Datadog

Cloud monitoring as a service

Integrate the Datadog API with the Python API

Setup the Datadog API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Datadog and Python remarkably fast. Free for developers.

Run Python Code with Python API on New Monitor Event (Instant) from Datadog API
Datadog + Python
 
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New Monitor Event (Instant) from the Datadog API

Emit new events captured by a Datadog monitor

 
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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

 
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Post Metric Data with the Datadog API

The metrics end-point allows you to post time-series data that can be graphed on Datadog's dashboards. See docs

 
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Overview of Datadog

With the Datadog API, you can build a variety of applications and tools to help
you monitor and optimize your Datadog account. Here are a few examples:

  • A tool to help you visualize your Datadog account data
  • A tool to help you manage your Datadog account settings
  • A tool to help you monitor and troubleshoot your Datadog account
  • A tool to help you migrate your data to Datadog

Connect Datadog

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    datadog: {
      type: "app",
      app: "datadog",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.datadoghq.com/api/v1/user`,
      headers: {
        "DD-API-KEY": `${this.datadog.$auth.api_key}`,
        "DD-APPLICATION-KEY": `${this.datadog.$auth.application_key}`,
      },
    })
  },
})

Overview of Python

Python API on Pipedream offers developers to build or automate a variety of
tasks from their web and cloud apps. With the Python API, users are able to
create comprehensive and flexible scripts, compose and manage environment
variables, and configure resources to perform a range of functions.

By using Pipedream, you can easily:

  • Create automated workflows that run on a specific schedule
  • Compose workflows across various apps and services
  • React to events in cloud services or form data
  • Automatically create content and notifications
  • Construct classifications and predictions
  • Analyze and react to sentiment, sentiment analysis and sentiment score
  • Connect backends to the frontend with serverless functions
  • Work with files and databases
  • Perform web requests and fetch data
  • Integrate third-party APIs into your apps
  • Orchestrate data processing tasks and pipelines
  • Create powerful application APIs with authentication and authorization
  • Design CI/CD pipelines and Continuous Delivery services
  • Connect databases like MongoDB and MySQL
  • Monitor connections and events
  • Generate alerts and notifications for corresponding events

Connect Python

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def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}