UnifiOptimizer

A network admin that remembers. UnifiOptimizer watches a UniFi network the way a good technician would: it keeps a running history, notices when something starts misbehaving, waits to rule out the obvious false alarms, tells you what it thinks is wrong and why, and then checks whether the fix actually held.

This is a ground-up rebuild of UnifiOptimizer. The original tool ran a stateless snapshot on demand and printed a report. UnifiOptimizer keeps state. That one change is the whole point: a controller throws away its fine-grained stats after about a day, so anything you do not collect daily is simply gone, and no snapshot tool can tell you that a port started erroring on Tuesday or that a mesh link has been sliding for a week. UnifiOptimizer can, because it was watching.

The rebuild lives in the netadmin/ Python package and is the whole project now; the original stateless optimizer.py CLI was removed at cutover.

Architecture and design decisions are documented in full at docs/ARCHITECTURE.md, and there is a plain-language, hand-drawn walkthrough at docs/HOW_IT_WORKS.md.

Quick start

pip install unifioptimizer

# see it working on a fictional, PII-free demo network (no controller needed)
netadmin demo-seed --out data/netadmin-demo.db --now $(( $(date +%s) / 300 * 300 ))
NETADMIN_DB_PATH=data/netadmin-demo.db netadmin daemon   # then open http://localhost:8765

# or point it at your own controller: put credentials in data/secrets.env (below)
netadmin daemon

The wheel bundles the compiled dashboard, so pip install alone gives you a working UI with no Node.js. Running from a source checkout instead? See Install — it needs one build step.

What it does

UnifiOptimizer is one Python process that runs a collector, a detection engine, an issue-lifecycle tracker, a health model, and a small web/API server on the same event loop.

• Collects history into a local store. Every 60 seconds it pulls device, client, and health stats over the controller's REST API, listens to the event WebSocket in real time, and runs its own DNS and ICMP probes for the timing the controller does not report. Everything lands in one SQLite file (data/netadmin.db, WAL mode). On a small home network that file sits around 20 MB after a day with a few hundred thousand samples. Counters are stored as per-interval rates, gaps are recorded rather than papered over with zeros, and old data rolls up hourly then daily so year-over-year comparisons stay possible.

• Detects problems, with the false-alarm checks written down. Detectors are deterministic rules, not a black box: static thresholds plus rolling quantile bands off each series' own baseline. A cable detector that fires on a gigabit port stuck at 100 Mbps first confirms the port is genuinely gigabit-capable and the attached device is not a known 100 Mbps class, and it records those checks alongside the finding. That audit trail is what separates an admin from an alarm generator. The catalog covers wired faults (bad cable, duplex, port flapping, PoE budget, STP loops, SFP degradation), WiFi (sticky clients, ping-pong roamers, channel plan, DFS, airtime saturation, mesh backhaul), clients (flaky disconnects with reason-code weighting, DHCP failures), and WAN (ISP degradation, bufferbloat, DNS slowness, WAN flapping).

• Tracks each issue's whole life. A finding does not become a fresh alert every poll. It gets a fingerprint, and one open issue exists per fingerprint. An issue moves pending -> active -> resolving -> resolved, carries a "still occurring, day 5" clock, reopens the same row if it refires within a day instead of spawning a duplicate, and gets suppressed when a bigger fault explains it (a downed switch mutes its own ports' issues). Every state change is logged, so nothing about an issue is untraceable.

• Scores health honestly (Mist-style SLE). Each five-minute bucket, each active client contributes minutes judged pass or fail per service-level expectation (coverage, roaming, capacity, connect, WAN, infrastructure). Every failed minute is pinned to exactly one cause on one device. The headline health number and its explanation are the same query, so "88.6% overall, coverage 84%, 138 failed client-minutes, top offender the Living Room AP" is one click from the score. An idle client with bad signal contributes zero failed minutes, which is what keeps the number impact-weighted instead of theatrical.

