k8s-manifests/shortsmith/deployment.yaml

---
apiVersion: v1
kind: Namespace
metadata:
  name: shortsmith

---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  annotations:
    # Never let ArgoCD prune this PVC: it holds the job store and the rendered videos.
    argocd.argoproj.io/sync-options: Prune=false
  name: shortsmith-data
  namespace: shortsmith
spec:
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 5Gi

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: shortsmith
  namespace: shortsmith
  labels:
    app: shortsmith
spec:
  replicas: 1
  # Single replica on a RWO local-path volume holding a SQLite job store in WAL mode:
  # Recreate keeps two pods from opening /data/shortsmith.db during a roll. The queue
  # is per-process anyway, so a second replica would not share work, only the file.
  strategy:
    type: Recreate
  selector:
    matchLabels:
      app: shortsmith
  template:
    metadata:
      labels:
        app: shortsmith
    spec:
      containers:
        - name: shortsmith
          image: git.chemavx.xyz/chemavx/shortsmith:46b39256
          imagePullPolicy: Always
          ports:
            - name: http
              containerPort: 8080
          env:
            - name: SHORTSMITH_DATA_DIR
              value: "/data"
          volumeMounts:
            - name: data
              mountPath: /data
          # Measured IN THIS POD, sampling the cgroup's own memory.stat every 30 ms.
          # An earlier set of numbers taken on the dev host said 522 MB and produced a
          # 1Gi limit; the first real render was OOMKilled at 1483 MB. The host runs
          # ffmpeg 4.4.2 and the image ships 7.1.5, and 7.0 rewrote transcoding onto a
          # threaded scheduler whose inter-component queues hold decoded frames. So:
          # numbers measured outside the deployment target are a guess about it.
          #
          # Rendering is this service's normal mode, not a burst, so the request comes
          # from the peak and not from the resting figure.
          #
          #   at rest (imports + FastAPI app)              40 MB current
          #   frames, 3 workers, 1260 of them            +145 MB anon
          #   audio synthesis and WAV                     +82 MB anon
          #   encode pass 1, video only, -threads 3      +562 MB anon  <- the cost
          #   encode pass 2, mux the audio in             +15 MB anon
          #   two renders back to back, peak              640 MB anon / 716 current
          #   one render at the spec's 180 s ceiling      620 MB anon / 923 current
          #
          # anon is flat with duration; what grows is the page cache holding the PNG
          # frames (70 MB at 42 s, 287 MB at the 180 s ceiling). That is reclaimable,
          # so the request is sized against anon and the limit against current.
          #
          # 768Mi covers the 640 MB anon peak with ~20% headroom. The limit is 1.5Gi
          # and not 1Gi because of the ceiling case: at 1Gi that render peaked at
          # 940 MB of 1024, i.e. 84 MB of margin, surviving only because the kernel
          # had reclaimable cache to drop. Verified at 1.5Gi with memory.events
          # reading `max 0` — the limit was never reached, not merely never fatal.
          #
          # The CPU limit is what sizes the worker pool, not the request — the code
          # reads cpu.max, since cpu_count() reports the node's 16. At limits.cpu 3
          # that is 3 workers, verified in this pod. 42 s of video renders in ~31 s,
          # the 180 s ceiling in ~135 s.
          #
          # Consequence, deliberate: under sustained contention the pod runs 3 workers
          # on the 1 CPU it is guaranteed and a render takes about 3x longer. That is
          # benign here — POST /render returns a job id, the queue runs at concurrency
          # 1 and the caller polls, so a slow render is a later `done`, never a
          # timeout. Do not "fix" it by sizing the pool from the request: that would
          # trade an occasional slowdown for a permanent 3x on every render, including
          # the ones on an idle node, which is the common case.
          resources:
            requests:
              cpu: "1"
              memory: "768Mi"
            limits:
              cpu: "3"
              memory: "1536Mi"
          # The render runs off the event loop (asyncio.to_thread, and the frame
          # workers are separate processes), so /healthz answers while a job is in
          # flight. A probe timing out means the process is actually wedged.
          readinessProbe:
            httpGet:
              path: /healthz
              port: http
            initialDelaySeconds: 5
            periodSeconds: 10
          livenessProbe:
            httpGet:
              path: /healthz
              port: http
            initialDelaySeconds: 15
            periodSeconds: 30
            failureThreshold: 3
      volumes:
        - name: data
          persistentVolumeClaim:
            claimName: shortsmith-data
      imagePullSecrets:
        - name: gitea-registry-infisical

---
apiVersion: v1
kind: Service
metadata:
  # Must end in -svc. researchowl hit this: a Service named `searxng` collided with
  # the SEARXNG_* env vars k8s injects into every pod in the namespace and returned
  # 403s until it was renamed.
  name: shortsmith-svc
  namespace: shortsmith
spec:
  selector:
    app: shortsmith
  ports:
    - name: http
      port: 8080
      targetPort: http

# No Ingress on purpose: this is an internal API with no authentication, reached at
# shortsmith-svc.shortsmith.svc.cluster.local:8080 from inside the cluster. Ollama was
# exposed without auth once and had to be retrofitted with Authentik forward-auth.