with InfluxDB Cloud and Go?
Emit new event when a new bucket is created. See the documentation
Emit new event when a new script is created. See the documentation
Emit new event when a new task is completed. See the documentation
Runs a script and returns the result. See the documentation
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Updates an existing bucket in InfluxDB Cloud. See the documentation
Write data to a specific bucket in InfluxDB Cloud. See the documentation
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.
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()
},
})
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.
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)
}