Uptime Robot

Verifies downtime from multiple locations

Integrate the Uptime Robot API with the Go API

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

Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it

Overview of Uptime Robot

The Uptime Robot API allows you to monitor the uptime of your websites and services from a central hub. On Pipedream, you can harness this API to create automated workflows that trigger on events like downtime, maintenance, or performance issues. This enables real-time alerts, auto-generated reports, and seamless integration with other tools for incident management or data analysis.

Connect Uptime Robot

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    uptime_robot: {
      type: "app",
      app: "uptime_robot",
    }
  },
  async run({steps, $}) {
    const data = {
      "api_key": `${this.uptime_robot.$auth.api_key}`,
    }
    return await axios($, {
      method: "post",
      url: `https://api.uptimerobot.com/v2/getAlertContacts`,
      headers: {
        "Content-Type": `application/json`,
      },
      data,
    })
  },
})

Overview of Go

You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.

Connect Go

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package main

import (
	"fmt"

	pd "github.com/PipedreamHQ/pipedream-go"
)

func main() {
	// Access previous step data using pd.Steps
	fmt.Println(pd.Steps)

	// Export data using pd.Export
	data := make(map[string]interface{})
	data["name"] = "Luke"
	pd.Export("data", data)
}