Auto-Remediation: Powerful, Dangerous, and Necessary

Giving AI the ability to execute commands in production is terrifying.

We know. We built it anyway. Here's how we think about it.

The Case For It

Manual remediation is slow. The average MTTR for Kubernetes incidents is 47 minutes. Most of that time is spent on diagnosis, not the fix itself.

If you already know the root cause and the fix is a known runbook step, why is a human required?

The Case Against It

Because production is not a test environment. A wrong command at the wrong time can make things significantly worse.

# Intended
kubectl scale deployment/payment --replicas=10

# Catastrophic mistake  
kubectl delete namespace production

How We Handle It

Three layers of safety:

1. Pre-approved runbooks only

Tagent never invents remediation steps. It matches incidents to pre-approved runbook templates that your team has reviewed.

2. Blast radius check before execution

Before any command runs, Tagent re-evaluates the blast radius. If the impact scope has changed, it pauses and alerts.

3. Full audit trail

Every action is logged with: who approved it, what was executed, what changed, and what the outcome was.

The Honest Truth

Auto-remediation works well for known failure patterns. It doesn't work well for novel incidents. Tagent is designed to know the difference — and escalate to humans when it doesn't have enough confidence.

That's not a limitation. That's the right design.