Add a schema for source location.

This enables us to capture the full life of the container since the script can now be kicked off before the container is launched.

docker/scripts/graph_docker_memory.py

@@ -0,0 +1,167 @@
+#!/usr/bin/env python
+from __future__ import annotations
+
+import json
+import logging
+import re
+import subprocess
+from dataclasses import dataclass
+from datetime import datetime
+from time import sleep
+from typing import Collection, Final, NewType, Tuple
+
+ContainerId = NewType("ContainerId", str)
+ContainerName = NewType("ContainerName", str)
+
+SAMPLE_INTERVAL_SECONDS: Final[int] = 2
+
+
+@dataclass
+class Sample:
+    instant: datetime
+    stats: dict[ContainerId, Stats]
+
+
+@dataclass
+class Stats:
+    memory_usage_bytes: int
+
+
+def main():
+    logging.basicConfig(level=logging.INFO)
+    samples: list[Sample] = []
+    labels: dict[ContainerId, ContainerName] = {}
+    first_pass = True
+    # First wait for any docker container to exist.
+    while True:
+        sample, labels_in_sample = take_sample()
+        if labels_in_sample:
+            break
+        if first_pass:
+            first_pass = False
+            logging.info("Waiting for a docker container to exist to start recording.")
+        sleep(1)
+    # And then record memory until no containers exist.
+    while True:
+        sample, labels_in_sample = take_sample()
+        if not labels_in_sample:
+            break
+        samples.append(sample)
+        labels = {**labels, **labels_in_sample}
+        sleep(SAMPLE_INTERVAL_SECONDS)
+    if labels:
+        # Draws a red horizontal line at 32 GiB since that is the memory limit for cloud run.
+        write_plot(
+            samples,
+            labels,
+            # horizontal_lines=[(32 * 1024**3, "red", "Cloud Run Max Memory")],
+        )
+
+
+def write_plot(
+    samples: Collection[Sample],
+    labels: dict[ContainerId, ContainerName],
+    *,
+    horizontal_lines: Collection[Tuple[int, str, str | None]] = [],
+):
+    starting_time_per_container = {
+        container_id: min(
+            (sample.instant for sample in samples if container_id in sample.stats)
+        )
+        for container_id in labels.keys()
+    }
+    print(
+        """set terminal svg background '#FFFFFF'
+set title 'Docker Memory Usage'
+set xdata time
+set timefmt '%s'
+set format x '%tH:%tM:%tS'
+# Please note this is in SI units (base 10), not IEC (base 2). So, for example, this would show a Gigabyte, not a Gibibyte.
+set format y '%.0s%cB'
+set datafile separator "|"
+"""
+    )
+    for y_value, color, label in horizontal_lines:
+        print(
+            f'''set arrow from graph 0, first {y_value} to graph 1, first {y_value} nohead linewidth 2 linecolor rgb "{color}"'''
+        )
+        if label is not None:
+            print(f"""set label "{label}" at graph 0, first {y_value} offset 1,-0.5""")
+
+    # Include the horizontal lines in the range
+    if len(horizontal_lines) > 0:
+        print(f"""set yrange [*:{max(x[0] for x in horizontal_lines)}<*]""")
+    line_definitions = ", ".join(
+        [
+            f""""-" using 1:2 title '{gnuplot_escape(name)}' with lines"""
+            for container_id, name in sorted(labels.items())
+        ]
+    )
+    print("plot", line_definitions)
+    for container_id in sorted(labels.keys()):
+        start_time = int(starting_time_per_container[container_id].timestamp())
+        for sample in sorted(samples, key=lambda x: x.instant):
+            if container_id in sample.stats:
+                print(
+                    "|".join(
+                        [
+                            str(int((sample.instant).timestamp()) - start_time),
+                            str(sample.stats[container_id].memory_usage_bytes),
+                        ]
+                    )
+                )
+        print("e")
+
+
+def gnuplot_escape(inp: str) -> str:
+    out = ""
+    for c in inp:
+        if c == "_":
+            out += "\\"
+        out += c
+    return out
+
+
+def take_sample() -> Tuple[Sample, dict[ContainerId, ContainerName]]:
+    labels: dict[ContainerId, ContainerName] = {}
+    stats: dict[ContainerId, Stats] = {}
+    docker_inspect = subprocess.run(
+        ["docker", "stats", "--no-stream", "--no-trunc", "--format", "json"],
+        stdout=subprocess.PIPE,
+    )
+    for container_stat in (
+        json.loads(l) for l in docker_inspect.stdout.decode("utf8").splitlines()
+    ):
+        if not container_stat["ID"]:
+            # When containers are starting up, they sometimes have no ID and "--" as the name.
+            continue
+        labels[ContainerId(container_stat["ID"])] = ContainerName(
+            container_stat["Name"]
+        )
+        memory_usage = parse_mem_usage(container_stat["MemUsage"])
+        stats[ContainerId(container_stat["ID"])] = Stats(
+            memory_usage_bytes=memory_usage
+        )
+    for container_id, container_stat in stats.items():
+        logging.info(
+            f"Recorded stat {labels[container_id]}: {container_stat.memory_usage_bytes} bytes"
+        )
+    return Sample(instant=datetime.now(), stats=stats), labels
+
+
+def parse_mem_usage(mem_usage: str) -> int:
+    parsed_mem_usage = re.match(
+        r"(?P<number>[0-9]+\.?[0-9]*)(?P<unit>[^\s]+)", mem_usage
+    )
+    if parsed_mem_usage is None:
+        raise Exception(f"Invalid Mem Usage: {mem_usage}")
+    number = float(parsed_mem_usage.group("number"))
+    unit = parsed_mem_usage.group("unit")
+    for multiplier, identifier in enumerate(["B", "KiB", "MiB", "GiB", "TiB"]):
+        if unit == identifier:
+            return int(number * (1024**multiplier))
+    raise Exception(f"Unrecognized unit: {unit}")
+
+
+if __name__ == "__main__":
+    main()

