Tuning for Large Clusters

featureFlags:
  thorasManageThoras:
    mode: autonomous
    metricsCollectorFollowsMode: false

thorasWorker:
  replicas: 2
  queriesPerSecond: "100"
  postgresql:
    maxConns: 40
    maxConnLifetime: 15m

thorasApiServerV2:
  replicas: 3
  postgresql:
    maxConnLifetime: 15m

thorasForecast:
  trainingJitterMinutes: 120
  worker:
    scaler:
      maxReplicas: 150

metricsCollector:
  persistence:
    # Size at roughly 200 MiB per AST; see "Storage" below. 1Ti covers
    # ~5,000 ASTs.
    pvcStorageRequestSize: "1Ti"
  timescale:
    requests:
      # TS_TUNE_NUM_CPUS below reads this value, so it must be a whole core
      # count, not millicores.
      cpu: "8"
      memory: 30Gi
    limits:
      memory: 30Gi
  env:
    - name: TS_TUNE_NUM_CPUS
      valueFrom:
        resourceFieldRef:
          containerName: timescaledb
          resource: requests.cpu
          divisor: "1"
    - name: TS_TUNE_MAX_CONNS
      value: "500"

kubectl -n thoras exec deploy/metrics-collector -c timescaledb -- \
  /docker-entrypoint-initdb.d/001_timescaledb_tune.sh
kubectl -n thoras delete pod -l app=metrics-collector