Integrate the InfluxDB Cloud API with the Go API

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

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Popular InfluxDB Cloud and Go Actions#

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.

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Overview of InfluxDB Cloud#

Harness the power of InfluxDB Cloud API on Pipedream to build robust data workflows. InfluxDB Cloud, a time-series database, is ideal for managing high-velocity data and extracting insights in real-time. On Pipedream, you can easily trigger workflows based on InfluxDB data, automate data ingestion, and connect with countless other services to analyze, visualize, and act upon your data.

Connect InfluxDB Cloud#

import { InfluxDB } from '@influxdata/influxdb-client';
import { HealthAPI } from '@influxdata/influxdb-client-apis';

export default defineComponent({
  props: {
    influxdb_cloud: {
      type: "app",
      app: "influxdb_cloud",
    }
  },
  async run({steps, $}) {
    // See the Node.js client docs at
    // https://github.com/influxdata/influxdb-client-js
    const influxDB = new InfluxDB(this.influxdb_cloud.$auth.url);
    const healthAPI = new HealthAPI(influxDB)
    
    // Execute a health check to test our credentials
    return await healthAPI.getHealth()
  },
})

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#

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)
}

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