Exporting Metrics to Monitoring Platforms

Export real-time resource and execution metrics from Cerebrium applications to an existing observability platform. Monitor CPU, memory, GPU usage, request counts, and latency. Most major OTLP-compatible monitoring platforms are supported.

What metrics are exported?

Resource Metrics

Metric	Type	Unit	Description
`cerebrium_cpu_utilization_cores`	Gauge	cores	CPU cores actively in use per app
`cerebrium_memory_usage_bytes`	Gauge	bytes	Memory actively in use per app
`cerebrium_gpu_memory_usage_bytes`	Gauge	bytes	GPU VRAM in use per app
`cerebrium_gpu_compute_utilization_percent`	Gauge	percent	GPU compute utilization (0-100) per app
`cerebrium_containers_running_count`	Gauge	count	Number of running containers per app
`cerebrium_containers_ready_count`	Gauge	count	Number of ready containers per app

Execution Metrics

Metric	Type	Unit	Description
`cerebrium_run_execution_time_ms`	Histogram	ms	Time spent executing user code
`cerebrium_run_queue_time_ms`	Histogram	ms	Time spent waiting in queue
`cerebrium_run_coldstart_time_ms`	Histogram	ms	Time for container cold start
`cerebrium_run_response_time_ms`	Histogram	ms	Total end-to-end response time
`cerebrium_run_total`	Counter	—	Total run count
`cerebrium_run_successes_total`	Counter	—	Successful run count
`cerebrium_run_errors_total`	Counter	—	Failed run count

Prometheus metric name mapping: When metrics are ingested by Prometheus (including Grafana Cloud), OTLP automatically appends unit suffixes to metric names. Histogram metrics will appear with _milliseconds appended — for example, cerebrium_run_execution_time_ms becomes cerebrium_run_execution_time_ms_milliseconds_bucket, _count, and _sum. Counter metrics with the _total suffix remain unchanged. The example queries throughout this guide use the Prometheus-ingested names.

Labels

Every metric includes the following labels for filtering and grouping:

Label	Description	Example
`project_id`	Your Cerebrium project ID	`p-abc12345`
`app_id`	Full application identifier	`p-abc12345-my-model`
`app_name`	Human-readable app name	`my-model`
`region`	Deployment region	`us-east-1`

How it works

Cerebrium automatically pushes metrics to the configured monitoring platform every 60 seconds using the OpenTelemetry Protocol (OTLP). Provide an OTLP endpoint and authentication credentials through the Cerebrium dashboard — Cerebrium handles collecting resource usage and execution data, formatting it as OpenTelemetry metrics, and delivering it to the destination.

Metrics are pushed every 60 seconds
Failed pushes are retried 3 times with exponential backoff
If pushes fail 10 consecutive times, export is automatically paused to avoid noise (re-enable at any time from the dashboard)
Credentials are stored encrypted and never returned in API responses

Supported destinations

Grafana Cloud — Primary supported destination
Datadog — Via OTLP endpoint
Prometheus — Self-hosted with OTLP receiver enabled
Custom — Any OTLP-compatible endpoint (New Relic, Honeycomb, etc.)

Setup Guide

Step 1: Get your platform credentials

Gather an OTLP endpoint and authentication credentials from the monitoring platform before configuring the Cerebrium dashboard.

Grafana Cloud
Datadog
Self-hosted Prometheus
Custom OTLP

Sign in to Grafana Cloud
Go to your stack → Connections → Add new connection
Search for “OpenTelemetry” and click Configure
Copy the OTLP endpoint — this will match your stack’s region:
- US: https://otlp-gateway-prod-us-east-0.grafana.net/otlp
- EU: https://otlp-gateway-prod-eu-west-0.grafana.net/otlp
- Other regions will show their specific URL on the configuration page
On the same page, generate an API token. Click Generate now and ensure the token has the MetricsPublisher role — this is a separate token from any Prometheus Remote Write tokens you may already have.
The page will show you an Instance ID and the generated token. Run the following in your terminal to create the Basic auth string:

echo -n "INSTANCE_ID:TOKEN" | base64

Copy the output — you’ll paste it in the dashboard in the next step.

