demand-forecasting/fly.toml at master · twomathematicians-code/demand-forecasting · GitHub

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# Fly.io configuration for Demand Forecasting API
# Docs: https://fly.io/docs/reference/configuration/

app = "demand-forecast-api"

primary_region = "iad"  # Virginia — change to nearest: ams, lhr, sin, syd, gru

[build]
  dockerfile = "Dockerfile"

[env]
  PORT = "8080"
  DF_ENVIRONMENT = "production"
  DF_LOG_LEVEL = "INFO"
  DF_REDIS_ENABLED = "true"
  DF_REDIS_URL = "redis://localhost:6379/0"
  DF_KAFKA_CONSUMER_ENABLED = "false"
  DF_DRIFT_CHECK_ENABLED = "false"
  DF_MODEL_REGISTRY_PATH = "/data/models"
  DF_CORS_ORIGINS = "https://demand-forecast-api.fly.dev"

[[services]]
  protocol = "tcp"
  internal_port = 8080

  [[services.ports]]
    port = 80
    handlers = ["http"]
    force_https = true

  [[services.ports]]
    port = 443
    handlers = ["tls", "http"]
    force_https = true

  [[services.http_checks]]
    interval = "15s"
    timeout = "5s"
    grace_period = "30s"
    method = "get"
    path = "/api/v1/health"
    protocol = "http"
    tls_skip_verify = true

  [[services.http_checks]]
    interval = "10s"
    timeout = "3s"
    grace_period = "5s"
    method = "get"
    path = "/api/v1/health"
    protocol = "http"
    headers = { Type = "readiness" }

[deploy]
  release_command = "python -c 'from src.utils.config import get_app_config; print(\"Config OK\")'"

[[vm]]
  cpu_kind = "shared"
  cpus = 1
  memory_mb = 512

[[statics]]
  guest_path = "/app/static"
  url_prefix = "/static"

[mounts]
  source = "model_data"
  destination = "/data"
  initial_size = "3gb"