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dot-ai-operate

Automate Kubernetes Day 2 operations via natural language intents.

2|Updated Dec 8, 2025
Search Tags:#automation#devops#ai#kubernetes#operations#application management
One-click install
npx skills add https://github.com/vfarcic/dot-ai-website --skill dot-ai-operate
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dot-ai-operate
Source: https://github.com/vfarcic/dot-ai-website/tree/main/.claude/skills/dot-ai-operate
Command: npx skills add https://github.com/vfarcic/dot-ai-website --skill dot-ai-operate

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill streamlines Day 2 operations for Kubernetes applications, automating complex tasks like updates, scaling, and rollbacks through natural language commands.

Core Features & Use Cases

  • Automated Operations: Manage application lifecycle (updates, scaling, deletion) via conversational AI.
  • Intelligent Analysis: Analyzes current state, applies organizational policies, and validates changes.
  • Safe Execution: Performs dry-runs before executing operations to ensure safety and compliance.
  • Use Case: An operator can ask the AI to "scale the 'frontend' deployment to 5 replicas and then update its image to v1.2.0", and the AI will handle the entire process.

Quick Start

Use the dot-ai operate skill to scale the 'backend' deployment to 3 replicas.

Frequently Asked Questions about dot-ai-operate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate Kubernetes Day 2 operations like scaling and updates using natural language?▼

You can automate Kubernetes Day 2 operations by issuing natural language intents, which the AI translates into state analysis, dry-run validation, and safe execution for tasks like updates, scaling, and rollbacks.

What is the safest way to rollback or delete a Kubernetes application via conversational AI?▼

The safest way to rollback or delete a Kubernetes application is to use a process that analyzes the current state and validates all changes via a dry-run before executing the approved operations safely.

Can I apply organizational patterns and policies when scaling Kubernetes deployments?▼

Yes, when scaling Kubernetes deployments, the system analyzes the current state and applies your organizational patterns and policies to ensure the operation is compliant before validating via dry-run.

How do Kubernetes operations tools validate changes before executing updates?▼

Kubernetes operations tools validate changes by performing a dry-run to analyze the current state and ensure safety, applying organizational policies, and executing the approved operations only after validation passes.

Do I need to manually write scripts for Kubernetes application lifecycle management tasks?▼

No, you do not need to manually write scripts for Kubernetes application lifecycle management tasks like updates, scaling, and enhancements, as these can be fully automated using natural language commands.

What are the limitations of using AI to manage Kubernetes application operations?▼

A limitation is that the AI relies on analyzing the current state and dry-run validation, meaning operations require an approval step before execution, which may not suit fully autonomous continuous deployment pipelines.

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