My final year dissertation was ACRP — the Automated Chaos Resilience Platform. The brief I set myself: build a chaos engineering environment that runs entirely off-grid, injects real network faults on physical Cisco switches, and produces root cause analysis automatically using a locally hosted Llama 3 8B model. No cloud, no internet route out, by design.

Isolation forces you to understand every dependency

The first real lesson came in week one, when a package install silently failed because pip couldn't reach PyPI. Obvious in hindsight, but it set the tone for the whole project. In an air-gapped environment you can't quietly rely on a CDN or an external API being there — every tool and runtime has to be present and accounted for before you start.

Chaos engineering is mostly disciplined observation

The visible part of chaos engineering is "deliberately breaking things." The actual work is the observation loop: define a steady-state hypothesis, inject a fault, measure the deviation, learn something. My SRE control panel for ACRP wasn't useful because it could trigger a link-down event on a switch interface — it was useful because it could show, in real time, what the blast radius of that event actually was.

The difference between a chaos experiment and random sabotage is documentation. If you can't reproduce the fault and measure its effect, you haven't learned anything.

The AI layer helped more than I expected

Feeding raw Out-of-Band switch logs into a local Llama 3 8B model and getting back a structured fault classification and recommended remediation was the most experimental part of the project — and it worked better than I assumed it would. The honest caveat is that it occasionally produced a plausible-sounding but wrong diagnosis, which is exactly why the platform treats its output as an input to review rather than a final answer.

What I'd do differently

I'd front-load observability. I spent the first stretch of the project on fault injection mechanisms and the later stretch scrambling to add enough instrumentation to actually understand what those faults were doing. That ratio should have been reversed from day one.