Three independent improvements in one commit:
1. Parallel band scoring (pipeline.rs):
- rayon par_iter across 23 bands replaces the serial for loop.
- All band files now write via try_join_all over spawn_blocking
instead of serializing one-at-a-time on NFS. Chain per-step
drops from ~60s to ~15-25s on a 4-core box.
2. Prometheus metrics (new metrics.rs):
- axum server on METRICS_ADDR (default :9100) exposes /metrics and
/health. Scraped by existing Prometheus via annotation.
- Histograms: chain step duration (by outcome), decode duration.
- Gauge: tasks in flight (RAII guarded so panics don't leak).
- Counter: chain steps by outcome.
- worker.rs records step duration and wraps each run in an
InFlightGuard.
3. HA + ordering fixes:
- deployment-grid-rs.yaml: replicas 1→2, required podAntiAffinity
spreads them across hosts, nodeAffinity prefers talos5 for one.
PROP_GRID_RS_PARALLELISM 4→3 per pod (6 concurrent across
replicas; smaller secondary-node footprint).
- Readiness probe on /health so rollouts wait for the runtime to
be alive.
- claim_next ordering: run_time ASC → DESC so the newest hourly
run drains before any stragglers from a broken prior run. Within
a run, forecast_hour ASC keeps nearest-first.
- grid_task_enqueuer sets kind="forecast" explicitly and updates
conflict_target to the new 3-column unique index introduced by
migration 20260419222624.
Replaces the serial claim→process loop with a JoinSet of N worker tasks,
each running the same claim→fetch→decode→score→complete flow against
grid_tasks. FOR UPDATE SKIP LOCKED already prevents contention between
workers so no additional coordination is needed.
talos5 is 4c/4t (i5-7260U); PROP_GRID_RS_PARALLELISM=4 turns the full
f01..f18 chain from ~18 min serial into roughly ~5 min. Per-task peak
memory after the streamed-bands refactor is ~250 Mi, so 4 concurrent is
~1 Gi — well under the 2 Gi container limit.
Postgres pool sized to parallelism + 2 so NOTIFY and an opportunistic
claim retry share the pool without blocking a worker transaction.
Both the hot (`prop`) Deployment and the `prop-backfill` Deployment
labelled their pods with `app: prop` so both joined the same libcluster
Erlang cluster. The `prop` Service selector was `app: prop` too — which
meant the backfill pod (PHX_SERVER=false, no listener on :5000) was in
the Service endpoint pool.
With sessionAffinity: ClientIP, Cloudflared's source IP got hashed to
the backfill endpoint after a backfill pod roll and every request
from that client returned 502 (connection refused on :5000).
Fix: add `tier: hot` to hot-pod template labels; narrow the Service
selector to `{app: prop, tier: hot}`. Backfill keeps `tier: backfill`
and is cleanly excluded. libcluster selector (still `app: prop`) is
unchanged so backfill stays in the Erlang cluster for Oban queue
leader election and Oban.Pro's Smart engine.
Rust `prop-grid-rs` has been validated end-to-end on talos5 on the
streamed-bands image (main-1776635096-6d91461): real chain steps
complete in ~7 s each and the peak-heap refactor landed.
Changes:
- `PropagationGridWorker.seed_chain` now enqueues a single f00 Oban
job instead of f00–f18. The f00 analysis-hour keeps its enrichment
(native-level duct, NEXRAD composite, commercial-link boost,
ProfilesFile write) and the GridCache broadcast.
- `GridTaskEnqueuer.seed/1` is called again so grid_tasks gets the
18 forecast-hour rows the Rust worker claims.
- Test asserts only one Oban job is enqueued and the matching 18
grid_tasks rows land in the DB.
- `deployment-grid-rs.yaml` flips `PROP_SCORES_DIR` from
`/data/scores_shadow` to `/data/scores` so Rust writes to the live
score tree. No file collision — Elixir only writes the f00 files.
The hot pod memory shrink (6 Gi → 1 Gi) is deferred until one full
hourly cycle runs clean under the new split.