google_cloud_auth/fetch_token_from_metadata_server.bash

@@ -0,0 +1,2 @@
+curl "http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/identity?audience=AUDIENCE" \
+     -H "Metadata-Flavor: Google"

google_cloud_logging/log_stream/log_stream/log_entry.py

@@ -0,0 +1,86 @@
+from __future__ import annotations
+from enum import Enum
+from typing import Annotated, Union
+from pydantic import BaseModel, Field, TypeAdapter
+
+
+class BaseLogEntry(BaseModel):
+    # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry
+
+    log_name: Annotated[str, Field(alias="logName")]
+    resource: dict  # https://cloud.google.com/logging/docs/reference/v2/rest/v2/MonitoredResource
+
+    timestamp: str
+    receive_timestamp: Annotated[str, Field(alias="receiveTimestamp")]
+    severity: LogSeverity
+    insert_id: Annotated[str, Field(alias="insertId")]
+    http_request: Annotated[
+        dict | None, Field(alias="httpRequest", default=None)
+    ]  # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#HttpRequest
+    labels: Annotated[dict[str, str] | None, Field(default=None)]
+    metadata: Annotated[
+        dict | None, Field(default=None)
+    ]  # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#MonitoredResourceMetadata
+    operation: Annotated[
+        dict | None, Field(default=None)
+    ]  # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#LogEntryOperation
+    trace: Annotated[str | None, Field(default=None)]
+    span_id: Annotated[str | None, Field(alias="spanId", default=None)]
+    trace_sampled: Annotated[bool | None, Field(alias="traceSampled", default=None)]
+    source_location: Annotated[
+        SourceLocation | None, Field(alias="sourceLocation", default=None)
+    ]
+    split: Annotated[
+        dict | None, Field(default=None)
+    ]  # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#LogSplit
+    error_groups: Annotated[
+        list[dict] | None, Field(alias="errorGroups", default=None)
+    ]  # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#LogErrorGroup
+    apphub: Annotated[
+        dict | None, Field(default=None)
+    ]  # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#AppHub
+
+
+class ProtoPayloadLogEntry(BaseLogEntry):
+    # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry
+    proto_payload: Annotated[dict, Field(alias="protoPayload")]
+
+
+class TextPayloadLogEntry(BaseLogEntry):
+    # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry
+    text_payload: Annotated[str, Field(alias="textPayload")]
+
+
+class JsonPayloadLogEntry(BaseLogEntry):
+    # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry
+    json_payload: Annotated[dict, Field(alias="jsonPayload")]
+
+
+LogEntry = Annotated[
+    Union[ProtoPayloadLogEntry, JsonPayloadLogEntry, TextPayloadLogEntry, BaseLogEntry],
+    Field(),
+]
+
+
+class LogSeverity(str, Enum):
+    # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#LogSeverity
+    DEFAULT = "DEFAULT"
+    DEBUG = "DEBUG"
+    INFO = "INFO"
+    NOTICE = "NOTICE"
+    WARNING = "WARNING"
+    ERROR = "ERROR"
+    CRITICAL = "CRITICAL"
+    ALERT = "ALERT"
+    EMERGENCY = "EMERGENCY"
+
+
+class SourceLocation(BaseModel):
+    # https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#LogEntrySourceLocation
+    file: str
+    line: str
+    function: Annotated[str | None, Field(default=None)]
+
+
+def create_log_entry(entry: dict) -> LogEntry:
+    return TypeAdapter(LogEntry).validate_python(entry)

