FabledSteward/plugins/docker/models.py

# plugins/docker/models.py
from __future__ import annotations
import uuid
from datetime import datetime, timezone
from sqlalchemy import (
    BigInteger, Boolean, DateTime, Float, ForeignKey, Index, Integer, String, Text,
    UniqueConstraint,
)
from sqlalchemy.orm import Mapped, mapped_column
from steward.models.base import Base


class DockerContainer(Base):
    """Latest known state per container, scoped to the host that reported it.

    Collection is per-host via the host agent, so container names are only
    unique within a host — the natural key is (host_id, name). host_id is NOT
    NULL: every container arrives through a host_agent ingest that resolves a
    Host first. Deleting a host cascades its containers away.
    """
    __tablename__ = "docker_containers"

    host_id: Mapped[str] = mapped_column(
        String(36), ForeignKey("hosts.id", ondelete="CASCADE"), primary_key=True
    )
    name: Mapped[str] = mapped_column(String(255), primary_key=True)
    container_id: Mapped[str] = mapped_column(String(64), nullable=False, default="")
    image: Mapped[str] = mapped_column(String(512), nullable=False, default="")
    status: Mapped[str] = mapped_column(String(32), nullable=False, default="unknown")
    # running | stopped | paused | exited | dead
    cpu_pct: Mapped[float | None] = mapped_column(Float, nullable=True)
    mem_usage_bytes: Mapped[int | None] = mapped_column(Integer, nullable=True)
    mem_limit_bytes: Mapped[int | None] = mapped_column(Integer, nullable=True)
    mem_pct: Mapped[float | None] = mapped_column(Float, nullable=True)
    restart_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
    ports_json: Mapped[str] = mapped_column(Text, nullable=False, default="[]")
    # JSON: [{"host_port": 8080, "container_port": 80, "protocol": "tcp"}]
    started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
    scraped_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), nullable=False,
        default=lambda: datetime.now(timezone.utc),
    )

    # ── Enrichment (agent ≥ 1.4.0) ────────────────────────────────────────────
    # Health/exit/restart come from `docker inspect` (not the list endpoint);
    # exit_code is only meaningful for stopped containers.
    health: Mapped[str | None] = mapped_column(String(16), nullable=True)  # healthy|unhealthy|starting
    exit_code: Mapped[int | None] = mapped_column(Integer, nullable=True)
    oom_killed: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
    # Grouping: compose project + swarm placement, read off container labels.
    compose_project: Mapped[str | None] = mapped_column(String(255), nullable=True)
    service_name: Mapped[str | None] = mapped_column(String(255), nullable=True)
    task_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
    node_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
    # Cumulative-since-start I/O counters (BigInteger — they exceed 2^31 quickly).
    net_rx_bytes: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
    net_tx_bytes: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
    blk_read_bytes: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
    blk_write_bytes: Mapped[int | None] = mapped_column(BigInteger, nullable=True)


class DockerMetric(Base):
    """Time-series CPU/memory per container — one row per sample per running
    container, scoped to the reporting host."""
    __tablename__ = "docker_metrics"

    id: Mapped[str] = mapped_column(
        String(36), primary_key=True, default=lambda: str(uuid.uuid4())
    )
    host_id: Mapped[str] = mapped_column(
        String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False, index=True
    )
    container_name: Mapped[str] = mapped_column(String(255), nullable=False, index=True)
    scraped_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), nullable=False,
        default=lambda: datetime.now(timezone.utc),
        index=True,
    )
    cpu_pct: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
    mem_pct: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
    mem_usage_bytes: Mapped[int] = mapped_column(Integer, nullable=False, default=0)

    # Per-container history lookups filter on (host_id, container_name) then sort
    # by time — a composite index keeps the rows() sparkline queries cheap.
    __table_args__ = (
        Index("ix_docker_metrics_host_container_time",
              "host_id", "container_name", "scraped_at"),
    )


class DockerMetricHourly(Base):
    """Hourly rollup of docker_metrics — avg cpu/mem per container per hour.