1 Gi OOM'd during a real chain step. Each forecast hour loads both a
surface and pressure-level HRRR GRIB2 (~40 MB combined), decodes via
wgrib2 subprocess (which allocates its own buffers), scores 92k grid
points × 23 bands (~2.1M intermediates), and writes 23 score files.
2 Gi absorbs the spike; still ~3× smaller than the Elixir-per-pod
budget we're replacing.
The real worker binary OOM-killed at 512 Mi on startup. The plan's
512 Mi assumption was speculative — actual Rust RSS at boot includes
sqlx pool buffers, reqwest connection pool, tokio runtime, and
tracing JSON subscriber. 1 Gi leaves room for all of that plus the
steady-state ~500 Mi during a chain step.
Mirrors the Elixir wiring:
- ImageRepository + ImagePolicy scan git.mcintire.me/graham/prop-grid-rs
for main-<ts>-<sha> tags and pick the highest timestamp.
- ImageUpdateAutomation already covers ./k8s via the Setters strategy,
so the new setter marker on deployment-grid-rs.yaml means flux will
rewrite it on every CI push and commit the update back to main.
Extracts the memory-hostile HRRR fetch → decode → score pipeline for
forecast hours 1–18 into a separate Rust service (`prop-grid-rs`).
Elixir retains f00 with its native-duct + NEXRAD + commercial-link
enrichment; Rust handles the other 18 steps per hourly chain.
Hand-off via a new `grid_tasks` table (`FOR UPDATE SKIP LOCKED` claim
from Rust, Postgrex `NOTIFY propagation_ready` back to Elixir). Rust
writes the same on-disk score-grid format Elixir already uses, to the
same `/data/scores` NFS tree. Phase 1 ships in shadow mode with
PROP_SCORES_DIR=/data/scores_shadow.
Rust crate layout at `rust/prop_grid_rs/` (1:1 module parity with the
Elixir source it ports):
- grid, region, band_config, scores_file, sounding_params
- scorer: all 10 factors + composite. Matches the Elixir scorer
byte-for-byte across 115 golden-fixture samples (5 scenarios
× 23 bands).
- decoder: wgrib2 subprocess + Fortran-record lola-binary parser
- fetcher: HRRR URL derivation + idx cache (1h TTL) + 8-way
parallel byte-range downloads with 429/5xx retry
- pipeline: end-to-end chain step, f00 rejected at the boundary
- db: sqlx grid_tasks claim/complete + propagation_ready NOTIFY
- bin/worker: tokio main loop, JSON logs, SIGTERM-safe
91 Rust tests + clippy -D warnings clean. 2,158 Elixir tests green.
Elixir additions:
- `GridTaskEnqueuer` seeds fh=1..18 rows from
`PropagationGridWorker.seed_chain/0`
- `NotifyListener` LISTEN → warm `ScoreCache` → PubSub fan-out
- `ShadowComparator` diffs prod vs shadow `.ntms` bodies
- `mix rust.golden` task writes the Rust-side golden fixture
k8s: new `deployment-grid-rs.yaml` pinned to talos5 (32 GB NUC) via
`prop-grid-rs=primary` nodeSelector + `workload=grid-rs:NoSchedule`
toleration, 512 Mi limit, sharing the existing NFS `/data` mount.
The plan document is at `plans/vivid-hatching-quail.md` (local to my
workstation); phases 2 (cutover) and 3 (talos5 concurrency tuning)
follow after 72h of shadow-mode parity.
talos5 is a NUC7i5 with 32GB RAM and a Samsung 980 Pro NVMe. Adding
a 4th hot-path replica lets the anti-affinity rule place one pod
per physical host across node1/2/3/5 and gives the hourly f00-f18
grid chain 4-way parallel fan-out, with the NVMe-backed pod
handling its share of grib extraction.
PROP_ROLE=backfill drops the hot-path propagation/commercial/solar
queues and the Cron plugin. Paired with a dedicated Deployment
(nodeSelector: prop-backfill=true, 4Gi memory, no web) this lets 8GB
T620 workers drain the hrrr/weather/terrain/iemre/narr backfill
queues without competing with the hourly grid chain.
