prop/k8s/deployment-hrrr-point-rs.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: hrrr-point-rs
  namespace: prop
  # Phase 3 Stream C: per-QSO HRRR fetches move off the BEAM pods.
  # Elixir writes to hrrr_fetch_tasks (one row per valid_time with a
  # points JSONB array); this deployment drains via FOR UPDATE SKIP
  # LOCKED, fetches each HRRR cycle once, and upserts hrrr_profiles.
spec:
  # Parallelism on QSO-submit spikes comes from multiple replicas
  # claiming rows from hrrr_fetch_tasks via FOR UPDATE SKIP LOCKED —
  # no coordination needed between workers.
  # Replica count is HPA-managed (hpa.yaml, min 1 / max 4).
  # Zero-downtime rollout: surge first so the new pod is serving
  # before the old one drains, otherwise a deploy during a QSO-submit
  # burst leaves the per-QSO fetch lane empty until the new pod is
  # ready. Both pods race for hrrr_fetch_tasks via FOR UPDATE SKIP
  # LOCKED, so brief overlap is safe.
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  selector:
    matchLabels:
      app: hrrr-point-rs
  template:
    metadata:
      labels:
        app: hrrr-point-rs
        tier: hrrr-points
      annotations:
        # Scraped by the Prometheus at 10.0.15.31 via the
        # `kubernetes-pods` job in prometheus.yml.j2 (apiserver proxy).
        # The hrrr_point_worker binary spawns the same metrics::serve
        # listener as prop-grid-rs (METRICS_ADDR, default 0.0.0.0:9100)
        # and reports prop_grid_rs_point_batch_* + points_processed_*
        # series.
        prometheus.io/scrape: "true"
        prometheus.io/port: "9100"
        prometheus.io/path: "/metrics"
        prometheus.io/job: "hrrr-point-rs"
    spec:
      # Anti-affinity against prop-grid-rs was removed; the scheduler
      # is free to colocate. Contention on wgrib2 + NFS hasn't been an
      # observed bottleneck in practice.
      # Per-QSO point fetches are short (~5-15 s), but a stack of
      # claimed rows can take a couple of minutes to drain. 120 s lets
      # the worker finish in-flight tasks before SIGKILL.
      terminationGracePeriodSeconds: 120
      imagePullSecrets:
        - name: forgejo-registry
      securityContext:
        runAsUser: 65534
        runAsNonRoot: true
        fsGroup: 65534
        seccompProfile:
          type: RuntimeDefault
      containers:
        - name: hrrr-point-rs
          # Shares the prop-grid-rs image so one CI pipeline produces
          # both binaries. k8s `command:` overrides the default
          # ENTRYPOINT to launch the per-QSO point worker.
          image: codeberg.org/gmcintire/prop-grid-rs:main-1777132414-6aa91e7
          imagePullPolicy: IfNotPresent
          command: ["/usr/bin/tini", "--", "/usr/local/bin/hrrr-point-worker"]
          env:
            - name: HRRR_BASE_URL
              value: "http://skippy.w5isp.com:8080"
            - name: HRRR_FALLBACK_BASE_URL
              value: "https://noaa-hrrr-bdp-pds.s3.amazonaws.com"
            - name: RUST_LOG
              value: "info"
            - name: PROP_GRID_RS_PG_CONNS
              value: "4"
            # Shared NFS idx cache — same directory as prop-grid-rs so a
            # chain-step idx fetch warms both workers.
            - name: HRRR_IDX_CACHE_DIR
              value: "/data/hrrr_idx"
            # /metrics + /health listener; same default as prop-grid-rs.
            - name: METRICS_ADDR
              value: "0.0.0.0:9100"
          envFrom:
            - secretRef:
                name: prop-secrets
          ports:
            - name: metrics
              containerPort: 9100
              protocol: TCP
          # Readiness mirrors prop-grid-rs: /health returns 200 once the
          # axum metrics listener is bound. Liveness intentionally
          # omitted — an idle worker (no claimable tasks) is healthy,
          # and the kubelet will restart on process crash anyway.
          readinessProbe:
            httpGet:
              path: /health
              port: 9100
            initialDelaySeconds: 10
            periodSeconds: 10
            timeoutSeconds: 3
            failureThreshold: 6
          resources:
            requests:
              cpu: 100m
              memory: 256Mi
            limits:
              # Per-batch peak is a single CONUS surface + pressure
              # decode (~40 MB blob, ~200 MB wgrib2 working set plus
              # the full 92k-cell merged CellValues map kept in memory
              # until all requested points are drained). 1 Gi OOMKilled
              # repeatedly — four restarts in ten minutes — so bumped
              # to 2 Gi. The scheduler-on-worker2 placement has plenty
              # of headroom.
              cpu: "2"
              memory: 2Gi
          securityContext:
            allowPrivilegeEscalation: false
            runAsNonRoot: true
            runAsUser: 65534
            capabilities:
              drop:
                - ALL
            seccompProfile:
              type: RuntimeDefault
          volumeMounts:
            - name: data
              mountPath: /data
      volumes:
        - name: data
          nfs:
            server: 10.0.15.103
            path: /data