    Raw per-sample rows (~2880/container/day at 30s) are pruned beyond a short
    window; before deletion they're aggregated here so multi-day history stays
    cheap to store and query. One row per (host, container, hour bucket); the
    unique constraint lets retention upsert idempotently if it re-runs before the
    raw rows are deleted. `bucket` is the hour-truncated sample time.
    """
    __tablename__ = "docker_metrics_hourly"

    id: Mapped[str] = mapped_column(
        String(36), primary_key=True, default=lambda: str(uuid.uuid4())
    )
    host_id: Mapped[str] = mapped_column(
        String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False
    )
    container_name: Mapped[str] = mapped_column(String(255), nullable=False)
    bucket: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
    cpu_pct: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
    mem_pct: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
    mem_usage_bytes: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
    sample_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)

    __table_args__ = (
        # One bucket per container per host — the conflict target for the
        # idempotent rollup upsert; doubles as the history-query index.
        UniqueConstraint("host_id", "container_name", "bucket",
                         name="uq_docker_metrics_hourly_bucket"),
        Index("ix_docker_metrics_hourly_bucket", "bucket"),
    )


class DockerEvent(Base):
    """Lifecycle events derived by diffing consecutive host snapshots.

    The agent only reports current state, so Steward synthesises lifecycle by
    comparing each new snapshot against the stored DockerContainer state for the
    host: a container that appears → `start`; one that vanishes → `stop`; a
    transition to a stopped status with a non-zero exit → `die`; an OOM-kill
    flip → `oom`; a health status change → `health_change`. Scoped to the
    reporting host (names are only unique within a host). `event` is a plain
    string (no CHECK whitelist), matching how `status` is modelled on
    DockerContainer — keeps the value set open without a migration per addition.
    """
    __tablename__ = "docker_events"

    id: Mapped[str] = mapped_column(
        String(36), primary_key=True, default=lambda: str(uuid.uuid4())
    )
    host_id: Mapped[str] = mapped_column(
        String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False
    )
    container_name: Mapped[str] = mapped_column(String(255), nullable=False)
    event: Mapped[str] = mapped_column(String(16), nullable=False)
    # start | stop | die | oom | health_change
    detail: Mapped[str | None] = mapped_column(String(255), nullable=True)
    # e.g. "exit 137", "healthy→unhealthy", image on start
    at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), nullable=False,
        default=lambda: datetime.now(timezone.utc),
    )

    # Timeline lookups filter on (host_id, container_name) and sort by time;
    # retention prunes by `at` alone — index both access paths.
    __table_args__ = (
        Index("ix_docker_events_host_container_time",
              "host_id", "container_name", "at"),
        Index("ix_docker_events_at", "at"),
    )


class DockerSwarmService(Base):
    """A Swarm service as seen by a manager host: desired vs running replicas.

    Manager-scoped — only a host that is a Swarm manager reports these, so a
    single-manager cluster yields one row set keyed by that host. Service names
    are unique within a swarm; we still key by (host_id, service_name) so two
    managers reporting independently don't collide.
    """
    __tablename__ = "docker_swarm_services"

    host_id: Mapped[str] = mapped_column(
        String(36), ForeignKey("hosts.id", ondelete="CASCADE"), primary_key=True
    )
    service_name: Mapped[str] = mapped_column(String(255), primary_key=True)
    mode: Mapped[str] = mapped_column(String(16), nullable=False, default="replicated")
    # replicated | global
    desired: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
    running: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
    image: Mapped[str | None] = mapped_column(String(512), nullable=True)
    # task→node placement of running replicas: [{"node_id", "running"}], JSON.
    # A manager sees every task, so this captures cross-node placement that the
    # local docker_containers rows (this host only) can't.
    placement_json: Mapped[str] = mapped_column(Text, nullable=False, default="[]")
    updated_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), nullable=False,
        default=lambda: datetime.now(timezone.utc),
    )


class DockerSwarmNode(Base):
    """A Swarm node as seen by a manager host: role / availability / status."""
    __tablename__ = "docker_swarm_nodes"

    host_id: Mapped[str] = mapped_column(
        String(36), ForeignKey("hosts.id", ondelete="CASCADE"), primary_key=True
    )
    node_id: Mapped[str] = mapped_column(String(64), primary_key=True)
    hostname: Mapped[str] = mapped_column(String(255), nullable=False, default="")
    role: Mapped[str] = mapped_column(String(16), nullable=False, default="worker")
    # manager | worker
    availability: Mapped[str] = mapped_column(String(16), nullable=False, default="active")
    # active | pause | drain
    status: Mapped[str] = mapped_column(String(16), nullable=False, default="unknown")
    # ready | down | unknown
    leader: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
    updated_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), nullable=False,
        default=lambda: datetime.now(timezone.utc),
    )