A single container that continuously measures the availability and performance of https://mithal.space and serves a live dashboard of the results on port 8080.

q5-mithal-dashboard/
├── collector/
│   ├── collect.py             # measures latency, uptime, DNS, TLS, search — every 60s
│   └── requirements.txt       # requests (pinned); everything else is stdlib
├── dashboard/
│   ├── index.html             # self-contained dashboard (Chart.js from CDN)
│   └── data/metrics.json      # rolling 48h JSON array, written by the collector
├── start.sh                   # entrypoint: collector in background + static server
├── Dockerfile
└── README.md

Why data/ lives inside dashboard/: the dashboard directory is the web root, so the page fetches data/metrics.json from its own origin. One container, one port, no CORS, no API layer.

1. What is collected

Every 60 seconds collector/collect.py appends one record to the JSON array:

{
  "ts": "2026-07-26T15:46:40.381676+00:00",
  "up": true,
  "code": 200,
  "latency_ms": 848.58,
  "dns_ms": 0.67,
  "ssl_days_left": 50,
  "search_ms": 1056.08
}

Field	How it is measured
`latency_ms`	timed `GET https://mithal.space`, 10 s timeout, redirects followed
`up`	`true` when the status code is 200–399
`code`	the HTTP status code — `null` when the connection itself failed
`dns_ms`	timed `socket.getaddrinfo("mithal.space", 443)`
`ssl_days_left`	TLS handshake to `mithal.space:443`, cert `notAfter` parsed → days remaining
`search_ms`	timed `GET https://mithal.space/search?q=test` (`null` if it errors or returns ≥ 400)

Every measurement is independent: a failure records null for that field only and never aborts the run or crashes the loop. Records older than 48 hours are pruned on each write, and the file is written atomically (temp file + rename) so the dashboard never reads a half-written array.

Configuration — constants at the top of collect.py, all overridable by env var:

Variable	Default	Meaning
`TARGET_URL`	`https://mithal.space`	site under test
`SEARCH_URL`	`https://mithal.space/search?q=test`	search endpoint to time
`INTERVAL_S`	`60`	seconds between collections
`TIMEOUT_S`	`10`	per-request timeout
`RETENTION_HOURS`	`48`	how much history to keep
`METRICS_FILE`	`dashboard/data/metrics.json`	output path

2. Run locally (without Docker)

cd q5-mithal-dashboard
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r collector/requirements.txt

One-shot collection (useful as a smoke test or under cron):

python collector/collect.py --once

Continuous collection every 60 s — leave this running:

python collector/collect.py

In a second terminal, serve the dashboard (the data/ directory must be inside the served root, which it is):

cd q5-mithal-dashboard/dashboard && python -m http.server 8080

Open http://localhost:8080/index.html.

Opening index.html straight from disk does not work — browsers block fetch() over file://. The page detects this and shows an explanatory banner instead of failing silently.

3. The dashboard

Element	Detail
Status badge	green `UP` / red `DOWN` from the newest record, with HTTP code and timestamp
Uptime tile	`up_checks / total_checks × 100` over the last 24 h, one decimal
TLS card	"X days remaining" — green > 30, yellow 8–30, red ≤ 7 (`Expired` at ≤ 0)
Latest response	newest `latency_ms`, with `search_ms` and `dns_ms` underneath
Chart	`latency_ms` (solid blue) and `search_ms` (dashed purple) for the last hour; failed checks draw gaps, red points mark down checks
Table	last 10 checks — time, ✅/❌, code, latency, DNS, search
Refresh	re-fetches every 60 s; last-updated clock in the header

Empty, missing, or corrupt data renders a "no data yet" state on every tile plus a banner explaining what to do — it never throws.

To point the page elsewhere, edit the one constant at the top of the <script>:

const DATA_URL = 'data/metrics.json';

4. Build the image

The container runs the collector in the background and serves the dashboard in the foreground, both from one process tree (start.sh):

docker build -t mithal-monitor:latest ./q5-mithal-dashboard

docker run --rm -p 8080:8080 --name mithal-monitor mithal-monitor:latest

Open http://localhost:8080/index.html. The first record appears within a few seconds of startup, then one per minute.

Image notes:

python:3.12-slim, non-root user appuser (uid 10001) owning the served tree so the collector can write into it.
requirements.txt installed before the code is copied, for layer caching.
start.sh restarts the collector if it ever exits, and traps SIGTERM/SIGINT so the container stops promptly.
HEALTHCHECK fetches the dashboard page itself.
Metrics live inside the container's filesystem, so history resets on redeploy. That is intentional for this exercise; to keep history across restarts, mount a volume at /app/dashboard/data (this is exactly what Ghaymah Block Storage is for — see Q4).

5. Deploy to Ghaymah

This deployment uses Docker Hub namespace agamy74.

docker login

docker tag mithal-monitor:latest docker.io/agamy74/mithal-monitor:latest

docker push docker.io/agamy74/mithal-monitor:latest

On Apple Silicon / ARM, build for the platform Ghaymah runs:
docker buildx build --platform linux/amd64 -t docker.io/agamy74/mithal-monitor:latest --push ./q5-mithal-dashboard

Make sure the Docker Hub repository is public — Ghaymah pulls it anonymously.

Then, in the Ghaymah dashboard:

Field	Value
Container Image URL	`docker.io/agamy74/mithal-monitor:8bc563f`
Application Name	`mithal-monitor`
Port Number	`8080` (matches `EXPOSE`)
Public Access	enabled
Environment Variables	(optional) `INTERVAL_S=60`, `TARGET_URL=https://mithal.space`, `SEARCH_URL=https://mithal.space/search?q=test`

Click Deploy, then open https://mithal-monitor-292f00f076b1.hosted.ghaymah.systems/index.html and screenshot the live dashboard. Leave it running so the 24 h uptime tile and the hourly chart fill with real history before submission.

6. Local verification performed

Measured against the live site on 2026-07-26:

Check	Result
`collect.py --once` against mithal.space	`UP code=200 latency=2693ms dns=7.07ms search=866ms ssl=50d`
60 s loop (run at 6 s for testing)	5 further records appended, pruning and atomic writes working
Failure path (unreachable host)	recorded `up:false` with `code/latency_ms/dns_ms/ssl_days_left/search_ms` all `null`, exit 0, no crash
Dashboard against real `metrics.json`	badge UP, uptime 100.0% (6/6), TLS card "50 days — Healthy" in green, chart with both series, 6-row table; no console errors
Dashboard with the data file removed	"no data yet" state on every tile + banner, no crash
`docker build`	not run — the local Docker daemon was not running; build with the command in §4 before pushing

The dashboard/data/metrics.json in this repo holds those first real samples; the collector prunes anything older than 48 h automatically.

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