs',
  headers: {
    Authorization: `Basic ${creds}`,
  },
});

Storage layout

OTel data is stored alongside Prometheus and Loki data in the same ClickHouse tables, so one query can join signals from all three:

Table	Contents
metrics	Prometheus remote-write and OTLP metrics (one row per sample)
logs	Loki push and OTLP logs, with trace_id / span_id when the record carries them

Both are partitioned by tenant and month and sorted by source and time, with 10-minute, hourly and daily rollups maintained automatically.

API reference

Endpoint	Method	Content-Type	Description
/otlp/v1/logs	POST	application/x-protobuf	OTLP log ingestion
/otlp/v1/metrics	POST	application/x-protobuf	OTLP metric ingestion

Best practices

Pro tip: use the OpenTelemetry Collector as a gateway to batch, filter, and route data before sending to Icelake.

• Use the batch processor in your OTel Collector for efficient ingestion
• Map resource attributes to meaningful labels for queryability
• Set up separate pipelines for logs and metrics
• Monitor collector health alongside Icelake ingestion rates

Related docs

• Quickstart — your first data in Icelake in minutes
• Prometheus — remote write path for metrics-only pipelines
• Loki & LogQL — log-shipping alternative if you’re not on OTEL