google_cloud_logging/log_stream/log_stream/log_stream.py

@@ -0,0 +1,127 @@
+from __future__ import annotations
+from collections import deque
+from datetime import datetime, timezone
+from logging import getLogger
+import json
+from typing import Callable, Final, Iterator
+from pydantic import ValidationError
+import requests
+
+from log_stream.log_entry import create_log_entry, LogEntry
+
+BATCH_SIZE: Final[int] = 1000
+REQ_TIMEOUT: Final[int] = 60
+logger = getLogger("LogStream")
+
+
+class LogStream:
+    _query: str
+    _project: str
+    _start_date: datetime
+    _end_date: datetime
+    _buffer: deque[dict]
+    _finished: bool
+    _next_page_token: str | None
+    _session: requests.Session
+    _access_token: Callable[[], str]
+
+    def __init__(
+        self,
+        query: str,
+        project: str,
+        start_date: datetime,
+        end_date: datetime | None,
+        access_token: Callable[[], str],
+    ) -> None:
+        self._query = query
+        self._project = project
+        self._start_date = start_date
+        self._end_date = (
+            end_date if end_date is not None else datetime.now(timezone.utc)
+        )
+        self._buffer = deque(maxlen=BATCH_SIZE)
+        self._finished = False
+        self._next_page_token = None
+        self._session = requests.Session()
+        self._access_token = access_token
+
+    def parsed(self) -> ParsedLogStream:
+        return ParsedLogStream(self)
+
+    def __iter__(self) -> Iterator[dict]:
+        return self
+
+    def __next__(self) -> dict:
+        if len(self._buffer) == 0 and not self._finished:
+            self._populate_buffer()
+
+        if len(self._buffer) == 0:
+            self._finished = True
+            raise StopIteration()
+
+        return self._buffer.popleft()
+
+    def _populate_buffer(self) -> None:
+        # https://cloud.google.com/logging/docs/reference/v2/rest/v2/entries/list
+        data = {
+            "filter": "\n".join((self._get_timestamp_filter(), self._query)),
+            "orderBy": "timestamp desc",
+            "pageSize": BATCH_SIZE,
+            "resourceNames": [f"projects/{self._project}"],
+        }
+        if self._next_page_token is not None:
+            data["pageToken"] = self._next_page_token
+        headers = {
+            "Authorization": f"Bearer {self._access_token()}",
+            "x-goog-user-project": self._project,
+        }
+        req = requests.Request(
+            "POST",
+            "https://logging.googleapis.com/v2/entries:list",
+            data=data,
+            headers=headers,
+        )
+        prepared = self._session.prepare_request(req)
+        logger.info(f"Sending a request to {prepared.url}")
+        response = self._session.send(
+            prepared,
+            timeout=REQ_TIMEOUT,
+        )
+        response.raise_for_status()
+        response_body = response.json()
+        if (token := response_body.get("nextPageToken")) is not None:
+            self._next_page_token = token
+        else:
+            self._finished = True
+            self._next_page_token = None
+
+        self._buffer.extend(response_body.get("entries", []))
+
+    def _get_timestamp_filter(self) -> str:
+        time_format = "%Y-%m-%dT%H:%M:%S.%fZ"
+        self._start_date.isoformat()
+        # TODO: convert start/end date to UTC
+        start = self._start_date.strftime(time_format)
+        end = self._end_date.strftime(time_format)
+        return f"""
+        timestamp>="{start}"
+        timestamp<="{end}"
+        """
+
+
+class ParsedLogStream:
+    _inner: LogStream
+
+    def __init__(self, inner: LogStream) -> None:
+        self._inner = inner
+
+    def __iter__(self) -> Iterator[LogEntry]:
+        return self
+
+    def __next__(self) -> LogEntry:
+        raw = next(self._inner)
+        try:
+            return create_log_entry(raw)
+        except ValidationError as e:
+            logger.error("Failed to parse log message: %s", json.dumps(raw))
+            raise

