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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+]
+
+[package.dependencies]
+typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
+
+[[package]]
+name = "requests"
+version = "2.32.3"
+description = "Python HTTP for Humans."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
+    {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
+]
+
+[package.dependencies]
+certifi = ">=2017.4.17"
+charset-normalizer = ">=2,<4"
+idna = ">=2.5,<4"
+urllib3 = ">=1.21.1,<3"
+
+[package.extras]
+socks = ["PySocks (>=1.5.6,!=1.5.7)"]
+use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
+
+[[package]]
+name = "typing-extensions"
+version = "4.13.2"
+description = "Backported and Experimental Type Hints for Python 3.8+"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "typing_extensions-4.13.2-py3-none-any.whl", hash = "sha256:a439e7c04b49fec3e5d3e2beaa21755cadbbdc391694e28ccdd36ca4a1408f8c"},
+    {file = "typing_extensions-4.13.2.tar.gz", hash = "sha256:e6c81219bd689f51865d9e372991c540bda33a0379d5573cddb9a3a23f7caaef"},
+]
+
+[[package]]
+name = "typing-inspection"
+version = "0.4.0"
+description = "Runtime typing introspection tools"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "typing_inspection-0.4.0-py3-none-any.whl", hash = "sha256:50e72559fcd2a6367a19f7a7e610e6afcb9fac940c650290eed893d61386832f"},
+    {file = "typing_inspection-0.4.0.tar.gz", hash = "sha256:9765c87de36671694a67904bf2c96e395be9c6439bb6c87b5142569dcdd65122"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.12.0"
+
+[[package]]
+name = "urllib3"
+version = "2.4.0"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813"},
+    {file = "urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466"},
+]
+
+[package.extras]
+brotli = ["brotli (>=1.0.9) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\""]
+h2 = ["h2 (>=4,<5)"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
+
+[metadata]
+lock-version = "2.1"
+python-versions = ">=3.11"
+content-hash = "cc9fea2ced97263679d49067a40c51d60fa99df1b28bc61942c32127afe2d704"

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/]+/"

kubernetes/autoscale/k8s/autoscale.yaml

@@ -0,0 +1,70 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: autoscale-test
+  namespace: default
+spec:
+  selector:
+    matchLabels:
+      app: autoscale-test
+  template:
+    metadata:
+      labels:
+        app: autoscale-test
+    spec:
+      containers:
+        - name: echoservice
+          image: gcr.io/hip-wharf-319304/echoservice:latest
+          imagePullPolicy: Always
+          env:
+            - name: "WORKERS"
+              value: "8"
+          ports:
+            - name: http
+              containerPort: 8080
+              protocol: TCP
+          livenessProbe:
+            httpGet:
+              path: /
+              port: http
+          readinessProbe:
+            httpGet:
+              path: /
+              port: http
+          resources:
+            requests:
+              cpu: "250m"
+              memory: "256Mi"
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: autoscale-test
+  namespace: default
+spec:
+  selector:
+    app: autoscale-test
+  type: LoadBalancer
+  ports:
+    - port: 80
+      targetPort: "http"
+---
+apiVersion: autoscaling/v2beta2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: autoscale-test
+  namespace: default
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: autoscale-test
+  minReplicas: 1
+  maxReplicas: 10
+  metrics:
+    - type: Resource
+      resource:
+        name: cpu
+        target:
+          type: Utilization
+          averageUtilization: 50

kubernetes/autoscale/service/Dockerfile

@@ -0,0 +1,17 @@
+FROM python:3.9
+
+RUN useradd -m -g nogroup server
+USER server
+
+WORKDIR /home/server
+ENV FLASK_APP=main.py
+
+# Perform the install of requirements first to avoid re-installing on every code change
+COPY requirements.txt /home/server/
+RUN pip install -r /home/server/requirements.txt
+
+COPY *.py /home/server/
+
+# CMD ["python", "/home/server/main.py"]
+
+CMD ["/home/server/.local/bin/gunicorn", "--config", "/home/server/gunicorn.conf.py", "main:app"]