• Proposes fixes you approve. When a fix maps cleanly to a controller config change (channel plan, transmit power step-down, removing a misapplied min-RSSI, cycling a PoE port), UnifiOptimizer can render the exact API payload, show you a full before-state, and apply it only when you click. It then watches for a verification window to confirm the issue actually cleared. Nothing applies on its own. See Safety model.

• Explains, when you want a second opinion. For any issue, UnifiOptimizer compiles a markdown dossier: the issue trail, the evidence windows as compact tables, related issues on the same segment, the confounders already ruled out, and the relevant playbook entry. You can hand that to any model yourself (the default, no API key needed), pipe it through GitHub Copilot CLI, or wire an Anthropic key. The investigator explains and correlates; it never applies anything.

• Alerts through Home Assistant. Optional and off by default. Over MQTT discovery it publishes a health sensor, per-severity issue counts, and a binary sensor per active P1/P2 that clears on resolve, so HA automations can notify you on a new critical issue.

How it works

The one idea behind UnifiOptimizer is memory. A controller throws away its fine-grained stats after about a day, so UnifiOptimizer keeps its own history and reads everything else (detection, health, issue tracking) from that. The full walkthrough is in docs/HOW_IT_WORKS.md; the short of it:

It watches, remembers, then tells you.

One issue per fingerprint, not a new alert every poll.

Health you can argue with.

The interface

The web UI ships with the daemon and renders in light and dark. Every screenshot here is from the built-in netadmin demo-seed network: fictional devices, fabricated MACs, documentation-range IPs, so nothing below is a real network.

The issues view is the triage surface: every open finding with its severity, the detector that raised it, the affected device, and how long it has been going.

Open one and it carries its whole lifecycle: the evidence, the false alarms ruled out, and a proposed fix you approve before anything touches the controller.

When you need to hand someone the whole picture, Export report renders a print-ready network assessment: executive summary, topology, per-service health, RF and client analysis, and a walkthrough of every finding. It states its own data window and poll coverage up front, and every number traces to a stored query. There is no sample or projected data.

First run points UnifiOptimizer at your console. Type the address, or let it scan the network for you, and the API key is written to the daemon, never shown in the browser or sent anywhere else.

Two ways to run it

Both modes share every layer. The on-demand mode is literally the daemon's startup path without the scheduler.

Daemon (always-on)

The permanent home. It backfills whatever the controller still retains, then polls, detects, tracks, and scores continuously.

netadmin daemon                 # binds 127.0.0.1:8765 by default
netadmin status                 # hit a running daemon's /api/health
netadmin status --json          # ...and print the raw health payload

Healthy status shows status: ok, collector jobs green with resetting poll ages, websocket.state: running, and backfill: done.

Tech visit (on demand)

One pass over the history the controller still holds, then exit. This is the "walk in, look around, leave a report" mode for a network you are not running the daemon against.

netadmin visit --lookback-days 3   # backfill + detect + report over a 3-day window

The daemon is the recommended mode. A visit can only analyze what the controller still retains (roughly a day of five-minute stats), which is exactly the gap the daemon exists to close.

Install

Requirements

• Python 3.11+
• A UniFi controller (CloudKey Gen2/Gen2+, UDM/UDM-Pro, or self-hosted Network application) reachable on your LAN
• An admin account on the controller, or an API key (UniFi OS consoles on Network 9.x). Read-only controller accounts do not expose the stats and events UnifiOptimizer needs.
• Node.js 18+ only to build the web UI from a source checkout; the published wheel ships it prebuilt, so pip install unifioptimizer needs no Node.js

Get a credential. On a modern UniFi OS console, create a revocable API key (Settings -> Control Plane -> Integrations); on an older or self-hosted controller, use a dedicated local admin account instead. Ubiquiti moves that screen between firmware versions, so rather than guess, run

netadmin detect --host YOUR-CONTROLLER

and it reads your console and prints the exact path to click for your device. The full per-console walkthrough, the version requirements, and what to put in data/secrets.env are in docs/CONTROLLER_SETUP.md.

