Node sizes its heap from the container's memory cap. The 1g default gave
524 MB, which a long-used account fills in normal operation: on a live
instance 490 to 507 MB stayed live after a full GC, garbage collection
stalled requests for up to 8.5 s, and the process ran out of heap 26 times
in a week, taking the weekly backup with it. 1536m gives 792 MB. The
example env and the backup runbook say how to lower it on a small host.
Both grids carry an aria-label while their data loads, on a plain div,
which axe reports as aria-prohibited-attr: the label has no role to
name. A scan that lands while the scores strip is still loading fails on
it. The loading grids now take role=status, the role a loading region
has and which already implies the polite live region; the loaded vitals
grid carries neither.
Entering the Insights overview fired every section's reads at once, about
two dozen requests on a seeded account, and the server worked through
them in a queue: the hero and the first sections waited behind trends,
the period review, cycle, signals, rhythm events, health status,
breathing, labs and ECG, all far below the fold.
The first three sections in the account's own order still mount with
the page. Every later one renders a 1 px sentinel until it comes within
400 px of the visible area of the shell's scroll container, then mounts
and fetches; once mounted it stays. Measured on a seeded account under a
4x CPU slowdown: 24 -> 13 requests on entry, the entry network span
1.3-1.8 s -> 0.5-0.9 s, LCP about 1.35 s -> 0.9 s, blocking time about
550 ms -> 200 ms. Scrolling to the end still loads all 25 and renders
all ten sections.
Specs that assert on, measure or scan the lower sections scroll them in
first through a shared helper, so their coverage is unchanged.
On a short window (around 785 px and below) the nav list is taller than
the room between the logo band and the footer group, so it scrolls. With
nothing marking the edge, the last visible entry was cut off right at
the Collapse row and read as the footer covering it; macOS hides the
scrollbar that would have said otherwise.
While the list overflows, the footer group draws the same hairline the
user section does. A ResizeObserver on the nav and its list keeps the
state current as the window or the entries change; with room to spare
the rail is unchanged. The e2e spec checks the edge, that the last entry
scrolls fully clear of the footer, and that a tall window draws no edge.
The in-memory day-aggregate fake re-filtered every row for every day,
converting each timestamp to the profile timezone again, so a 1000-day
series took about five seconds and the graded pulse-status test hit its
timeout. It now groups by day and segment in one pass (4.8 s to 85 ms).
The medications list and the compliance summary refetch on every mount,
so a take or skip logged on another device shows on return (#316). The
nav link's hover / touch / focus intent and the route-commit preload
prefetch both reads too, so every visit through a link sent each of
them twice: the prefetch, then the identical request from the mount a
few hundred milliseconds after the first answer landed.
The mount now skips its refetch only when the cached data answers a
prefetch that went to the network for this visit: within the last 10 s,
and since the route last left /medications. A direct load, a return
with an older entry, or a quick return whose prefetch found the entry
still fresh keep the refetch on mount.
A Coach snapshot, a derived-metric batch or the Insights page fans out
into a dozen readers that each probe the same account's rollup coverage
at once. In production one MCP get_metrics call held 59 of these probes
open on the database together, each taking about 320 ms under that
contention, and the same burst repeated every 15 minutes.
Concurrent probes for one account now join the query already running.
Nothing is kept after it settles, each caller gets its own map, and a
measurement write drops the in-flight entry so a probe that starts after
a write always reads afresh. The registry lives on globalThis so every
server bundle shares it.
Day keys and wall-clock fields are computed per row in the analytics,
digest and personal-record loops, and each call ran
Intl.DateTimeFormat#formatToParts plus a resolvedOptions() allocation
to re-validate the zone. In a CPU profile of an Insights page load the
zone helpers were 17-19% of the busy time on the request thread.
Probe the offset once per UTC hour at both ends of the hour and derive
the wall clock arithmetically; an hour that contains a transition, an
instant outside 1971-2199 or an invalid date keeps the formatter path.
Zone validity is memoised per name. userDayKey drops from 9.3 to 1.5 us
per call, wallClockInTz from 6.4 to 0.5 us; a parity test checks the
result against Intl around every 2026 transition in ten zones.
The health score card passed the episode onset, an ISO instant, straight
into its sentence, so it read "Rest Mode active since
2025-08-04T09:55:00.000Z". It now shows the day that instant falls on in
the profile timezone, in the user's date format. The test that pinned the
raw value now pins the formatted day.
probeRollupCoverage runs ahead of the dashboard snapshot, the analytics
slices and the comprehensive insights. It read every live row of the
account for SELECT DISTINCT type and counted every DAY bucket per type,
which the planner served with a sequential scan of measurement_rollups.
Walk the distinct types with a recursive CTE along the live index and
test coverage with EXISTS. On a copy of a long-lived account the probe
drops from 24-50 ms to under 2 ms and returns the same map; an
integration test keeps the old query as the oracle.
A production build loads src/lib/db.ts once per server bundle, and the
client was only parked on globalThis outside production. The running
process held three clients: about 28 MB of query-compiler state each on
a heap capped near 520 MB, and three pg pools each sized to the full
per-process connection budget. Park the client on globalThis in every
environment so each copy of the module resolves the same one.
Recharts sizes every tick and label by writing it into one off-screen
span and reading getBoundingClientRect(). Under <body> each read forced
a document-wide style recalc, because the stylesheet's descendant-subject
:has() rules leave Chromium no way to scope the invalidation. A seeded
dashboard made 149 such reads per cold load at about 2.8 ms each, about
1.8 s of main-thread time under a 4x CPU slowdown.
