Geckoboard
Communicate, don't complicate. We help teams & businesses share data, metrics and KPIs in a way anyone can understand.
Integrate the Geckoboard API with the Go API
Setup the Geckoboard API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Geckoboard and Go remarkably fast. Free for developers.
Popular Geckoboard and Go Actions#
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Overview of Geckoboard#
The Geckoboard API grants you the power to craft custom dashboards that display key metrics and performance indicators for your business. With this API, you can push data to widgets, create and manage dashboards, and automate the sharing of insightful data visualizations. When leveraged through Pipedream, you can build workflows that connect Geckoboard with various other apps, enabling real-time data updates, integrating with your current tools, and powering automated reporting processes.
Connect Geckoboard#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
geckoboard: {
type: "app",
app: "geckoboard",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.geckoboard.com/datasets`,
auth: {
username: `${this.geckoboard.$auth.api_key}`,
password: ``,
},
})
},
})
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)
}