Three changes: detection windows tightened, a Signal transport deployed, and
alerts attached to all 84 non-transport endpoints.
── Failing faster ──────────────────────────────────────────────────────────
The heartbeat is a TICKER, not a deadline: Gatus wakes every interval and asks
"did anything arrive in the last interval", so real detection is 1-2x the
window. And a window can only ever be as tight as the push frequency - which is
why two checks moved rather than just having their numbers changed.
liveness, cpu, ups, service-health, probes 16m -> 11m
disk, zfs daily/30h -> 6-hourly/7h
backup store + pull job daily/30h -> 6-hourly/7h
DNS records 24h -> 6h
backup dump 30h -> 26h
backup-dump stays slow because the dump genuinely is daily. The store-side check
catches the same fault within 6h by reading the source's dump timestamp out of
the artefact filename, so 26h is a backstop rather than the primary signal.
── Thresholds differ by check type, deliberately ───────────────────────────
`failure-threshold` counts consecutive failures, but "consecutive" is a
different amount of wall-clock time per check: a push endpoint produces one
failure per heartbeat window, a pulled one per interval. The default of 3 would
mean 33 minutes on an 11m heartbeat and over a day on a 7h one.
More importantly the heartbeat window ALREADY encodes the tolerance - an 11m
window on a 5-minute push is exactly "one missed push forgiven" - so stacking a
threshold of 3 triples a tolerance that was already chosen. Hence:
push/heartbeat endpoints failure-threshold 1
pulled, 5m (public) failure-threshold 3 (= 15 minutes)
pulled, 6h/24h (dns, domain) failure-threshold 1
── The Signal transport ────────────────────────────────────────────────────
roles/signal_api runs signal-cli-rest-api on the observability host, pinned by
digest, MODE=native.
It publishes NO PORTS. The API has no authentication of any kind - anything that
reaches it can send messages as you and read your Signal. Gatus talks to it over
a shared docker network by service name, which is also WHY the network exists:
Gatus runs in a container, so the host's loopback is unreachable from it and a
port published on 127.0.0.1 would not have worked.
MODE=native and not json-rpc because this VPS has 464MB of RAM and already runs
Gatus and Caddy. The json-rpc modes hold a resident JVM; native runs a binary
per request, and alerts are rare enough that startup cost per alert is the right
trade.
Monitored - Gatus polls /v1/health over the same network path the alerts take,
so it proves the delivery route rather than mere container liveness. Deliberately
NOT backed up: the data directory holds Signal private keys and the recovery
path is to link the device again from the phone.
Neither the signal-api endpoint nor Gatus's self-check carries a Signal alert.
If either is down, Signal is precisely what cannot deliver the alert.
── Four traps hit while linking, all now in the role README ────────────────
* /v1/qrcodelink is BROKEN in native mode - returns "no data to encode" while
the binary itself emits a perfectly good URI. Not worked around by switching
MODE, which would put a JVM in the path of every alert permanently.
* The data dir must be owned by uid 1000, not root. A root-owned 0700 dir
cannot be traversed by the container user, so linking silently never
completes and /v1/accounts returns "Failed to read local accounts list".
* `docker exec` runs as ROOT while the service runs as uid 1000, so without
--config the account is written to /root/... on the container's ephemeral
layer. It reports success and is destroyed on the next recreate.
* The phone reporting "network error" was IPv6: chat.signal.org resolves to
dualstack AAAA records first, the container has no IPv6 address, and this
host's IPv6 path is broken - the same edge that 404'd the Go tarball. Fixed
with a mounted gai.conf that prefers IPv4.
Verified: provider loads (configuredProviders=[signal]), a test message was
delivered and confirmed received, 84 endpoints carry alerts, 86 UP / 0 DOWN.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Five checks, 27 endpoints, replacing what Uptime Kuma used to watch:
is it up every 5min, all hosts
is disk full daily, all hosts
is CPU hot every 5min, nodito
is ZFS broken daily, nodito
is UPS online every 5min, nodito
Two roles, kept separate so neither knows about the other - they meet at a URL
and a token, the same way caddy_site and each service meet at a vhost:
roles/gatus_endpoint runs on the observability host, writes ONE file into
/opt/gatus/config/endpoints/. Gatus merges every *.yaml
there and appends lists, so callers compose without
coordinating.
roles/healthcheck runs on the monitored host: a check script, a systemd
service, a timer, and an optional push. Ships a library
of check bodies under templates/checks/.
Everything PUSHES. Gatus never reaches out, which matters because nodito and its
VMs are behind NAT, and because four of the five checks are internal state with
no pollable surface at all. Liveness pushes too, deliberately: a heartbeat proves
the host is running AND can reach the internet, where an ICMP probe from one
vantage point only proves it answers pings from there. And since Gatus alerts
when a heartbeat window expires, a check that stops running raises the alarm by
itself - a dead timer looks exactly like a dead host, which is the correct
reading.
One bearer token per host, generated straight into the vault and never printed.
A token only writes results for its own host's endpoints, so a compromised host
can lie about itself, which it could do anyway.
Three things learned from the source that shaped this:
* Gatus polls its own config every 30s and reloads
(main.listenToConfigurationFileChanges), so gatus_endpoint needs no restart
handler - writing the file IS the deploy.
* ...but on a reload it panics if the new config fails to parse, unless
skip-invalid-config-update is set. Endpoint files are contributed by other
playbooks, so one malformed file would take the monitor down at the worst
possible moment. Now set.
* The push URL uses a key Gatus computes, not the name you write:
sanitize(group) + "_" + sanitize(name), lowercased with / _ . , space # + &
replaced by "-" (config/key/key.go). So knots_box_local is
knots-box-local in the URL. The playbook derives it rather than hand-writing.
storage: maximum-number-of-results 900, up from upstream's 100. Gatus bounds the
database by COUNT and trims inline on insert, so there is no retention job and
no way to fill a disk - but history depth is then a function of check frequency,
and 100 results at a 5-minute interval is 8 hours. 900 is ~3 days of liveness
and ~2.5 years of the daily disk check. The uptime table is separate and its
30-day retention is hard-coded upstream.
A bug worth recording: the first deploy shipped five scripts that all died with
"syntax error: unexpected end of file". Jinja strips an included template's
trailing newline and trim_blocks then eats the newline after {% endif %}, so the
closing brace of check() landed on the same line as the body's last statement -
`return 0}`. Every check was broken and the deploy still reported failed=0,
because the role's "run once" task has failed_when: false and reports the result
as a debug message nobody read. The blank line that fixes it is now load-bearing
and commented as such.
Verified by triggering every unit by hand rather than waiting on timers: all
checks exit 0 on all hosts, and Gatus shows 26 UP / 1 DOWN. The one DOWN is
liveness_watchtower, which is honest - that host currently refuses SSH (TCP
connects, no banner exchange) and is excluded from this deploy. It is also the
box still running Uptime Kuma.
Known waste, not yet fixed: healthcheck installs its dependencies per CHECK
rather than per HOST, so apt runs 29 times estate-wide for a curl that is
already present, and daemon_reload runs 4x per host.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