Install the package

The published wheel ships the compiled dashboard inside it, so end users need no Node.js:

pip install unifioptimizer

From a source checkout, build the dashboard once so the daemon can serve it:

git clone https://github.com/gneitzke/UnifiOptimizer.git
cd UnifiOptimizer
pip install -e .                 # console script + runtime deps
python tools/build_web.py        # compile + bundle the dashboard (needs Node 18+)

./install.sh runs both steps (and creates a venv) in one command. Skipping the build leaves the API and daemon fully working; only the web dashboard waits until you build it. Either way you get the runtime deps: httpx, pydantic, APScheduler, websockets, FastAPI/uvicorn, dnspython, aiomqtt.

Configuration

Two files under data/, both read at runtime, neither ever committed:

• data/secrets.env (chmod 600, gitignored) holds credentials:

  UNIFI_HOST=https://192.168.1.1
  UNIFI_API_KEY=your-api-key            # preferred; or the pair below
  # UNIFI_USERNAME=audit
  # UNIFI_PASSWORD=...
  UNIFI_SITE=default
  

• data/config.yaml, under a netadmin: block, holds structural config: the SQLite path, the API bind (server_host/server_port, default 127.0.0.1:8765), pinned CORS origins, collector cadences, retention tiers, probe targets, and the Home Assistant block. Every key is optional and falls back to the defaults in netadmin/config.py. Two settings are worth checking on first run:

  netadmin:
    probe:
      gateway_ip: 192.168.1.1      # DNS/RTT probe target; auto-discovered if unset
      anchor: 1.1.1.1              # public resolver, the "is it me or my ISP" comparison
    wan_plan_down_mbps: null       # set your plan rate to enable WAN saturation
    wan_plan_up_mbps: null         # and bufferbloat detection (null = those detectors abstain)
  

Environment variables override YAML: DB_PATH, LOG_LEVEL, SITE_ID, SERVER_HOST, SERVER_PORT map directly to the field names (no prefix).

Safety model

Read-only by default. The current build talks to the controller with GETs and a small set of documented read-query POSTs. There is no automatic mutation anywhere in the collector or the daemon.

When the fix engine is enabled, it holds to hard rules:

• The daemon never applies on its own. Every apply is a deliberate human action, a CLI flag or a UI button. There is no scheduler job or callback that applies a fix.
• Dry-run is the default. A dry-run renders the exact API payload without sending it. Applying requires an explicit confirm flag.
• Configuration changes are revertible. An apply captures the full before-state, records the change to the store, and reverts in one click. (A PoE power-cycle is momentary and has no state to restore; it is marked as such.)
• Blast radius is capped. No more than a configured number of devices change per apply, and mesh-uplink APs' min-RSSI is never touched except to remove a misapplied one.

From the CLI a fix is a dry-run by default and applies only with an explicit confirm:

netadmin fix 42                    # render the exact payload; send nothing
netadmin fix 42 --apply --confirm  # apply it, after capturing the before-state
netadmin fix --revert 7            # restore change 7 from its saved before-state

In the web UI the same plan appears under Proposed fix on the issue page: an Apply button behind a confirmation modal, and Revert on any change already applied. The confirm token binds each apply to the exact plan you reviewed, so a device that changed since you looked is refused rather than applied blind.

The daemon's HTTP API has no authentication yet, so it binds loopback only. Do not publish port 8765 to an untrusted network without your own authenticating proxy in front of it; reach a remote daemon over an SSH tunnel. Full policy in SECURITY.md.

What it can and cannot do

Honesty about limits is part of the design.

• Physical faults it flags but cannot fix. A bad cable, a mesh AP with a −81 dBm backhaul, a coverage hole with no better AP for the affected clients: UnifiOptimizer identifies these with evidence and tells you where to look, but the fix is your hands on hardware. The fix engine only changes controller config.

