Http

Monitor Kubernetes services & pods with Prometheus and send alerts to Slack

Maintain high availability for your Kubernetes clusters by automatically piping Prometheus metrics into context-rich Slack notifications. This proactive monitor tracks pod readiness, scheduling delays, and container restart spikes to give your DevOps team immediate visibility into infrastructure health. By summarizing service endpoint changes and resource issues, it ensures your technical team stays informed without drowning in alert noise.

Run this with your team's AI

What This Recipe Does

The Service and Pods Discovery automation provides real-time visibility into your cloud infrastructure by automatically mapping and monitoring the health of your digital services. Instead of manually checking server statuses or navigating complex developer consoles, this workflow continuously audits your environment to identify active pods and services. By centralizing this data, business operations teams can ensure that customer-facing applications are running optimally and that infrastructure resources are being utilized efficiently. This automated discovery process eliminates the visibility gap between technical infrastructure and business oversight, allowing for faster response times to service interruptions and better resource planning. It transforms raw technical data into a clear inventory of your operational state, ensuring that your team always has an accurate picture of the systems powering your business without requiring manual manual intervention or specialized technical knowledge.

What your team gets

Something anyone can use

Forms and dashboards, so it is not a script only one person understands

It keeps running

Runs on your schedule in the cloud, so it does not stop when a laptop closes

Your other tools can call it

Endpoints, so the rest of your stack can trigger the same work

Accounts connected once

Http connected for the team, not per person

How It Works

  1. 1

    Open the recipe and connect your accounts

    Connect Http once, in your team cloud, and nobody has to do it again on their own machine

  2. 2

    Tell your own agent what is different about your process

    Claude, ChatGPT, Cursor, whichever your team already uses. It adapts the recipe to how you actually work

  3. 3

    Run it, then leave it running

    It lives in your team cloud, so it keeps going after you close the laptop and every teammate's AI can use it

Who Uses This

Frequently Asked Questions

Do I need to manually trigger the discovery process?

No, the automation is built with a schedule trigger that runs at defined intervals to ensure your service inventory is always current.

Can this monitor services across different environments?

Yes, the workflow can be configured to fetch data from various endpoints, allowing you to track services in production, staging, and development environments simultaneously.

What information is captured during the discovery process?

The automation identifies active services and their associated pods, providing a snapshot of the current operational status and infrastructure health.

Is technical expertise required to view the results?

While the setup connects to your infrastructure, the output is designed to be consumed by business users as a clear list of active services and operational pods.

Coming from n8n?

This recipe uses nodes like ScheduleTrigger, HttpRequest, Code, StickyNote and 1 more. On Runwork, you don't need to learn n8n's workflow syntax. Describe what you want to your own AI agent in plain English.

ScheduleTrigger HttpRequest Code StickyNote Merge

Based on n8n community workflow. View original

Related Recipes

Run this with the AI your team already uses

Your agent adapts it, your team cloud keeps it running, and everyone's AI can find it.

Open this recipe in Runwork