ipx/.claude/skills/ipx-prod-check/SKILL.md

name, description

name	description
ipx-prod-check	Look for problems in production ipx (the iPX container on Tower) from its logs in Loki, its traces in Tempo and its metrics in Prometheus, and file what is found as Gitea issues. Use when asked to check on production, look for issues or errors in ipx, see why something is slow or failing in production, review the logs, or investigate a report about the live site.

Checking production ipx

Production logs one JSON object a line (IPX_LOG_FORMAT=json), which Alloy ships to Loki under {container="iPX"}, and sends traces to Tempo tagged resource.deployment.environment.name="production". Anything without that tag is a daemon run by hand, not production. Loki and Tempo publish no query port, so use the script beside this file:

Q=.claude/skills/ipx-prod-check/query.py
$Q logs    '<LogQL>'           [since]   # lines, newest first (500 at most)
$Q metric  '<LogQL metric>'    [since]   # $range becomes `since`
$Q traces  '<TraceQL>'         [since]   # slowest first
$Q trace   <trace id>                    # one trace as a tree, with its log lines
$Q prom    '<PromQL>'          [since]   # Prometheus, now; $range becomes `since`

since is 1h, 24h, 7d. Default to 24h; widen it to see whether something is new.

What the log carries

Every line has timestamp, level, message and target; lines inside a span have span (the innermost: {"name":"feed","feed":"x"}). Loki's | json flattens it to span_name, span_feed. Lines inside a traced span, requests and scans, also carry trace_id and span_id: give the trace_id to $Q trace to see the whole request or scan. (From 2026-09-29 16:30 UTC; before that, lines had no trace id, the access log's time was ms, and each event was logged twice, words under ipx::scan and fields under ipx::io.)

target	fields	what
ipx::http	method, path, route, status, duration_ms	one per web request; route is the pattern, empty for an unrouted path
ipx::scan	ev and the event's own: feed, new, downloaded, failed, bytes, msg, url, feeds, reason, from, to; on a failure error.type and, from an HTTP error, http.response.status_code	the daemon's events, one line each, in words; warnings are feed and download failures
ipx::io	ev, feeds, pending, downloaded on the status reply	commands arriving (-> {...}) and the healthcheck's answer
ipx	message, sometimes fields	start-up, shutdown, account and config messages
ipx::client	ev, user, feed, enclosure, deadair; msg, src, line on an error; ms on a timing	what the page reports from the browser (#190): page_error, rejection and player_error as warnings; play_start (ms from play to sound) and stall (ms waiting mid-play) as info. Lines carry the trace of the action in the page: its API requests send traceparent, one trace id per tap or key

Events (ev): feed_start, feed_done (new, downloaded, failed, torrents), feed_skip (not due, routine), feed_error (msg), feed_moved (from, to: a permanent redirect followed, the address updated), download_done (bytes), download_error (msg, url), torrent_deferred, reaped, scan_done (feeds checked), reap_done, status (feeds, pending, downloaded: the healthcheck's, every 30s), error (msg).

error.type is the HTTP status (404, 503) or one of dns, redirect_loop, timeout, tls, not_a_feed, site_message, connect, parse, other; Loki's | json names it error_type.

Filter on the text before | json where you can (|= "\"ev\":\"feed_error\""): it is much cheaper than parsing every line. Lines before 2026-09-29 14:00 UTC are text, not JSON, and | json | __error__="" drops them.

What Prometheus carries

The daemon's own state between requests, which no log line or trace holds (#194): ipx serves /metrics on [web] metrics_bind (production: 192.168.1.130:9187, LAN only), on a thread and port of its own, from memory alone, and Prometheus scrapes it every 15 s as job="ipx". Kept from 2026-10-11 15:15 UTC. All gauges:

metric	what
ipx_db_connections{state="in_use"|"idle"}, ipx_db_connections_max	the database pool: in use reaching the max means requests and scans wait for a connection
ipx_worker_queue	commands waiting for the sequential worker (scans, downloads, adds)
ipx_event_listeners	open pages and socket clients on the live-update stream
ipx_torrent_slots_free	of 2
ipx_deadair_playing	episodes being played through DeadAir's playlist
ipx_runtime_workers, ipx_runtime_tasks, ipx_runtime_queue	tokio: threads, live tasks, tasks waiting for a thread
ipx_process_resident_bytes, ipx_process_open_fds	memory and open files and sockets
ipx_uptime_seconds, ipx_build_info{version}	since the daemon started; what runs

The checks

Run these, then read the lines behind whatever stands out. Most of the time is in the reading: a count says something happened, the lines and traces say why.

1. Warnings and errors, grouped. What went wrong, how often, and since when.

   $Q metric 'sum by (target, message) (count_over_time({container="iPX"} | json | __error__="" | level=~"WARN|ERROR" [$range]))'
   

   Feed and download failures name the feed in the message; group them in the next check instead.

2. Failing feeds and downloads.

   $Q metric 'sum by (feed, error_type) (count_over_time({container="iPX"} |= "\"ev\":\"feed_error\"" | json | __error__="" [$range]))' 7d
   $Q metric 'sum by (feed, error_type) (count_over_time({container="iPX"} |= "\"ev\":\"download_error\"" | json | __error__="" [$range]))' 7d
   

   Tell the publisher's problems from ipx's. A 404, 410, DNS failure or 503 from the feed's own server is the publisher (worth saying, since the feed may have moved; one issue for a feed that has been dead for days, not for a 503 once). A parse error on a feed that loads in a browser, a redirect loop ipx should follow, or the same failure on many feeds at once is ipx.

