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Fiberplane Studio helps developer teams build better incident workflows and automated, data-rich incident reviews.


Fiberplane workflow relies on three key principles:

  • describe and template your incident review requirements in code
  • integrate with your alerting and on-call tooling and automate your reviews
  • query and attach your observability data where needed

Creating your first template

Templates are central feature in Fiberplane enabling you to create incident workflows and programmatically set structure for your postmortems.

In this guide we will create our first template, upload it to Fiberplane, and add it to our incident workflow.


A Fiberplane account: go to and sign up for an account.


  1. Download, install, and authenticate the CLI

    Fiberplane CLI is the main tool to programmatically interact with Fiberplane resources (notebooks, templates, and daemons) from your local machine.

    Installing Fiberplane CLI...
    brew install fiberplane/tap/fp

    Once installed you can authenticate the CLI by running:

    Authenticating Fiberplane CLI...
    fp login
  2. Initialize a template

    To initialize a basic template in the current directory run:

    Initializing a Fiberplane template...
    fp templates init

    The command will scaffold a template and save it to a file template.jsonnet in the current directory.

    local fp = import 'fiberplane.libsonnet';
    local c = fp.cell;
    local fmt = fp.format;
    title='Replace me!'
    c.h1('This is a section'),
    c.text('You can add any types of cells and pre-fill content'),
  3. Create the template in Fiberplane

    Run the following command to create the template in Fiberplane passing in our source file template.jsonnet as an argument.

    Creating a template in Fiberplane...
    fp templates create ./template.jsonnet

    The command will prompt you for the title and description of your template, and will add the template to your Fiberplane account.

    You can verify that the template is added by listing out all of your templates with fp templates list or by navigating to your Fiberplane home screen’s Templates tab.

Adding a data source

Data sources can be added to Fiberplane notebooks using the Providers. Providers enable you to query them even if they are not exposed to the wider internet (using the Fiberplane Daemon).

How Providers work

Whenever you execute a data query in the notebook:

  1. The query is forwarded to the Fiberplane Daemon fpd installed in your cluster;
  2. The fpd then queries the Provider data source (e.g. your Prometheus or Elastic instance);
  3. When the Provider returns the data, the fpd processes, encrypts, and then returns it back to the Studio.

Set up the Fiberplane Daemon

The Fiberplane Daemon is a package that runs in your infrastructure. It enables you to connect the Fiberplane Studio to the data sources in your cluster(s) securely without exposing them to the Internet.

The Fiberplane Daemon is available as a container on Docker Hub.

  1. Create an API Token

    In the Studio

    In order for the Daemon to receive queries from Fiberplane Notebooks, it needs to be authorized. This step will generate a Daemon API Token that will be needed in later steps.

    You can do it in the Settings > FPD menu or using our CLI tool.

    Register a proxy

    In order for the Daemon to talk to the Fiberplane Studio successfully it needs to be successfully authorized. This step will generate a Daemon API Token that will be needed later.

    Go to your Fiberplane Settings page.

    Click + New to register a proxy with a name that identifies the cluster you will install it into (for example, “Production”). This will generate and display a Daemon API Token that the proxy will use to authenticate with the Fiberplane Studio. Copy the Daemon API Token generated in Step 2 for the next step.

    Using the CLI

    Make sure you have the Fiberplane CLI installed.

    To register a daemon run a command:

    Creating an API token...
    fp daemon create my-daemon

    You can leave out the daemon name to have one randomly generated, but we recommend naming it according to the environment it will be deployed to (for example, production). Note that daemon names must follow the Fiberplane name format.

  2. Configure the data sources

    We need to provide instructions for the daemon to look for data source APIs in the correct places. To do that create a data_sources.yaml in your working directory. Here’s an example configuration

    - name: prometheus-prod
    eescription: Prometheus (Production)
    providerType: prometheus # any of the currently supported Providers
    # Replace the following line with your Prometheus URL
    url: http://prometheus
  3. Deploy the daemon

    We can now deploy and authenticate the daemon using the API Token we have created earlier.

    Run the following command (or add the equivalent of docker-compose) in your terminal. Replace <FPD_API_TOKEN> with the API token you have created earlier.

    Deploying daemon as a Docker container...
    docker run \
    -v "$PWD/data_sources.yaml:/app/data_sources.yaml" \
    fiberplane/fpd:v2 \

Next steps

Let’s recap what we have done here so far:

  • we have successfully created and initialized our first Template
  • we have initialized and deployed our first Fiberplane Daemon fpd
  • we have configured the fpd to query the data sources in our closed off internal system

Where do we go from here? We can:

  • set up a dedicated folder in our code for Fiberplane Templates and a GitHub Action to automatically update it when things change;
  • connect more Providers to Fiberplane so we can have multiple sources of data in our notebooks;
  • learn how to send data from our terminal sessions to notebooks.