@datadog/datadog-api-client

What is @datadog/datadog-api-client?

@datadog/datadog-api-client is an official Node.js client library for interacting with the Datadog API. It allows developers to programmatically manage and interact with Datadog's monitoring, logging, and tracing services. This includes creating and managing dashboards, monitors, events, and more.

What are @datadog/datadog-api-client's main functionalities?

Create a Dashboard

This code sample demonstrates how to create a new dashboard in Datadog using the @datadog/datadog-api-client package.

const { v1: datadog } = require('@datadog/datadog-api-client');
const configuration = datadog.createConfiguration();
const apiInstance = new datadog.DashboardsApi(configuration);

const params = {
  body: {
    title: 'Example-Dashboard',
    widgets: [],
    layoutType: 'ordered',
    description: 'A sample dashboard',
    isReadOnly: false,
    notifyList: []
  }
};

apiInstance.createDashboard(params).then((data) => {
  console.log('API called successfully. Returned data: ' + JSON.stringify(data));
}).catch((error) => {
  console.error(error);
});

Create a Monitor

This code sample demonstrates how to create a new monitor in Datadog using the @datadog/datadog-api-client package.

const { v1: datadog } = require('@datadog/datadog-api-client');
const configuration = datadog.createConfiguration();
const apiInstance = new datadog.MonitorsApi(configuration);

const params = {
  body: {
    name: 'Example-Monitor',
    type: 'metric alert',
    query: 'avg(last_5m):avg:system.cpu.user{host:host0} > 75',
    message: 'CPU usage is high on host0',
    tags: ['env:production'],
    options: {
      thresholds: {
        critical: 75
      }
    }
  }
};

apiInstance.createMonitor(params).then((data) => {
  console.log('API called successfully. Returned data: ' + JSON.stringify(data));
}).catch((error) => {
  console.error(error);
});

Post an Event

This code sample demonstrates how to post a new event to Datadog using the @datadog/datadog-api-client package.

const { v1: datadog } = require('@datadog/datadog-api-client');
const configuration = datadog.createConfiguration();
const apiInstance = new datadog.EventsApi(configuration);

const params = {
  body: {
    title: 'Example-Event',
    text: 'An example event for Datadog',
    tags: ['env:production'],
    alertType: 'info'
  }
};

apiInstance.createEvent(params).then((data) => {
  console.log('API called successfully. Returned data: ' + JSON.stringify(data));
}).catch((error) => {
  console.error(error);
});

Other packages similar to @datadog/datadog-api-client

newrelic

The 'newrelic' package is the official Node.js client for New Relic, a competitor to Datadog. It provides similar functionalities for monitoring and managing application performance, but is specific to New Relic's ecosystem.

prom-client

The 'prom-client' package is a client for Prometheus, an open-source monitoring and alerting toolkit. While it doesn't offer the same breadth of features as Datadog, it is widely used for metrics collection and monitoring in cloud-native environments.

elastic-apm-node

The 'elastic-apm-node' package is the official Node.js agent for Elastic APM, part of the Elastic Stack. It provides performance monitoring and error tracking for Node.js applications, similar to Datadog's APM features.

README

Node.js Datadog API Client

This repository contains a Node.js API client for the Datadog API.

How to install

The package is under @datadog/datadog-api-client and can be installed through NPM or Yarn:

# NPM
npm install @datadog/datadog-api-client

# Yarn
yarn add @datadog/datadog-api-client

Getting Started

Here's an example getting a monitor:

import { client, v1 } from '@datadog/datadog-api-client';

const configuration = client.createConfiguration();
const apiInstance = new v1.MonitorsApi(configuration);

let params:v1.MonitorsApiGetMonitorRequest = {
  // number | The ID of the monitor
  monitorId: 1,
};

apiInstance.getMonitor(params).then((data: v1.Monitor) => {
  console.log('API called successfully. Returned data: ' + data);
}).catch((error:any) => console.error(error));

Authentication

By default the library will use the DD_API_KEY and DD_APP_KEY environment variables to authenticate against the Datadog API. To provide your own set of credentials, you need to set the appropriate keys on the configuration:

import { client } from '@datadog/datadog-api-client';

const configurationOpts = {
  authMethods: {
    apiKeyAuth: "<API KEY>",
    appKeyAuth: "<APPLICATION KEY>"
  },
};

const configuration = client.createConfiguration(configurationOpts);

Unstable Endpoints

This client includes access to Datadog API endpoints while they are in an unstable state and may undergo breaking changes. An extra configuration step is required to enable these endpoints:

configuration.unstableOperations["<version>.<operationName>"] = true

where <operationName> is the name of the method used to interact with that endpoint. For example: listLogIndexes, or getLogsIndex.

