Kairos AI

Kairos AI is a secure infrastructure automation platform that uses AI agents to manage cloud and DevOps operations, reducing manual toil while keeping teams in contro

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Kairos (INFRAai) — The Agent That Handles Ops While You Sleep

Inspiration

Most infrastructure failures are not hard to fix — they’re hard to detect quickly, triage correctly, and execute safely.

I was tired of the DevOps reality:

  • getting woken up at 3 AM because a VM hit 95% CPU
  • watching engineers scramble when production traffic gets blocked
  • debugging incidents that follow the same repetitive playbook

DevOps today is mostly reactive: we wait for things to break, then scramble to fix them.

So I built Kairos (INFRAai) — a DevOps agent that monitors cloud infrastructure 24/7, detects incidents, recommends safe fixes, and can execute them autonomously with human approval.

What I Learned

This project taught me that agentic AI is not just prompting — real autonomy requires structure, state, safety, and feedback loops.

Key things I learned:

  • How to design a human-in-the-loop system for risky infrastructure actions
  • How to use structured JSON output from an LLM instead of unreliable text parsing
  • How to build an alert → decision → action pipeline using Cloud Monitoring webhooks
  • How to keep Terraform changes consistent with existing state (no regeneration chaos)
  • How to verify actions using metrics, not assumptions

How I Built It

Kairos is designed as a pipeline of connected layers:

1) Monitoring Layer

  • GCP Cloud Monitoring detects incidents (high CPU, downtime, firewall blocks)
  • Alerts are sent to the backend using webhooks

2) Backend (FastAPI)

  • Receives webhook payloads
  • Normalizes them into a standard incident schema
  • Stores incident logs and execution state in SQLite + Redis

3) LLM Decision Layer

  • Gemini 2.5 Pro analyzes each incident and outputs a structured decision:
    • severity (Low/Medium/High)
    • recommended action
    • reasoning
    • confidence score
    • whether approval is required

4) Human Approval Layer (Telegram)

  • High-risk actions are sent to Telegram
  • The user can approve by replying "1"
  • The user can stop all autonomy instantly using "STOP AUTONOMY"

5) Execution Layer

  • Executes actions via:
    • Terraform modifications (state-preserving)
    • direct GCP API calls (fast operational actions)

6) Feedback Loop

After every action, Kairos checks metrics again to confirm the problem is actually resolved.

Challenges I Faced

1) LLM Output Reliability

Early versions sometimes produced JSON that looked correct but had missing or hallucinated fields.
I solved this using strict Pydantic schema validation and enforcing structured outputs.

2) Terraform State Consistency

Scaling or changing infra safely required preserving Terraform state.
I avoided regeneration and made the agent perform targeted modifications only.

3) Cloud Monitoring Webhook Complexity

GCP monitoring alerts come as deeply nested JSON and vary across incident types.
I built a normalization layer that consistently extracts:

  • policy name
  • resource
  • metric
  • value
  • timestamp

4) Trust and Safety

The biggest challenge was making an autonomous infra system that users can trust.
I solved this using:

  • human approval gates
  • confidence scores
  • reasoning logs
  • a kill-switch that halts execution instantly

Math / Monitoring Logic

Kairos triggers a CPU incident using a simple threshold rule:

$$ CPU_usage = \frac{\text{busy_time}}{\text{total_time}} \times 100 $$

An alert triggers when:

$$ CPU_usage > 90\% $$

After applying an action (like scaling), Kairos re-checks the metric and confirms recovery.

Future Improvements

  • Multi-cloud support (AWS + Azure)
  • Predictive incident prevention using historical metrics
  • Rollback intelligence if an action makes things worse
  • Cost optimization agent for continuous rightsizing
  • Slack + Teams integration

Built With

  • Gemini 2.5 Pro
  • Terraform
  • Google Cloud Platform (Compute Engine, Cloud SQL, VPC, Monitoring)
  • FastAPI + Pydantic
  • SQLite + Redis
  • Telegram Bot API
  • React + TypeScript + Monaco Editor
  • Docker + ngrok

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