The /path calculator showed "0 / 9 HRRR points" in production despite
the on-disk profile store being current. Root cause: profile_from_cell/2
treated the cell's :profile key as a wrapper sub-map and called
Map.put_new on it — but the :profile key actually holds the vertical
pressure-level LIST. Every point sample crashed with BadMapError, the
crash propagated as {:exit, _} through Task.async_stream, and the
consumer silently dropped all 9 results.
Fix: stop wrapping. Cells are already flat HrrrProfile-shaped maps;
just stamp lat/lon (from the caller, since cells don't carry their
own coords — those are the map key) and valid_time onto the cell.
Audit + log every other async error path so the next silent failure
isn't invisible:
- PathLive HRRR point lookup
- Propagation.point_forecast per-hour reads
- Viewshed ray crashes
- IemClient ASOS network fetches
- RtmaClient range-download tasks
- Recalibrator factor-vector batches (positive + negative samples)
- MapLive forecast preload tasks
- RoverLive station resolution
LiveViews already had handle_async/3 exit clauses with logging. The
gap was always in Task.async_stream consumers that wrote {:exit, _} -> []
without surfacing the reason.
Add the rule to CLAUDE.md and project memory so this never repeats.
Also fix a pre-existing skewt_svg.ex compiler warning where
@critical_label_min_dy was used before being defined.
- IemRateLimiter gains AIMD-style adaptive spacing. signal_429/0
widens the current gap (*= 1.5, capped at max_interval_ms default
10s); signal_success/0 narrows it back toward the configured base
(*= 0.92, floored at interval_ms). Self-tunes to IEM's moving
ceiling without needing the manual "safe for 4 pods" constant.
- IemClient now routes every response through a central handle_response
helper that fires the widen/narrow feedback signals, eliminating the
four near-identical case blocks.
- Mix.Tasks.Weather.RebatchAsos collapses any already-queued single-
station "asos" jobs into the batched "asos_batch" shape the
enqueuer now emits, so the pending backfill queue converts to the
new per-request-efficient path instead of draining at the old rate.
Idempotent; supports --dry-run.
2833 tests + credo green.
IEM's ASOS CSV endpoint accepts multiple station= params in a single
request. Prior code enqueued one WeatherFetchWorker job per nearby
station per QSO endpoint — N jobs × 1 station each — which paid the
IemRateLimiter's 1500ms gap and the IEM 429-retry tail N times per
contact.
Changes:
- IemClient.asos_url/3 accepts a list of station codes.
- IemClient.fetch_asos_batch/3 fetches N stations in one call and
returns rows grouped by station_code (with absent codes filled as
empty lists so callers can stub them).
- parse_asos_csv/1 now exposes the station_code column it was
previously discarding.
- WeatherFetchWorker gains an "asos_batch" fetch_type clause that
unpacks rows per (station_id, station_code), upserting or stubbing
each. The single-station "asos" clause stays for already-queued
retryable jobs.
- ContactWeatherEnqueueWorker.build_asos_jobs/3 now emits one batch
job per (lat, lon, 4h window) covering every uncovered nearby
station (sorted for deterministic unique-args).
Expected effect on backfill: ~10-20x fewer IEM requests per contact
enrichment cycle, matching drop in 429 retry traffic.
Three bugs were letting mechanism/terrain/radar contacts ping-pong
between :complete and :queued on every backfill cron:
1. enqueue_for_contact/2 now filters out types that are already
:complete on the contact before building jobs. Previously
mark_status!/3 demoted every non-empty jobs_by_type entry back to
:queued, overwriting the :complete that workers had just set.
2. reconcile_stale_queued/1 now also flips mechanism_status and
radar_status back to :complete when the companion data
(propagation_mechanism / contact_common_volume_radar) already
exists. Drains the existing ~14k row backlog on the first post-
deploy tick.
3. IemClient.parse_iemre_json/1 accepts "" and nil so a 200-with-
empty-body IEMRE response doesn't FunctionClauseError the worker
through four retry attempts.