kubernetes/autoscale/service/Makefile

@@ -0,0 +1,22 @@
+IMAGE_NAME:=echoservice
+GCP_PROJECT:=hip-wharf-319304
+
+.PHONY: all
+all: build push
+
+.PHONY: build
+build:
+	docker build -t $(IMAGE_NAME) .
+
+.PHONY: push
+push:
+	docker tag $(IMAGE_NAME) gcr.io/$(GCP_PROJECT)/$(IMAGE_NAME)
+	docker push gcr.io/$(GCP_PROJECT)/$(IMAGE_NAME)
+
+.PHONY: clean
+clean:
+	docker rmi $(IMAGE_NAME) gcr.io/$(GCP_PROJECT)/$(IMAGE_NAME) $(IMAGE_NAME)
+
+.PHONY: run
+run:
+	docker run --rm -i -t -p "8080:8080" $(IMAGE_NAME)

kubernetes/autoscale/service/gunicorn.conf.py

@@ -0,0 +1,9 @@
+import os
+
+env_port = int(os.environ.get("PORT", 8080))
+
+bind = f"0.0.0.0:{env_port}"
+workers = int(os.environ.get("WORKERS", 8))
+preload_app = True
+max_requests = 100
+max_requests_jitter = 50

kubernetes/autoscale/service/main.py

@@ -0,0 +1,28 @@
+import json
+import os
+
+from flask import Flask, request
+
+app = Flask(__name__)
+
+
+def get_request_params():
+    request_json = request.get_json(silent=True)
+    request_args = request.args
+    if request_json:
+        return request_json
+    elif request_args:
+        return request_args
+    else:
+        return None
+
+
+@app.route("/", methods=("GET", "POST"))
+def index():
+    return json.dumps(
+        {"headers": {k: v for k, v in request.headers}, "params": get_request_params()}
+    )
+
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=int(os.environ.get("PORT", 8080)), debug=True)

kubernetes/autoscale/service/requirements.txt

@@ -0,0 +1,2 @@
+flask==1.1.2
+gunicorn==20.1.0

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}]))

terraform/basic_gke/main.tf

@@ -207,16 +207,43 @@ module "cf_to_pubsub" {
   source               = "../modules/cf_to_pubsub"
   project              = var.project
   region               = var.region
-  topic_name         = "bigquery-etl"
+  function_name        = "cf-to-pubsub"
+  function_description = "CloudFunction to PubSub"
+  function_source_name = "cf_to_pubsub"
   source_bucket        = google_storage_bucket.bucket
   service_cloudbuild   = google_project_service.cloudbuild
+
+  environment_variables = {
+    GCP_PROJECT = var.project
+    GCP_TOPIC   = "bigquery-etl"
+  }
 }
 
-output "log_to_bq_endpoint" {
+output "cf_to_pubsub_endpoint" {
-  description = "https endpoint to log to BigQuery."
+  description = "https endpoint to log to BigQuery through pubsub."
   value       = module.cf_to_pubsub.https_trigger_url
 }
 
+module "cf_to_bq" {
+  source               = "../modules/cf_to_pubsub"
+  project              = var.project
+  region               = var.region
+  function_name        = "cf-to-bq"
+  function_description = "CloudFunction to BigQuery"
+  function_source_name = "cf_to_bq"
+  source_bucket        = google_storage_bucket.bucket
+  service_cloudbuild   = google_project_service.cloudbuild
+
+  environment_variables = {
+    BQ_TABLE = "${var.project}.pubsub_etl.pubsub_etl"
+  }
+}
+
+output "cf_to_bq_endpoint" {
+  description = "https endpoint to log to BigQuery directly."
+  value       = module.cf_to_bq.https_trigger_url
+}
+
 #################### PubSub to BigQuery ###################
 
 module "bigquery" {

terraform/modules/bigquery/bigquery.tf

@@ -99,9 +99,13 @@ resource "google_project_service" "dataflow" {
   disable_dependent_services = true
 }
 
