---
title: How to send metrics and logs to your Cockpit
description: Learn how to send metrics and logs to your Cockpit using Scaleway's comprehensive guide. This tutorial covers sending Python logs to Scaleway's Cockpit for centralized monitoring and analysis using Grafana, ensuring efficient data management and analysis in your infrastructure.
tags: metrics cockpit logs observability
dates:
  validation: 2026-02-10
  posted: 2022-10-31
---
import Requirements from '@macros/iam/requirements.mdx'

import image from './assets/scaleway-logs-python.webp'
import image2 from './assets/scaleway-explore-python-logs.webp'


This page shows you how to send data such as [metrics](/cockpit/concepts/#metric) and [logs](/cockpit/concepts/#logs) to your [Cockpit](/cockpit/concepts/#cockpit). You can push metrics with any `Prometheus Remote Write` compatible agent such as the [Prometheus](https://prometheus.io/docs/introduction/overview/), [Grafana](https://grafana.com/docs/agent/latest/) or [OpenTelemetry Collector](https://opentelemetry.io/docs/collector/) agents.
You can push logs with any Loki compatible agent such as the [Promtail](https://grafana.com/docs/loki/latest/clients/promtail/), [Fluentd](https://docs.fluentd.org/), [Fluent Bit](https://docs.fluentbit.io/manual/) or [Logstash](https://www.elastic.co/guide/en/logstash/current/introduction.html) agents.

<Requirements />

 - A Scaleway account logged into the [console](https://console.scaleway.com)
 - [Owner](/iam/concepts/#owner) status or [IAM permissions](/iam/concepts/#permission) allowing you to perform actions in the intended Organization
 - Configured an agent. Read our dedicated [documentation](/cockpit/how-to/send-metrics-with-grafana-alloy/) to find out how to configure the Grafana Alloy agent


<Message type="important">
 - Having the default configuration on your agents might lead to more of your resources' metrics being sent, a high consumption, and a high bill at the end of the month.
 - Sending metrics and logs for Scaleway resources or personal data using an external path is a billable feature. In addition, any data that you push yourself is billed, even if you send data from Scaleway products. Refer to the [product pricing](https://www.scaleway.com/en/pricing/managed-services/#cockpit) for more information.
</Message>

## Send metrics and logs to your Cockpit

1. Click **Cockpit** in the **Monitoring** section of the [console](https://console.scaleway.com/) side menu. The **Cockpit** overview page displays.
2. [Create a token](/cockpit/how-to/create-token/) with the **Push** permission for metrics and logs.
    <Message type="important">
     - Make sure that you create your token in the same region as the [data sources](/cockpit/concepts/#data-sources) you want to use it for.
     - Make sure that you copy your token's secret key and save it before you exit the page.
    </Message>
3. Configure your applications to send metrics and logs to your Cockpit [endpoints](/cockpit/concepts/#endpoints), using your token's secret key for authentication.

    <Message type="important">
     Retrieve your metrics' and logs' push endpoints in the [Data sources tab](https://console.scaleway.com/cockpit/dataSource) of the Scaleway console.
    </Message>
4. [Log in to your Grafana account](/cockpit/how-to/access-grafana-and-managed-dashboards/).
5. Create your [Grafana dashboard](/cockpit/how-to/access-grafana-and-managed-dashboards/) and start monitoring your data.

---


    ## Sending Python logs to Cockpit

    The section below provides you with a Python script that sends test log messages to Cockpit. It is a safe way to ensure that your custom log setup works before integrating real application logs.

    <Message type="important">
     - You need custom logs in the `fr-par` region to follow the procedure below. Find out [how to create custom logs](/cockpit/how-to/create-external-data-sources/)
     - You must have [created](/iam/how-to/create-api-keys/) a Scaleway API key and retrieved your API secret key
    </Message>

    1. Open a terminal and run `pip install python-logging-loki` or `pip3 install python-logging-loki` if you are using Python 3, to install the [logging_loki](https://pypi.org/project/python-logging-loki/) package to send your Python logs.
    2. [Create a Cockpit token](/cockpit/how-to/create-token/) with the **Push** permission for logs.
    3. Create a `python_logs.py` Python file and paste the following code snippet into it. Make sure that you replace `000avb0d-34ae-66hh-643b-f9e0n3k17773` with the ID of your logs data source and `$COCKPIT_TOKEN_SECRET_KEY` with your Cockpit token's secret key.

      ```
      import logging
      import logging_loki
      import time

      handler = logging_loki.LokiHandler(
          url="https://000avb0d-34ae-66hh-643b-f9e0n3k17773.cockpit.fr-par.scw.cloud/loki/api/v1/push",
          tags={"job": "logs_from_python"},
          auth=("$COCKPIT_TOKEN_SECRET_KEY"),
          version="1",

      )

      logger = logging.getLogger("my-first-python-logger")
      logger.addHandler(handler)

      def main():
          # Start generating log messages
          for i in range(10):
              logger.error(f"Error message {i}")
              time.sleep(1)

      if __name__ == "__main__":
          main()


      ```

      This script sets up a logger that sends error log messages to the Loki endpoint in Cockpit. It then generates 10 error log messages with a one-second delay between each message. These log messages are sent to Cockpit and can be viewed and analyzed via the Grafana dashboard we will create in the next part.

      <Message type="tip">
        If you are using the Scaleway Loki API, you can `POST` through the `Authorization: Bearer <token>` header, or `POST` using the following endpoint: `https://api_key:YOUR_COCKPIT_TOKEN@logs.cockpit.fr-par.scw.cloud/loki/api/v1/push`.
      </Message>

  ### Creating a Grafana dashboard and visualizing your Python logs

    1. [Log into your Grafana account](/cockpit/how-to/access-grafana-and-managed-dashboards/).
    2. Click **Toggle menu**, then click **Dashboards**.
    3. Click **New** in the top right corner of your screen, then **Import**.
    4. Upload the JSON file of the [Grafana Log Viewer dashboard for Loki](https://grafana.com/grafana/dashboards/13639-logs-app/) or enter `13639` in the **Import via grafana.com** field.
    5. Click **Load**.
    6. Enter a name for the dashboard or leave the default name.
    7. Select a folder in which to store the dashboard.
    8. Select your custom logs data source in the **Loki** drop-down. Make sure that the data source you select is in the `fr-par` region.
    9. Click **Import**.
    10. Open a terminal and enter the following command.
        ```
        python3 python_logs.py
        ```
    11. Click the **Home** icon > **Dashboards**. Your **Logs / App** dashboard should display.
    12. Click the **Logs / App** dashboard. You should see 10 log lines labeled `Error message 0` through `Error message 9`, one per second. This confirms that your setup is working.

        If your logs do not display, try changing the time range to match the time at which you ran your Python file.

        <Lightbox image={image} alt="Error logs display" />
    13. Click the **View in Explore** button for more configuration options.
        <Lightbox image={image2} alt="" />

<Message type="tip">
  Read our more in depth-documentation on [how to configure the Grafana Alloy agent](/cockpit/how-to/send-metrics-with-grafana-alloy/) to push your Scaleway metrics, and visualize them in a Grafana dashboard.
</Message>