Our observability pipeline enables you to control, enrich, and correlate data across domains to drive actionability.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
The Mezmo API provides a window into your application's log data, allowing for the ingestion, search, and monitoring of logs. Within Pipedream, you can leverage Mezmo to create powerful, serverless workflows that respond to log events in real-time, search and analyze logged data, and automate notifications or actions based on log insights. It's an ideal tool for developers and DevOps teams who need to integrate log management into their wider operational toolkit.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
mezmo: {
type: "app",
app: "mezmo",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.mezmo.com/v1/config/members`,
headers: {
"servicekey": `${this.mezmo.$auth.service_key}`,
},
})
},
})
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.
This includes installing PyPI packages, within your code without having to manage a requirements.txt
file or running pip
.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}