Changing Server

When talking to a different server, like the eu instance, change the server variables:

import { client } from '@datadog/datadog-api-client';

const configuration = client.createConfiguration();

configuration.setServerVariables({
  site: "datadoghq.eu"
});

Disable compressed payloads

If you want to disable GZIP compressed responses, set the compress flag on your configuration options:

import { client } from '@datadog/datadog-api-client';
const configurationOpts = {
  httpConfig: {
    compress: false
  },
};

const configuration = client.createConfiguration(configurationOpts);

Enable requests logging

If you want to enable requests logging, set the debug flag on your configuration object:

import { client } from '@datadog/datadog-api-client';
const configurationOpts = {
  debug: true
};

const configuration = client.createConfiguration(configurationOpts);

Enable retry

To enable the client to retry when rate limited (status 429) or status 500 and above:

import { client } from '@datadog/datadog-api-client';
const configurationOpts = {
  enableRetry: true
};

const configuration = client.createConfiguration(configurationOpts);

The interval between 2 retry attempts will be the value of the x-ratelimit-reset response header when available. If not, it will be :

(backoffMultiplier ** current_retry_count) * backoffBase

The maximum number of retry attempts is 3 by default and can be modified with

maxRetries

Adding timeout to requests

To add timeout or other mechanism to cancel requests, you need an abort controller, for example the one implemented by abort-controller. You can then pass the `signal method to the HTTP configuration options:

import { client, v1 } from '@datadog/datadog-api-client';
import AbortController from 'abort-controller';

const controller = new AbortController();
const timeout = setTimeout(
  () => { controller.abort(); },
  1000,
);
const configurationOpts = {
  httpConfig: {
    signal: controller.signal
  },
};

const configuration = client.createConfiguration(configurationOpts);

const apiInstance = new v1.MonitorsApi(configuration);
apiInstance.listMonitors().then((data: v1.Monitor[]) => {
  console.log('API called successfully. Returned data: ' + data);
}).catch((error:any) => console.error(error)).finally(() => clearTimeout(timeout));

Pagination

Several listing operations have a pagination method to help consume all the items available. For example, to retrieve all your incidents:

import { client, v2 } from "@datadog/datadog-api-client";

async function main() {
  const configuration = client.createConfiguration();
  configuration.unstableOperations["v2.listIncidents"] = true;
  const apiInstance = new v2.IncidentsApi(configuration);

  for await (const incident of apiInstance.listIncidentsWithPagination()) {
      console.log("Got incident " + incident.id);
  }
}

main();

Zstd compression

Zstd compression support requires users to supply their own zstd compressor callback function. The callback should accept string arg and return compressed Buffer data. Callback signature (body: string) => Buffer. For example, using zstd.ts package:

import { compressSync } from 'zstd.ts'
import { client, v2 } from "@datadog/datadog-api-client";

async function main() {
  const configurationOpts = {
    zstdCompressorCallback: (body: string) => compressSync({input: Buffer.from(body, "utf8")})
  }
  const configuration = client.createConfiguration(configurationOpts);
  const apiInstance = new v2.MetricsApi(configuration);
  const params: v2.MetricsApiSubmitMetricsRequest = {
      body: {
          series: [
              {
                  metric: "system.load.1",
                  type: 0,
                  points: [
                      {
                          timestamp: Math.round(new Date().getTime() / 1000),
                          value: 0.7,
                      },
                  ],
              },
          ],
      },
      contentEncoding: "zstd1",
  };

  apiInstance.submitMetrics(params).then((data: v2.IntakePayloadAccepted) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  }).catch((error: any) => console.error(error));
}

main();

Configure proxy

You can provide custom HttpLibrary implementation with proxy support to configuration object. See example below:

import pako from "pako";
import bufferFrom from "buffer-from";
import fetch from "node-fetch";
import { HttpsProxyAgent } from "https-proxy-agent";
import { v1, client } from "@datadog/datadog-api-client";

const proxyAgent = new HttpsProxyAgent('http://127.0.0.11:3128');

class HttpLibraryWithProxy implements client.HttpLibrary {
    public debug = false;

    public send(request: client.RequestContext): Promise<client.ResponseContext> {
        const method = request.getHttpMethod().toString();
        let body = request.getBody();

        let compress = request.getHttpConfig().compress;
        if (compress === undefined) {
            compress = true;
        }

        const headers = request.getHeaders();
        if (typeof body === "string") {
            if (headers["Content-Encoding"] === "gzip") {
                body = bufferFrom(pako.gzip(body).buffer);
            } else if (headers["Content-Encoding"] === "deflate") {
                body = bufferFrom(pako.deflate(body).buffer);
            }
        }

        const resultPromise = fetch(request.getUrl(), {
            method: method,
            body: body as any,
            headers: headers,
            signal: request.getHttpConfig().signal,
            compress: compress,
            agent: proxyAgent,
        }).then((resp: any) => {
            const headers: { [name: string]: string } = {};
            resp.headers.forEach((value: string, name: string) => {
                headers[name] = value;
            });

            const body = {
                text: () => resp.text(),
                binary: () => resp.buffer(),
            };
            const response = new client.ResponseContext(resp.status, headers, body);
            return response;
        });

        return resultPromise;
    }
}

const configuration = client.createConfiguration({httpApi: new HttpLibraryWithProxy()});
const apiInstance = new v1.DashboardsApi(configuration);

apiInstance
    .listDashboards()
    .then((data: v1.DashboardSummary) => {
        console.log(
            "API called successfully. Returned data: " + JSON.stringify(data)
        );
    })
    .catch((error: any) => console.error(error));

Documentation

Documentation for API endpoints can be found in GitHub pages.

Contributing

As most of the code in this repository is generated, we will only accept PRs for files that are not modified by our code-generation machinery (changes to the generated files would get overwritten). We happily accept contributions to files that are not autogenerated, such as tests and development tooling.

Author

[e-mail]

License

Apache License, v2.0