The API token must have the MetricsPublisher role. The default Prometheus Remote Write token will not work with the OTLP endpoint. If you’re unsure, generate a new token from the OpenTelemetry configuration page — it will have the correct role by default.

Sign in to Datadog
Go to Organization Settings → API Keys
Create or copy an existing API key
Your OTLP endpoint depends on your Datadog site:

Datadog Site	OTLP Endpoint
US1 (datadoghq.com)	`https://api.datadoghq.com/api/v2/otlp`
US3 (us3.datadoghq.com)	`https://api.us3.datadoghq.com/api/v2/otlp`
US5 (us5.datadoghq.com)	`https://api.us5.datadoghq.com/api/v2/otlp`
EU (datadoghq.eu)	`https://api.datadoghq.eu/api/v2/otlp`
AP1 (ap1.datadoghq.com)	`https://api.ap1.datadoghq.com/api/v2/otlp`

Find the site in the Datadog URL — for example, if you log in at app.us3.datadoghq.com, your site is US3.Keep your API key and endpoint handy for the next step.

Enable the OTLP receiver in your Prometheus config:
- Add --enable-feature=otlp-write-receiver flag
- Or use an OpenTelemetry Collector as a sidecar
Your endpoint will be http://YOUR_PROMETHEUS_HOST:4318 (this is the OTLP HTTP port — not 4317, which is gRPC) — copy this for the next step

Any platform that supports OpenTelemetry OTLP over HTTP will work, including New Relic, Honeycomb, Lightstep, and others.

Get the OTLP HTTP endpoint from your provider’s documentation
Get the required authentication headers

Common examples:

Platform	Auth Header Name	Auth Header Value
New Relic	`api-key`	Your New Relic license key
Honeycomb	`x-honeycomb-team`	Your Honeycomb API key
Lightstep	`lightstep-access-token`	Your Lightstep token

Step 2: Configure in the Cerebrium dashboard

In the Cerebrium dashboard, go to your project → Integrations → Metrics Export
Paste your OTLP endpoint from Step 1
Add the authentication headers from Step 1:

Grafana Cloud
Datadog
Self-hosted Prometheus
Custom OTLP

Header name: Authorization - Header value: Basic YOUR_BASE64_STRING (the output from the terminal command in Step 1)

Header name: DD-API-KEY - Header value: Your Datadog API key

Header name: Authorization (if auth is enabled on your Prometheus, otherwise leave empty) - Header value: Bearer your-token (if auth is enabled)

Click Save & Enable

Metrics start flowing within 60 seconds. The dashboard shows a green “Connected” status with the time of the last successful export. If something looks wrong, click Test Connection to verify Cerebrium can reach the monitoring platform. The result includes details to help troubleshoot.

Viewing Metrics

Once connected, metrics appear in the monitoring platform within a minute or two (exact latency depends on the platform’s ingestion pipeline).

Grafana Cloud
Datadog
Prometheus

Go to your Grafana Cloud dashboard → Explore
Select your Prometheus data source — it will be named something like grafanacloud-yourstack-prom (find it under Connections → Data sources if you’re unsure)
Search for metrics starting with cerebrium_

Example queries:

Histogram metrics in Prometheus have _milliseconds appended by OTLP’s unit suffix convention, so you’ll see names like cerebrium_run_execution_time_ms_milliseconds_bucket. This is expected behavior — see the metric name mapping note above.

