The first case spent 14 s per full-snapshot build in the all-time pulse
aggregate, planned against a table with no statistics, until autovacuum
analyzed it; on a loaded runner that took it past its 60 s budget. Analyze
measurements and rollups after seeding, as a production table would be.
The cases and the comparison they make are unchanged.
The parity test built a fresh Intl.DateTimeFormat for each of ~36k
comparisons and crossed the 5 s timeout on CI runners. One formatter per
zone halves its time; it also gets an explicit 20 s budget, since it is
meant to be exhaustive.
backupPayloadSchema is built when validations/backup.ts is evaluated and
holds about 12 MB of heap. The restore job, the stored-backup readers and
the export writer import that module, and they sit on the boot path, so
every server process built the schema at start whether or not it ever
touched a backup.
The schema version, the compatibility check and the per-section summary
move to validations/backup-summary.ts, which never builds the schema. The
call sites that validate a file (upload, restore, the summary and download
routes, and the streamed reader's element check) load backup.ts with a
dynamic import at that moment; everything else takes only types. The
OpenAPI registry keeps its static import, since only the spec generator
loads it.
After warm-up on a production build under --max-old-space-size=524, the
used heap drops by about 29 MB, and the schema no longer appears in a heap
snapshot. A structural test refuses a new static value import of the
module outside the registry.
get_metric_series (and get_metrics, the metric resources and the review
prompts, which fan out over it) answered with one section of a Coach
snapshot, but built the whole snapshot to get it: the all-type feature
extraction, the derived wellness layer, trajectory, correlations, memory,
GLP-1, cycle, illness, labs and visits. On a seeded account with about
215k measurements a resting heart rate read ran 208 SQL statements and
blocked the event loop for 175 ms to return under 2 KB.
The MCP surface now asks the executor for a source snapshot. It runs the
same prelude (prefs, module gates, admitted sources, cutoffs, now shared in
snapshot-prelude.ts) and the same block builders over the requested
source's reads only. The core clinical aggregates come from extractFeatures
scoped to the one block, whose bulk read keeps its all-type cap so the rows
a block sees do not change. A section large enough for the full builder's
prompt-budget pass to trim, and the environment cluster, go to the full
builder, so their results are the old ones by construction.
The integration test compares the tool's serialised result with the full
builder's section and grounding for nine sources over four windows, the
get_metrics batch and the metric resource, on a seeded account dense enough
to put the feature row cap into play.
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.
A document whose preview render fails for good (a PDF whose first page
renders blank) was queued by the boot-time backfill, refused, and queued
again at the next boot, without end.
The thumbnail job now keeps the failure with the document
(document_thumbnail_failures, migration 0374): the reason, the attempts
since the last success and when the newest failed. The backfill, both the
boot discovery and the per-account pass, leaves a document out after one
deterministic refusal (raster-failed, empty-render, pixel-cap) or three of
any other kind, until the document changes. A direct enqueue still renders
it, and a preview that is made clears the record.
A weekly or nightly backup job whose process died (a restart, a
container out of memory) stayed active until its two- or four-hour
expiry, and its retry walked the accounts in the same order: the account
that killed it has the oldest copy, so it led again, and every account
after it went without a copy for as long as that record stayed too
large.
Both passes now send with a five-minute pg-boss heartbeat, so a dead run
fails within minutes and its retry picks it up. Each pass records when it
started and finished every account (backup_pass_attempts, migration
0373); an account whose last attempt never finished goes behind all the
others. The backups page shows when the run in progress started and names
an account a run died under, for the weekly and the off-host card, and a
heartbeat timeout reads as what it means.
Since v1.39.6 the preview scanner parsed the JSON on its way into the
pieces, kept every section but the three bulk tables, and validated the
whole document at the end: a second copy of the record beside the
writer's own, inside the weekly job. On an account with a document vault
that is most of the record.
The writer now shows each section and each bulk row to an observer just
before writing it. The preview collects key uses from that and takes its
counts from the writer's own FullBackupCounts; nothing is parsed or kept.
An upload hands over the summary and key uses it has already validated.
The round trip pins the writer's counts and key uses to a full read of
the copy on an account with a row in every model, and a memory test holds
what the pass keeps once the producer is done.
Measured on 70,000 measurements, 3,000 mood entries and 40 one-megabyte
documents under --max-old-space-size=524: held after the producer
56 MB before, 3 MB after; peak heapUsed 398 MB before, 334 MB after.
The drill read only the alphabetically last object of the newest date, so
one account stood in for all of them. It now checks every object of that
date one at a time, records a failure against the account it belongs to,
keeps going, and pages once per failing object with its key and how many
accounts were checked.
A text column written before key ids existed holds the bare base64 of
nonce, tag and ciphertext. The key check read such a value as an encoded
Bytes column, decoded it once too often, and accused the v1 key of not
opening a copy it opens. The instance's stored AI key has exactly that
shape and is the shortest v1 value in every disaster-recovery copy, so it
was picked as the probe and refused every restore of an account with v1
values, even with the instance settings left out of the verdict.
A legacy value now reads as a string unless its decoded head is base64
text. Samples are kept per section and only the sections the verdict
counts are probed; a key is unreadable when none of its probes opens.
Binary values open with the label their column is sealed under, taken
from the encrypted-column registry, and are not probed when no label is
known. A preview stored by an earlier release is still read, and its
sample's layout is derived again from the value.
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.
Marc-André Bombeck