The chart runtime now parks that span in a zero-size, contain: strict
host under <html>, which Recharts finds by id and keeps using. Each read
drops to about 0.01 ms; the dashboard's total blocking time under the
same slowdown falls from about 2.5 s to about 0.75 s. The host copies
<body>'s classes, where the app font is set, so every string measures
exactly as before; an e2e spec checks that parity on the drawn labels
and that the host survives a client-side round trip.
The tracker posts to `${data-host-url}${collect path}`, and the collect
path is compiled into the operator's Umami build: /api/send by default,
anything else when the instance sets COLLECT_API_ENDPOINT. The tag
pointed data-host-url at the app origin and the proxy listened only on
/api/send, so a renamed endpoint sent every page view and event to an
app path that does not exist and got a full 404 page back each time.
Point data-host-url at /api/monitoring/umami and answer every path under
it with one proxy route. The route reads the collect path from the
configured tracker (cached for an hour), forwards only that path to the
Umami host, and answers anything else, or an unreadable tracker, with an
empty response. The admin test event posts to the same learnt path. The
send-URL resolver lives in one module instead of two copies.
The rail animates its width from w-16 to w-64, and the labels laid out
against the growing width: every row overran the nav and multi-word
labels wrapped, so the nav's overflow-y-auto painted a vertical and a
horizontal scrollbar for the length of the transition.
Lay the expanded column out at its final width from the first frame and
let the rail clip it. The final layout is unchanged; the column fills
the expanded rail exactly. A unit test pins the structure and an e2e
spec samples the nav on every frame of a real expand and collapse.
Recapture Insights, resting heart rate, Medications and Coach at the
same 2552x1308 frame. The resting heart rate shot no longer shows the
raw metric enum in the chart legend. Images are palette-quantised, about
a fifth of their previous size.
The note had one form per locale, so a single left-out record read as a
plural. It now resolves One, Few and Other through tCount like the other
counted strings, with the singular in every locale and the Polish few form.
A sample the app wrote before the origin marker existed still carries the
HealthLog row id as HKExternalUUID. A hit on one of the account's rows of
the same kind now leaves it out exactly, for Withings and import mirrors as
well as manual ones; either id of a blood pressure pair covers both halves,
since the app stamps both samples of a reading with one id.
The manual-mirror lookup read one OR clause per row on every batch, even
for an account without a single MANUAL row. The types that hold MANUAL rows
are now read once per import; a batch asks nothing for any other type, and
one time window per type for those.
Cycle samples carry the marker too and are now left out like the rest, and
a sample the export repeats (a correlation's records also stand on their
own) is counted once.
The comment claimed the app's own sync filters by the marker. It does not:
the app's echo check is HKExternalUUID plus the sample's authoring source
being the app itself, and the marker exists for the deletion path, where
the source is not visible. Say so, and say why the export import reads the
marker and the row id instead.
The wide tier let the trend column grow to 8rem while the sparkline it
holds is a fixed 72px glyph, so at 1920 px an empty 56 px strip opened
between the sparkline and the chevron. The column now stays 72px in both
tiers; the extra width goes to the range bar and the name, as before.
The wide-list spec reads the resolved grid tracks and asserts the trend
track is 72px at every width it covers.
The systolic and diastolic reads each took the ladder's source per day on
their own. Whenever a source held only half of a reading on a day (a deleted
diastolic, an orphaned sample, a sub-floor systolic), the two picks diverged
and the pairing joined one source's systolic to another source's diastolic.
A sub-floor systolic could also claim a day and then contribute nothing,
leaving the day empty although a lower-ranked source had a valid reading.
The source is now picked per day from the systolic rows that pass the floor,
both halves are read from it in one statement, and a pair is only made
within one source, which also covers a reading that straddles midnight.
src/app/favicon.ico was still the filled heart from the first release on a
solid white square. Next serves it next to favicon.svg, and browsers that
pick the ICO (Safari, bookmarks, history, some tab states) showed the old
icon on a white slab. It is now the current logo at 16, 32 and 48 px with a
transparent background.
A structural test lists every file that takes a database or in-memory mean
over measurement values and names pulse, and requires each to use the shared
statistic, hand the type to a fold that does, or state why it never averages
pulse readings. A new plain mean over pulse, or a reader that drops the type,
fails it.
The insights comparison snapshot took its current and baseline pulse figures
from a reading AVG, and the Coach's data inventory told the model a reading
mean of the whole pulse history. Both now read the mean of the user's local
days, each the mean of its hours' means, through the day-mean helper. Every
other type keeps its aggregate.
The feature extraction, the signals of the day, the status cards, the graded
series, the Coach snapshot, the mood correlations and the report's trend arrow
each still averaged pulse over its readings, so a dense workout hour decided
the day and a workout day the window. They now read a pulse day as the mean of
its hours' means and a window as the mean of its days, through the day-mean
helper. Counts, extremes and spreads stay over every reading; every other type
is unchanged.
The doctor report's pulse average and day points, the correlation channels,
the illness correlation, the personal baseline and the Coach's tiered context
each folded pulse readings into a day by plain mean. They now take the day as
the mean of its local hours' means and a window as the mean of its days, in
the zone each reader buckets by. The day aggregates carry the weighted sums for
an hourly-mean type, so every caller reads one day value. Every other type is
unchanged.
A blood pressure reading is a <Correlation> wrapping its systolic and diastolic
records, and the marker can sit on the correlation instead of on each record.
The import only read it from a record's own metadata, so a marked correlation
would have come back in full.
A correlation's records are now held until it closes, then all kept or all left
out together: the marker on the correlation, before or after its records, or on
a record, applies. Tests cover each, the marker not spilling onto the next
record, and a self-closing record.
Marc-André Bombeck