# CPU usage by app
cerebrium_cpu_utilization_cores{project_id="YOUR_PROJECT_ID"}

# Memory for a specific app
cerebrium_memory_usage_bytes{app_name="my-model"}

# Container scaling over time
cerebrium_containers_running_count{project_id="YOUR_PROJECT_ID"}

# Request rate (requests per second over 5 minutes)
rate(cerebrium_run_total[5m])

# p99 execution latency
histogram_quantile(0.99, rate(cerebrium_run_execution_time_ms_milliseconds_bucket{app_name="my-model"}[5m]))

# p99 end-to-end response time
histogram_quantile(0.99, rate(cerebrium_run_response_time_ms_milliseconds_bucket{app_name="my-model"}[5m]))

# Error rate as a percentage
rate(cerebrium_run_errors_total{app_name="my-model"}[5m]) / rate(cerebrium_run_total{app_name="my-model"}[5m]) * 100

# Average cold start time
rate(cerebrium_run_coldstart_time_ms_milliseconds_sum{app_name="my-model"}[5m]) / rate(cerebrium_run_coldstart_time_ms_milliseconds_count{app_name="my-model"}[5m])

Go to Metrics → Explorer in your Datadog dashboard
Search for metrics starting with cerebrium
Filter by project_id, app_name, and other labels using the “from” field

Query your Prometheus instance directly. All Cerebrium metrics are prefixed with cerebrium_:

# List all Cerebrium metrics
{__name__=~"cerebrium_.*"}

# CPU usage across all apps
cerebrium_cpu_utilization_cores

Managing Metrics Export

Manage metrics export configuration from the dashboard at any time under Integrations → Metrics Export.

Disable export: Toggle the switch off. The configuration is preserved — re-enable at any time without reconfiguring.
Update credentials: Enter new authentication headers and click Save Changes. Use this when rotating API keys.
Change endpoint: Update the OTLP endpoint field and click Save Changes.
Check status: The dashboard shows whether export is connected, the time of the last successful export, and any error messages.

Troubleshooting

Metrics not appearing

Check the dashboard status. Go to Integrations → Metrics Export and look for the connection status. If it shows “Paused,” export was automatically disabled after repeated failures — click Re-enable after fixing the issue.
Run a connection test. Click Test Connection on the dashboard. Common errors:
- 401 / 403 Unauthorized: Your auth headers are wrong. For Grafana Cloud, make sure you’re using a MetricsPublisher token (not a Prometheus Remote Write token). For Datadog, verify your API key is active.
- 404 Not Found: The OTLP endpoint URL is incorrect. Double-check the URL matches your platform and region.
- Connection timeout: Your endpoint may be unreachable. For self-hosted Prometheus, confirm the host is publicly accessible and port 4318 is open.
Check your platform’s data source. In Grafana Cloud, make sure you’re querying the correct Prometheus data source (not a Loki or Tempo source). In Datadog, check that your site region matches the endpoint you configured.

Metrics appear but values look wrong

Histogram metrics have _milliseconds in the name. This is normal — Prometheus appends unit suffixes from OTLP metadata. Use the full name (e.g., cerebrium_run_execution_time_ms_milliseconds_bucket) in your queries.
Container counts fluctuate during deploys. This is expected — you may see temporary spikes in cerebrium_containers_running_count during rolling deployments as new containers start and old ones drain.
Gaps in metrics. Short gaps (1-2 minutes) can occur during deployments or scaling events. If you see persistent gaps, check whether export was paused.

Still stuck?

Contact support@cerebrium.ai with the project ID and error message from the dashboard for further investigation.

​What metrics are exported?

​Resource Metrics

​Execution Metrics

​Labels

​How it works

​Supported destinations

​Setup Guide

​Step 1: Get your platform credentials

​Step 2: Configure in the Cerebrium dashboard

​Viewing Metrics

​Managing Metrics Export

​Troubleshooting

​Metrics not appearing

​Metrics appear but values look wrong

​Still stuck?

What metrics are exported?

Resource Metrics

Execution Metrics

Labels

How it works

Supported destinations

Setup Guide

Step 1: Get your platform credentials

Step 2: Configure in the Cerebrium dashboard

Viewing Metrics

Managing Metrics Export

Troubleshooting

Metrics not appearing

Metrics appear but values look wrong

Still stuck?