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fix(docker): widen memory byte columns to BIGINT (int32 overflow on ingest)
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docker_metrics.mem_usage_bytes and docker_containers.mem_usage_bytes /
mem_limit_bytes were int4 (max 2,147,483,647). A container using >2.1 GB of RAM
(e.g. 8.18 GB) overflowed the column, so asyncpg raised "value out of int32
range" and the entire docker ingest batch failed — no metrics stored for any
host with a large container.

The I/O counters and the milestone-77 rollup/disk tables already used
BigInteger; this trio (docker_001-era) was missed.

- models.py: DockerMetric.mem_usage_bytes, DockerContainer.mem_usage_bytes,
  DockerContainer.mem_limit_bytes → BigInteger.
- migration docker_008_bigint_mem: ALTER COLUMN ... TYPE BIGINT (safe in-place
  int4→int8 promotion).
- integration regression test: persist an ~8 GB container, assert the
  current-state and time-series rows round-trip.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016Jg27rgypiW2efULXJDtMC
This commit is contained in:
Bryan Van Deusen
2026-06-19 22:50:32 -04:00
parent c8b6719b37
commit 2545e8c6ce
3 changed files with 79 additions and 3 deletions
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plugins/docker/models.py
+6 -3
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@@ -29,8 +29,10 @@ class DockerContainer(Base):
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)
# BigInteger: a container's memory usage/limit routinely exceeds 2^31 bytes
# (~2.1 GB), which overflows int4 and fails the insert.
mem_usage_bytes: Mapped[int | None] = mapped_column(BigInteger, nullable=True)
mem_limit_bytes: Mapped[int | None] = mapped_column(BigInteger, 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="[]")
@@ -78,7 +80,8 @@ class DockerMetric(Base):
)
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)
# BigInteger: per-container memory usage exceeds 2^31 bytes (~2.1 GB) routinely.
mem_usage_bytes: Mapped[int] = mapped_column(BigInteger, 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.