I've been doing K8s consulting for Series B startups and kept seeing the same pattern: massive over-provisioning (like 8GB RAM limits on apps using 500MB), but no easy way to audit it without installing agents like Kubecost or CAST AI.
The problem: Security teams block agent installs for 3-6 months. The waste just sits there burning money.
So I built this. It's a bash script that runs locally using your existing kubectl context. It:
- Compares resource requests vs actual usage (kubectl top)
- Finds orphaned load balancers, unused storage, missing requests
- Anonymizes pod names locally (SHA256 hashes) before exporting
- Generates a report you can share
It's ~300 lines of bash + Python, MIT licensed. You can audit the code before running.
Or clone first if you don't trust curl | bash:
```bash
git clone https://github.com/WozzHQ/wozz.git
cd wozz
bash scripts/wozz-audit.sh
```
Most common finding: "AI-generated YAML" with overly generous limits. ChatGPT/Copilot tends to suggest 8GB when 1GB would work.
I'm doing free analysis for the first 50 clusters (email output to audit@wozz.io). Would love feedback on:
1. Is the anonymization approach sufficient for your security team?
2. What other cost patterns should I detect?
3. Would a GitHub Action version be useful?
rokumar510•2mo ago
I've been doing K8s consulting for Series B startups and kept seeing the same pattern: massive over-provisioning (like 8GB RAM limits on apps using 500MB), but no easy way to audit it without installing agents like Kubecost or CAST AI.
The problem: Security teams block agent installs for 3-6 months. The waste just sits there burning money.
So I built this. It's a bash script that runs locally using your existing kubectl context. It: - Compares resource requests vs actual usage (kubectl top) - Finds orphaned load balancers, unused storage, missing requests - Anonymizes pod names locally (SHA256 hashes) before exporting - Generates a report you can share
It's ~300 lines of bash + Python, MIT licensed. You can audit the code before running.
Try it: ```bash curl -sL https://raw.githubusercontent.com/WozzHQ/wozz/main/scripts/w... | bash ```
Or clone first if you don't trust curl | bash: ```bash git clone https://github.com/WozzHQ/wozz.git cd wozz bash scripts/wozz-audit.sh ```
Most common finding: "AI-generated YAML" with overly generous limits. ChatGPT/Copilot tends to suggest 8GB when 1GB would work.
I'm doing free analysis for the first 50 clusters (email output to audit@wozz.io). Would love feedback on: 1. Is the anonymization approach sufficient for your security team? 2. What other cost patterns should I detect? 3. Would a GitHub Action version be useful?
Code: https://github.com/WozzHQ/wozz Website: https://wozz.io
Happy to answer questions!