+resource "random_id" "temp_storage" {
+  byte_length = 4
+}
+
 resource "google_storage_bucket" "temp_storage" {
   project       = var.project
-  name          = "${var.project}-bigquery-etl"
+  name          = "${var.project}-etl-temp-${random_id.temp_storage.hex}"
   force_destroy = true
 }
 

terraform/modules/cf_to_pubsub/cf_to_pubsub.tf

@@ -11,9 +11,22 @@ variable "region" {
   type        = string
 }
 
-variable "topic_name" {
+variable "function_name" {
-  description = "The name of topic where the events should be published."
+  description = "Name for the cloud function. If unspecified, one will be generated."
   type        = string
+  default     = ""
+}
+
+variable "function_description" {
+  description = "Description for the cloud function."
+  type        = string
+  default     = ""
+}
+
+variable "environment_variables" {
+  description = "Environment variables for the execution of the cloud function."
+  type        = map(any)
+  default     = {}
 }
 
 variable "source_bucket" {
@@ -23,11 +36,16 @@ variable "source_bucket" {
 variable "function_source_name" {
   description = "Name of the folder containing the source code for the function."
   type        = string
-  default     = "cf_to_pubsub"
 }
 
 variable "service_cloudbuild" {
-  description = "THe cloudbuild google_project_service."
+  description = "The cloudbuild google_project_service."
+}
+
+variable "allow_external" {
+  description = "Whether or not to allow outside traffic ingress."
+  type        = bool
+  default     = true
 }
 
 output "https_trigger_url" {
@@ -35,6 +53,14 @@ output "https_trigger_url" {
   value       = google_cloudfunctions_function.function.https_trigger_url
 }
 
+locals {
+  function_name = var.function_name == "" ? "cf-${random_id.function_id.hex}" : var.function_name
+}
+
+resource "random_id" "function_id" {
+  byte_length = 4
+}
+
 resource "random_id" "cf_bucket_id" {
   byte_length = 4
 }
@@ -53,8 +79,8 @@ resource "google_storage_bucket_object" "remote_archive" {
 }
 
 resource "google_cloudfunctions_function" "function" {
-  name        = "cf-to-pubsub"
+  name        = local.function_name
-  description = "CloudFunction to PubSub"
+  description = var.function_description
   runtime     = "python39"
 
   available_memory_mb   = 128
@@ -63,13 +89,9 @@ resource "google_cloudfunctions_function" "function" {
   trigger_http          = true
   entry_point           = "main"
   max_instances         = 4
-  ingress_settings      = "ALLOW_ALL"
+  ingress_settings      = var.allow_external ? "ALLOW_ALL" : "ALLOW_INTERNAL_ONLY"
-  # ingress_settings      = "ALLOW_INTERNAL_ONLY"
 
-  environment_variables = {
+  environment_variables = var.environment_variables
-    GCP_PROJECT = var.project
-    GCP_TOPIC   = var.topic_name
-  }
 
   depends_on = [
     var.service_cloudbuild

terraform/modules/cf_to_pubsub/functions/cf_to_bq/main.py

@@ -0,0 +1,25 @@
+import json
+import os
+
+from google.cloud import bigquery
+
+client = bigquery.Client()
+
+
+def push_to_pubsub(request_params):
+    errors = client.insert_rows_json(os.environ["BQ_TABLE"], [request_params])
+    if errors != []:
+        raise Exception("Encountered errors while inserting rows: {}".format(errors))
+
+
+def main(request):
+    request_json = request.get_json(silent=True)
+    request_args = request.args
+
+    if request_json:
+        push_to_pubsub(request_json)
+    elif request_args:
+        push_to_pubsub(request_args)
+    else:
+        return ("No data provided.", 400)
+    return {"status": "ok", "source": "cf_to_bq"}

terraform/modules/cf_to_pubsub/functions/cf_to_bq/requirements.txt

@@ -0,0 +1,2 @@
+Flask==1.1.2
+google-cloud-bigquery==2.22.0

terraform/modules/cf_to_pubsub/functions/cf_to_pubsub/main.py

@@ -4,7 +4,7 @@ import os
 from google.cloud import pubsub_v1
 
 publisher = pubsub_v1.PublisherClient()
-topic = publisher.topic_path(os.environ.get("GCP_PROJECT"), os.environ.get("GCP_TOPIC"))
+topic = publisher.topic_path(os.environ["GCP_PROJECT"], os.environ["GCP_TOPIC"])
 
 
 def push_to_pubsub(request_params):
@@ -20,5 +20,5 @@ def main(request):
     elif request_args:
         push_to_pubsub(request_args)
     else:
-        raise Exception("No data provided.")
+        return ("No data provided.", 400)
-    return {"status": "ok"}
+    return {"status": "ok", "source": "cf_to_pubsub"}