Datadog

Cloud monitoring as a service

Integrate the Datadog API with the Snowflake API

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

Post Metric Data with Datadog API on New Row from Snowflake API
Snowflake + Datadog
 
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Post Metric Data with Datadog API on Query Results from Snowflake API
Snowflake + Datadog
 
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Insert Multiple Rows with Snowflake API on New Monitor Event (Instant) from Datadog API
Datadog + Snowflake
 
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Insert Row with Snowflake API on New Monitor Event (Instant) from Datadog API
Datadog + Snowflake
 
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Post Metric Data with Datadog API on Failed Task in Schema from Snowflake API
Snowflake + Datadog
 
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New Monitor Event (Instant) from the Datadog API

Emit new events captured by a Datadog monitor

 
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New Row from the Snowflake API

Emit new event when a row is added to a table

 
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New Query Results from the Snowflake API

Run a SQL query on a schedule, triggering a workflow for each row of results

 
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Failed Task in Schema from the Snowflake API

Emit new events when a task fails in a database schema

 
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New Database from the Snowflake API

Emit new event when a database is created

 
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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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Insert Multiple Rows with the Snowflake API

Insert multiple rows into a table

 
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Insert Single Row with the Snowflake API

Insert a row into a table

 
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Overview of Datadog

The Datadog API, accessible through Pipedream, empowers you to programmatically interact with Datadog's monitoring and analytics platform. This enables developers to automate the retrieval of monitoring data, manage alert configurations, and synchronize service health information across systems. With Pipedream's serverless execution model, you can create intricate workflows that react to Datadog events or metrics, manipulate the data, and pass it on to other services or even Datadog itself for a cohesive operational ecosystem.

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 Snowflake

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI.

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

2. Enter those details in Pipedream

Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.

You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University.

Connect Snowflake

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import { promisify } from 'util'
import snowflake from 'snowflake-sdk'

export default defineComponent({
  props: {
    snowflake: {
      type: "app",
      app: "snowflake",
    }
  },
  async run({steps, $}) {
    const connection = snowflake.createConnection({
      ...this.snowflake.$auth,
      application: "PIPEDREAM_PIPEDREAM",
    })
    const connectAsync = promisify(connection.connect)
    await connectAsync()
    
    async function connExecuteAsync(options) {
      return new Promise((resolve, reject) => {
        connection.execute({
          ...options,
          complete: function(err, stmt, rows) {
            if (err) {
              reject(err)
            } else {
              resolve({stmt, rows})
            }
          }
        })
      })
    }
    
    // See https://docs.snowflake.com/en/user-guide/nodejs-driver-use.html#executing-statements
    const { rows } = await connExecuteAsync({
      sqlText: `SELECT CURRENT_TIMESTAMP()`,
    })
    return rows
  },
})