3. Server errors and slow requests.

   $Q metric 'sum by (method, route, status) (count_over_time({container="iPX"} |= "\"target\":\"ipx::http\"" | json | __error__="" | status >= 500 [$range]))'
   $Q metric 'topk(10, quantile_over_time(0.95, {container="iPX"} |= "\"target\":\"ipx::http\"" | json | __error__="" | route != "" | route != "/api/events" | unwrap duration_ms [$range]) by (method, route))'
   

   Any 5xx is worth a look. 401s are people signing in, not a problem unless one address is hammering. For a slow route, find its traces (check 5) and see which span holds the time.

4. Is the worker keeping up? Scans should finish regularly, the queue should drain, and the daemon should not be restarting on its own.

   $Q metric 'sum(count_over_time({container="iPX"} |= "\"ev\":\"scan_done\"" [$range]))' 6h
   $Q logs '{container="iPX"} |= "\"ev\":\"status\"" | json | line_format "{{.timestamp}} pending={{.pending}} downloaded={{.downloaded}}"' 6h
   $Q logs '{container="iPX"} |= "daemon started"' 7d
   

   A daemon started not matched by a deploy (see git log and the image's build time) is a crash or an OOM kill: check docker inspect iPX -f '{{.State.OOMKilled}} {{.RestartCount}}' and the lines just before it. A pending count that only grows means downloads are not keeping up or not running.

   Since 2026-10-02 the daemon sleeps until the next feed is due (at most 10 minutes) instead of scanning every minute (#114), so expect tens of scans in 6 hours, not 360, nearly all with feeds above 0; none at all for over 10 minutes means the worker is stuck. And pending is the real queue (#113): files a scan will download on its own. Back-catalogue files are held, listed but not counted, so it is usually 0 or a handful.

5. Slow and failed traces.

   $Q traces '{resource.deployment.environment.name="production" && duration > 5s}'
   $Q traces '{resource.deployment.environment.name="production" && status = error}'
   $Q trace <id>
   

   Scans (scan) are long by nature, since they fetch many feeds one after another: look for one feed or fetch span holding most of it, or a download far slower than its size explains. A web request over a second is worth a look; the trace shows whether the time is in the handler or a scan it waited on.

6. The daemon's state, from Prometheus. Pressure and leaks that requests and traces only hint at.

   $Q prom 'up{job="ipx"}'
   $Q prom 'max(max_over_time(ipx_db_connections{job="ipx",state="in_use"}[$range]))' 24h
   $Q prom 'max(max_over_time(ipx_db_connections_max{job="ipx"}[$range]))' 24h
   $Q prom 'max(max_over_time(ipx_worker_queue{job="ipx"}[$range]))' 24h
   $Q prom 'max(max_over_time(ipx_runtime_queue{job="ipx"}[$range]))' 24h
   $Q prom 'max(resets(ipx_uptime_seconds{job="ipx"}[$range]))' 24h
   $Q prom 'ipx_process_resident_bytes{job="ipx"} - ipx_process_resident_bytes{job="ipx"} offset $range' 24h
   $Q prom 'ipx_process_open_fds{job="ipx"} - ipx_process_open_fds{job="ipx"} offset $range' 24h
   $Q prom 'ipx_runtime_tasks{job="ipx"} - ipx_runtime_tasks{job="ipx"} offset $range' 24h
   

   up 0 means Prometheus cannot reach the port: the container is down or metrics_bind is unset. Connections in use at the pool's max (10 on Postgres) means something is waiting for one: find the slow requests or scan of that time in check 3 and 5. A worker queue that only grows means downloads are not keeping up, or the worker is stuck on one job. A runtime queue above 0 for more than a scrape or two means every thread is busy: something is blocking a thread or burning one. Memory, open files or tasks only climbing across a day with no restart is a leak (a file or socket not closed, a task never ending); a step after a deploy is not. A reset of the uptime is a restart: match it with a deploy, or it is a crash (check 4).

Also check the container itself, since Loki cannot see a daemon that is not running:

docker ps --filter name=iPX --format '{{.Status}}'
docker logs --since 10m iPX 2>&1 | tail -5

docker logs and docker exec iPX ipx ... are fine. Do not query production's Postgres directly: ask the user if a question needs the database.

What to do with what you find

Follow the repository's rules in CLAUDE.md: every problem found gets a Gitea issue, with a closed stdin and a timeout on tea. Before filing, list the open issues and do not file one twice; comment on the existing issue with the new evidence instead.

R="--login git.sdf1.net --repo rays/ipx"
t() { timeout 30 /src/tea "$@" < /dev/null; }
t issues list $R --state open
t issues create $R -t "<what is wrong, as the user would notice it>" -L bug -d "<what, where, since when, how often, the query or trace id that shows it>"

Put in each issue what would let someone pick it up cold: the LogQL or TraceQL that shows it, a trace id, the first time it was seen and how often. A publisher's dead feed is worth one issue saying so (the user may want to unsubscribe or find its new address); a single 503 is not.

Finish with a short report to the user: what is healthy, what is wrong (with the issue numbers), and anything you could not tell from logs and traces alone. Do not fix things unless asked; the check is for finding them.

When the checks come back empty

Check that there is data before concluding all is well: $Q metric 'sum(count_over_time({container="iPX"} [1h]))' 1h should be in the hundreds or more. Nothing at all means Alloy is not shipping (it can take a few minutes to pick up a container after a deploy), or the container is down.