• WAN detection needs your plan rate, and Starlink is noisy. Saturation and bufferbloat detectors compare throughput against your configured plan rate; leave wan_plan_*_mbps null and they abstain rather than guess. Starlink and other variable-rate or CGNAT links make "plan rate" fuzzy and the WAN latency baseline drift, so those detectors lean on trend over absolute thresholds and will be less confident on such links than on a fixed-rate connection.

• Controller version changes what is available. On Network 9.x the stat/event history endpoint was removed; events now come only from the live WebSocket, which means no historical event backlog before the daemon first started watching. Unofficial v2 endpoints are probed at startup and used only when present. When evidence is thin, detectors return UNKNOWN instead of guessing.

• Some things are out of scope, stated plainly. No late-collision detection (no counter exposed), no ARP-conflict visibility, no confident non-WiFi interferer identification or hidden-node detection, no client-side downlink RSSI. UnifiOptimizer infers "unexplained airtime utilization" but will not name the microwave.

• PoE port power-cycle is not revertible. Cycling power to a port is a momentary action with no before-state to restore, so that one fix template is marked non-revertible. Every configuration change (channel, power, min-RSSI) captures its full before-state and reverts in one click.

Deployment

The daemon image, Dockerfile.netadmin, is a single arch-neutral Python image that builds unchanged for both linux/arm64 and linux/amd64. Every dependency ships prebuilt wheels for both, and nothing shells out to an arch-specific binary. There are two documented build paths, each producing the same image:

• amd64 / x86 NAS or server, with docker buildx.

  ./deploy/build-multiarch.sh          # builds arm64 + amd64, inspects, verifies
  

  The script builds both platforms to a local OCI tarball, prints the manifest list to prove both are present, and pushes nothing. Set SMOKE=1 to also load the host-native arch and run an import test. Publish to a registry only when you have one and want to; the script prints the exact --push command.

• arm64 / Apple Silicon, with Apple container. On macOS, Apple's container CLI builds and runs the same image from a git-archive tarball with no secrets in it. Bind the daemon to loopback, hand off the SQLite path, and keep it up with a LaunchAgent; the API is unauthenticated, so never expose it on the LAN.

Whichever way you build it, the container holds no secrets. Credentials and the SQLite store live on a bind-mounted data/ volume, and .dockerignore keeps secrets.env and the database out of every image layer.

Coming from the old tool

The original optimizer.py analyze/optimize CLI has been removed. Its one-shot analysis is now the daemon's continuous job, its HTML report became the web UI and the on-demand tech visit, and its change-application became the approval-gated fix engine. There is nothing to migrate: point UnifiOptimizer at your controller and it starts building the history the old tool never kept.

Testing

python -m pytest tests/netadmin -q       # the rebuild's suite
pip install -e ".[test]"                  # pytest, pytest-asyncio, respx

The pure-logic layers (issue engine, baselines, SLE, detectors) have exhaustive unit tests including confounder cases, controller payloads are replayed from sanitized recorded fixtures, and an end-to-end test drives a synthetic bad week (a cable degrades, a client flaps, firmware regresses) through ingest, detection, and the issue lifecycle. No test ever touches a live controller; every mutating path is exercised against mocks and dry-run rendering only.

Documentation

• docs/ARCHITECTURE.md: the full design. Data model, detector catalog, issue engine, SLE model, fix engine, the whole spine.
• docs/HOW_IT_WORKS.md: a plain-language, hand-drawn walkthrough of the whole thing.
• docs/DESIGN_FOUNDATION.md: the web UI design contract.
• docs/CONTROLLER_SETUP.md: per-console API-key setup (run netadmin detect and it tells you where to click for your device).
• docs/BACKUP.md: backing up and restoring the database.
• SECURITY.md: credential handling and the safety model.
• docs/DEVICE_DATABASE.md: the device-capability database.

License

This project is open source, MIT License, and available for personal and commercial use.

Acknowledgments

Built for the UniFi community, to help people run their networks instead of just photographing them.