# Datadog
source: https://docs.chalk.ai/docs/datadog

## Ingest Chalk metrics into Datadog.

Chalk stores a variety of time series metrics that measure the latency and
throughput of resolvers and streaming pipelines.
Chalk displays these metrics on the Chalk Dashboard, but can also export them to monitoring systems
of your choice via the OpenMetrics standard.

For this purpose, Chalk exposes an endpoint with metrics in a
text-based format that systems like Datadog
are designed to ingest.
Datadog polls this endpoint periodically and ingests
gauges, counters, histograms, and summaries from Chalk.
Then, these metrics appear in Datadog as custom metrics.

### Configuring Datadog

### Step 1: Create a Datadog agent

Datadog Agents are processes that run on your servers to collect metrics and send them to Datadog's online
monitoring systems.

You can use an existing agent to collect Chalk metrics, or
create an agent specifically for Chalk.
Once you have created an agent, you can configure it to ingest metrics from Chalk.

### Step 2: Create a Chalk service token

Chalk secures the metrics export endpoint using the same authentication and authorization mechanisms used for
accessing other Chalk systems.

After creating a Datadog agent, generate a set of service credentials with the logs.list
permission.

Datadog token

Keep the client_id and client_secret handy -- you'll need them in the next step.

### Step 3: Configure the agent

Next, configure the Datadog agent
to ingest OpenMetrics data from Chalk.

Edit the OpenMetrics configuration file, which
comes standard with Datadog Agent as of version 6.6.0. Datadog Agent configuration files are found in the
agent configuration directory.
In that directory is a file named openmetrics.d/conf.yaml.
Add the following content:

```
instances:
  - openmetrics_endpoint: https://api.chalk.ai/v1/metrics/export

    ## (Optional) A prefix to prepend to all metrics
    namespace: chalk

    metrics:
      - resolver_latency_seconds
      - resolver_request
      - feature_request
      - deployment
      - query_http_response

    headers:
      X-Chalk-Client-Id: token-<redacted>
      X-Chalk-Client-Secret: ts-<redacted>
```

In X-Chalk-Client-Id and X-Chalk-Client-Secret,
supply the client ID and secret you generated in
Step 2.
In the metrics section of the config file,
you can specify any of the metrics found in the
list of supported metrics.

### Step 4: Verification

Your Chalk metrics will appear on the Datadog
metrics summary page
after updating the Datadog Agent configuration and restarting your Datadog Agent.

They should appear like this:

Datadog verification