Complete newbie here - where to start with connecting two tools?

You've come to the right place, but you're probably asking the wrong question. "Where to start" implies there's a single, correct path, and that's the first trap. The industry is drowning in low-code "integration" platforms and "universal connector" frameworks that promise to solve this problem with a few clicks. They rarely do, at least not in a way that's maintainable, debuggable, or cost-effective for anything beyond a toy project.

The real starting point isn't picking a tool; it's understanding the gap. You have Tool A and Tool B. You need to make them work together. The first step is to map out the contract of each side.

* **What does Tool A provide?** Is it a webhook? A CLI you can call? An API (REST, GraphQL, gRPC)? Does it emit events to a log file or a message queue? Do you have to poll it?
* **What does Tool B consume?** What inputs does it accept? Same list: webhook listener, API, CLI, file drop, queue?

Nine times out of ten, you'll be writing a small piece of middleware—often called "glue code"—to sit between them. This is not a dirty secret; it's the correct engineering solution. Your goal should be to write the simplest, most transparent, and most observable piece of code possible.

Let's take a concrete example. Suppose you want to open a Jira ticket whenever a critical alert fires in Prometheus.

1. Prometheus can send alert notifications to a webhook (the Alertmanager handles this).
2. Jira has a REST API to create issues.

Your "glue" is a small HTTP service that listens for the Prometheus webhook, parses the JSON payload, maps the relevant fields to Jira's API schema, and makes an authenticated POST request to Jira.

Here's a skeletal example in Python using Flask (because it's readable, not because it's the only option):

```python
from flask import Flask, request
import requests
import os

app = Flask(__name__)
JIRA_URL = os.getenv('JIRA_URL')
JIRA_API_TOKEN = os.getenv('JIRA_API_TOKEN')

@app.route('/prometheus-to-jira', methods=['POST'])
def handle_alert():
prom_alert = request.json
# Extract data. This mapping is the crucial business logic.
summary = f"Alert: {prom_alert['alerts'][0]['labels']['alertname']}"
description = prom_alert['alerts'][0]['annotations']['description']

jira_payload = {
"fields": {
"project": {"key": "OPS"},
"summary": summary,
"description": description,
"issuetype": {"name": "Incident"}
}
}

headers = {"Authorization": f"Bearer {JIRA_API_TOKEN}", "Content-Type": "application/json"}
response = requests.post(f"{JIRA_URL}/rest/api/2/issue", json=jira_payload, headers=headers)
return {"jira_response_status": response.status_code}, response.status_code

if __name__ == '__main__':
app.run(host='0.0.0.0', port=5000)
```

You would then deploy this as a container in your cluster, point Prometheus' webhook config at its endpoint, and manage secrets properly. The complexity is in the mapping and error handling (what if Jira is down? What if the payload is malformed?), not in the concept.

So, my advice: stop looking for a "platform" to connect your tools. Start by documenting the inputs and outputs of each tool. Then, write the minimal code to translate between them. Use a simple serverless function, a container, or a script triggered by a cron job. Make sure it logs everything and has clear metrics. This approach will outlast any shiny, proprietary integration vendor.

— ND