google_cloud_logging/log_stream/log_stream/main.py

@@ -0,0 +1,54 @@
+from datetime import datetime, timezone, timedelta
+import logging
+import logging.config
+import json
+import os
+
+from pydantic import ValidationError
+
+from log_stream.log_stream import LogStream
+
+
+def main():
+    setup_logging()
+    log_query = """
+    severity>="ERROR"
+    """
+    now = datetime.now(timezone.utc)
+    one_week_ago = now - timedelta(days=7)
+    project = os.environ.get("CLOUDSDK_CORE_PROJECT")
+    assert isinstance(project, str)
+    access_token = os.environ.get("ACCESS_TOKEN")
+    assert isinstance(access_token, str)
+    logs = LogStream(log_query, project, one_week_ago, now, lambda: access_token)
+    for log in logs.parsed():
+        print(log.model_dump_json())
+
+
+def setup_logging():
+    logging_config = {
+        "version": 1,
+        "disable_existing_loggers": False,
+        "formatters": {
+            "regular": {
+                "format": "%(asctime)s %(name)-12s %(levelname)-8s %(message)s",
+            }
+        },
+        "handlers": {
+            "console": {
+                "class": "logging.StreamHandler",
+                "level": "INFO",
+                "formatter": "regular",
+            }
+        },
+        "root": {
+            "handlers": ["console"],
+            "level": "INFO",
+        },
+        "loggers": {"LogStream": {"level": "WARNING"}},
+    }
+    logging.config.dictConfig(logging_config)
+
+
+if __name__ == "__main__":
+    main()

google_cloud_logging/log_stream/poetry.lock

@@ -0,0 +1,473 @@
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+
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+
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+pathspec = ">=0.9.0"
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+
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+colorama = ["colorama (>=0.4.3)"]
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+urllib3 = ">=1.21.1,<3"
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+h2 = ["h2 (>=4,<5)"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
+
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google_cloud_logging/log_stream/pyproject.toml

@@ -0,0 +1,17 @@
+[tool.poetry]
+name = "log-stream"
+version = "0.0.0"
+description = "Stream logs from google cloud logging into python."
+authors = []
+
+[tool.poetry.dependencies]
+python = ">=3.11"
+requests = "^2.32.3"
+pydantic = "^2.11.4"
+
+[tool.poetry.group.dev.dependencies]
+black = "^24.1.1"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

google_cloud_logging/queries/compute_engine/instance_start

@@ -0,0 +1 @@
+protoPayload.methodName="v1.compute.instances.start"

google_cloud_logging/queries/compute_engine/instance_stop

@@ -0,0 +1 @@
+protoPayload.methodName="v1.compute.instances.stop"

google_cloud_logging/queries/dataflow/dataflow_job_created

@@ -0,0 +1 @@
+protoPayload.methodName="dataflow.jobs.create"

google_cloud_logging/queries/google_cloud_services/enable_or_disable_service

@@ -0,0 +1 @@
+(protoPayload.methodName="google.api.serviceusage.v1.ServiceUsage.EnableService" OR protoPayload.methodName="google.api.serviceusage.v1.ServiceUsage.DisableService")

google_cloud_logging/queries/kubernetes/oom

@@ -0,0 +1 @@
+"OOMKilling"

google_cloud_logging/queries/timestamp/explicit_range

@@ -0,0 +1,2 @@
+timestamp <= "2024-06-27T00:00:00.000000Z"
+timestamp >= "2024-01-01T00:00:00.000000Z"

google_cloud_logging/queries/vertex_ai_agent_builder/get_requests_for_engines

@@ -0,0 +1 @@
+textPayload=~"HTTP Request: POST https://us-discoveryengine.googleapis.com/[^\s/]+/projects/[^\s/]+/locations/us/collections/[^\s/]+/engines/[^\s/]+/"

metrics_explorer/over_provisioned/cloud_run_job/notes.org

@@ -0,0 +1,21 @@
+* Metrics Explorer PromQL Queries
+** Cloud Run Job Memory Utilization
+Line is a percent of memory usage.
+#+begin_src text
+  histogram_quantile(0.99,sum by (job_name,le)(increase(run_googleapis_com:container_memory_utilizations_bucket{monitored_resource="cloud_run_job"}[${__interval}])))
+#+end_src
+** Memory usage bytes
+#+begin_src text
+  histogram_quantile(0.50,sum_over_time(run_googleapis_com:container_memory_usage_bucket{monitored_resource="cloud_run_job"}[${__interval}]))
+#+end_src
+** Memory allocation
+#+begin_src text
+  sum by (job_name)(rate(run_googleapis_com:container_memory_allocation_time{monitored_resource="cloud_run_job"}[${__interval}]))
+#+end_src
+** Difference
+#+begin_src text
+  sum by (job_name)(
+      rate(run_googleapis_com:container_memory_allocation_time{monitored_resource="cloud_run_job"}[${__interval}])
+      - rate(run_googleapis_com:container_memory_usage_bucket{monitored_resource="cloud_run_job"}[${__interval}])
+      )
+#+end_src

metrics_explorer/pod_memory_limit/promql

@@ -0,0 +1 @@
+sum by (pod_name)(avg_over_time(kubernetes_io:container_memory_limit_bytes{monitored_resource="k8s_container",container_name=~".*airflow-worker.*"}[${__interval}]))