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devopssessionsjvr/agentic-ai-demo

Analysis updated 2026-05-18

★ 47HTMLAudience · ops devopsComplexity · 4/5Setup · hard

TLDR

A demo project simulating a DevOps pipeline where an AI agent detects issues and proposes fixes automatically.

Mindmap

mindmap
  root((agentic-ai-demo))
    What it does
      Simulates CI CD pipeline
      AI proposes fixes
      GitOps with ArgoCD
    Tech stack
      HTML
      Kubernetes
      ArgoCD
    Use cases
      Learn DevOps concepts
      See AI assisted fixes
      Demo GitOps workflow
    Audience
      DevOps engineers
      Learners
    Concepts
      CI CD
      GitOps
      Kubernetes rollouts

Code map

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What do people build with it?

USE CASE 1

Learn how CI/CD, GitOps, and Kubernetes rollouts fit together in one pipeline

USE CASE 2

See a simulated example of an AI agent proposing a pull request to fix a detected issue

USE CASE 3

Explore how ArgoCD applies a Git repository's desired state to a live system

USE CASE 4

Use as a teaching demo for AI-assisted DevOps automation

What is it built with?

HTMLKubernetesArgoCD

How does it compare?

devopssessionsjvr/agentic-ai-demosunrisefromdark/agentradarjaccen/awesome-gaussian-skills
Stars474845
LanguageHTMLHTMLHTML
Setup difficultyhardmoderateeasy
Complexity4/53/52/5
Audienceops devopsresearcherresearcher

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Demonstrates concepts that in practice require a Kubernetes cluster and ArgoCD setup.

In plain English

This repository is a demo project that simulates a DevOps pipeline with AI-assisted automation. DevOps refers to the set of practices for automating the building, testing, and deployment of software. The demo combines several common DevOps concepts: CI/CD pipelines (automated workflows that build and test code on every change), GitOps using ArgoCD (a practice where the desired state of a system is stored in a Git repository and automatically applied), Kubernetes rollouts (the process of deploying updated container-based applications), and AI-generated pull requests that automatically fix detected problems. The idea is to show how an AI agent can participate in the deployment process by detecting issues and proposing fixes as code changes, rather than requiring a human to manually diagnose and patch failures.

Copy-paste prompts

Prompt 1
Walk me through how this demo simulates an AI agent fixing a broken deployment.
Prompt 2
Explain what GitOps with ArgoCD means using this repository as an example.
Prompt 3
How does this project combine CI/CD, Kubernetes rollouts, and AI-generated pull requests?
Prompt 4
What would I need to turn this simulation into a real pipeline?

Frequently asked questions

What is agentic-ai-demo?

A demo project simulating a DevOps pipeline where an AI agent detects issues and proposes fixes automatically.

What language is agentic-ai-demo written in?

Mainly HTML. The stack also includes HTML, Kubernetes, ArgoCD.

How hard is agentic-ai-demo to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is agentic-ai-demo for?

Mainly ops devops.

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This repo across BitVibe Labs

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