Two independent wins the latest prod telemetry pointed at:
1. Iowa Environmental Mesonet rate limiter. IEM throttles per source
IP across all in-flight requests, so dropping the `:weather` Oban
queue to 1/pod wasn't enough — workers were still issuing back-to-
back requests inside each job and drawing a steady stream of HTTP
429s (1,396 retryable on the queue). A GenServer-based token bucket
serialises acquire() with a 700ms min gap per pod; three pods give
~4 req/sec cluster-wide, well under the observed 429 threshold.
Wrapped around every IemClient fetch.
2. Parallel HRRR surface + pressure grid fetch. The two products live
in separate wrfsfcf / wrfprsf GRIB files, so their fetch → wgrib2
→ decode pipelines are independent; running them sequentially was
adding ~30s per forecast hour for no reason. Task.async the pair,
merge at the end. Halves per-fh wall time and should unblock some
of the missing-hour cases we saw on the 14:00Z chain.
Adds spans to 15 previously-unmeasured hot paths so every question we
might ask while tuning has a histogram to answer it:
External I/O:
- iem.fetch_iemre (gridded weather reanalysis)
- mrms.list_latest / mrms.download (precip radar)
- rtma.fetch_observation
- ncei.fetch_metar (historical 5-min METAR backfill)
- solar.fetch_indices (GFZ solar indices)
- swpc.fetch (SWPC Kp/F10.7/X-ray)
- giro.fetch (ionosonde)
- qrz.request, geocoder.geocode (callsign enrichment)
- srtm.download_tile (terrain tile download + gunzip)
- hrrr.download_grib_ranges (parallel byte-range fetch phase)
Subprocess:
- wgrib2.extract_grid / extract_grid_from_file / extract_grid_from_file_mapped
LiveView hot paths:
- propagation.scores_at (map score fetch + cache hit/miss counter)
- propagation.point_forecast (sparkline)
- propagation.point_detail (click-to-inspect)
- propagation.daily_outlook_at (/map outlook strip)
Worker-level end-to-end:
- worker.terrain_profile
- worker.mechanism_classify
- worker.mrms_fetch
Each event is registered in Microwaveprop.PromEx.InstrumentPlugin as
a Prometheus histogram (default / long buckets as appropriate) plus
a counter for the scores_at cache hit/miss ratio. Prometheus at
10.0.15.25 will start seeing the new series on the next scrape after
deploy.
New AsosAdjustmentWorker runs every 10 minutes:
- Fetches latest ASOS observations from all ~2900 US stations via
IEM bulk currents API (parallel fetch across 51 state networks)
- For each grid point within 75km of a reporting station, re-scores
using fresh ASOS data (temp, dewpoint, wind, sky, pressure, precip)
with HRRR refractivity gradient from the last hourly computation
- Pushes updated scores to the map via PubSub
Also stores HRRR profiles in the database during grid computation
so the data persists for reference and ASOS blending.
- Add precip_1h_in and wx_codes fields to ASOS surface observations
- Add IEMRE reanalysis schema for radar-derived hourly precipitation
- Add IemreFetchWorker with exponential backoff and idempotency
- Integrate IEMRE enqueue into cron weather backfill pipeline
- All existing QSOs marked iemre_queued=false for automatic backfill
Previously retry: :transient only retried connection errors, not HTTP
429 rate limits. All clients now use a custom retry function that
handles 429, 500, 502, 503, 504 with 5 retries and jittered backoff.
IEM was returning 503s under 10 concurrent workers. Three fixes:
- Req transient retry with exponential backoff on IEM requests
- WeatherFetchWorker Oban job retries failed ASOS/RAOB fetches 2-3h later
with random jitter to avoid thundering herd
- Import script concurrency reduced 10→5, weather queue capped at 3
Store surface observations (ASOS) and upper-air soundings (RAOB) alongside
QSOs for atmospheric propagation correlation. Three new tables: weather_stations,
surface_observations, and soundings with JSONB profiles and pre-computed derived
parameters (refractivity, gradients, duct detection, stability indices).
Includes IEM API client for historical data import and import script seeded
with 95 ASOS + 9 sounding stations from PropCast coverage area.
