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Merge remote-tracking branch 'upstream/llvmspirv_pulldown' into HEAD
Closes: #16484
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FROM docker.io/python:3.12 | ||
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COPY requirements.lock.txt ./ | ||
RUN pip3 install --no-cache-dir -r requirements.lock.txt | ||
COPY metrics.py ./ | ||
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CMD ["python3", "metrics.py"] |
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import requests | ||
import time | ||
import os | ||
from dataclasses import dataclass | ||
import sys | ||
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import github | ||
from github import Github | ||
from github import Auth | ||
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GRAFANA_URL = ( | ||
"https://influx-prod-13-prod-us-east-0.grafana.net/api/v1/push/influx/write" | ||
) | ||
GITHUB_PROJECT = "llvm/llvm-project" | ||
WORKFLOWS_TO_TRACK = ["Check code formatting"] | ||
SCRAPE_INTERVAL_SECONDS = 5 * 60 | ||
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@dataclass | ||
class JobMetrics: | ||
job_name: str | ||
queue_time: int | ||
run_time: int | ||
status: int | ||
created_at_ns: int | ||
workflow_id: int | ||
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def get_metrics(github_repo: github.Repository, workflows_to_track: dict[str, int]): | ||
"""Gets the metrics for specified Github workflows. | ||
This function takes in a list of workflows to track, and optionally the | ||
workflow ID of the last tracked invocation. It grabs the relevant data | ||
from Github, returning it to the caller. | ||
Args: | ||
github_repo: A github repo object to use to query the relevant information. | ||
workflows_to_track: A dictionary mapping workflow names to the last | ||
invocation ID where metrics have been collected, or None to collect the | ||
last five results. | ||
Returns: | ||
Returns a list of JobMetrics objects, containing the relevant metrics about | ||
the workflow. | ||
""" | ||
workflow_runs = iter(github_repo.get_workflow_runs()) | ||
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workflow_metrics = [] | ||
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workflows_to_include = set(workflows_to_track.keys()) | ||
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while len(workflows_to_include) > 0: | ||
workflow_run = next(workflow_runs) | ||
if workflow_run.status != "completed": | ||
continue | ||
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# This workflow was already sampled for this run, or is not tracked at | ||
# all. Ignoring. | ||
if workflow_run.name not in workflows_to_include: | ||
continue | ||
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# There were no new workflow invocations since the previous scrape. | ||
# The API returns a sorted list with the most recent invocations first, | ||
# so we can stop looking for this particular workflow. Continue to grab | ||
# information on the other workflows of interest, if present. | ||
if workflows_to_track[workflow_run.name] == workflow_run.id: | ||
workflows_to_include.remove(workflow_run.name) | ||
continue | ||
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workflow_jobs = workflow_run.jobs() | ||
if workflow_jobs.totalCount == 0: | ||
continue | ||
if workflow_jobs.totalCount > 1: | ||
raise ValueError( | ||
f"Encountered an unexpected number of jobs: {workflow_jobs.totalCount}" | ||
) | ||
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created_at = workflow_jobs[0].created_at | ||
started_at = workflow_jobs[0].started_at | ||
completed_at = workflow_jobs[0].completed_at | ||
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job_result = int(workflow_jobs[0].conclusion == "success") | ||
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queue_time = started_at - created_at | ||
run_time = completed_at - started_at | ||
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if run_time.seconds == 0: | ||
continue | ||
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if ( | ||
workflows_to_track[workflow_run.name] is None | ||
or workflows_to_track[workflow_run.name] == workflow_run.id | ||
): | ||
workflows_to_include.remove(workflow_run.name) | ||
if ( | ||
workflows_to_track[workflow_run.name] is not None | ||
and len(workflows_to_include) == 0 | ||
): | ||
break | ||
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# The timestamp associated with the event is expected by Grafana to be | ||
# in nanoseconds. | ||
created_at_ns = int(created_at.timestamp()) * 10**9 | ||
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workflow_metrics.append( | ||
JobMetrics( | ||
workflow_run.name, | ||
queue_time.seconds, | ||
run_time.seconds, | ||
job_result, | ||
created_at_ns, | ||
workflow_run.id, | ||
) | ||
) | ||
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return workflow_metrics | ||
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def upload_metrics(workflow_metrics, metrics_userid, api_key): | ||
"""Upload metrics to Grafana. | ||
Takes in a list of workflow metrics and then uploads them to Grafana | ||
through a REST request. | ||
Args: | ||
workflow_metrics: A list of metrics to upload to Grafana. | ||
metrics_userid: The userid to use for the upload. | ||
api_key: The API key to use for the upload. | ||
""" | ||
metrics_batch = [] | ||
for workflow_metric in workflow_metrics: | ||
workflow_formatted_name = workflow_metric.job_name.lower().replace(" ", "_") | ||
metrics_batch.append( | ||
f"{workflow_formatted_name} queue_time={workflow_metric.queue_time},run_time={workflow_metric.run_time},status={workflow_metric.status} {workflow_metric.created_at_ns}" | ||
) | ||
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request_data = "\n".join(metrics_batch) | ||
response = requests.post( | ||
GRAFANA_URL, | ||
headers={"Content-Type": "text/plain"}, | ||
data=request_data, | ||
auth=(metrics_userid, api_key), | ||
) | ||
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if response.status_code < 200 or response.status_code >= 300: | ||
print( | ||
f"Failed to submit data to Grafana: {response.status_code}", file=sys.stderr | ||
) | ||
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def main(): | ||
# Authenticate with Github | ||
auth = Auth.Token(os.environ["GITHUB_TOKEN"]) | ||
github_object = Github(auth=auth) | ||
github_repo = github_object.get_repo("llvm/llvm-project") | ||
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grafana_api_key = os.environ["GRAFANA_API_KEY"] | ||
grafana_metrics_userid = os.environ["GRAFANA_METRICS_USERID"] | ||
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workflows_to_track = {} | ||
for workflow_to_track in WORKFLOWS_TO_TRACK: | ||
workflows_to_track[workflow_to_track] = None | ||
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# Enter the main loop. Every five minutes we wake up and dump metrics for | ||
# the relevant jobs. | ||
while True: | ||
current_metrics = get_metrics(github_repo, workflows_to_track) | ||
if len(current_metrics) == 0: | ||
print("No metrics found to upload.", file=sys.stderr) | ||
continue | ||
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upload_metrics(current_metrics, grafana_metrics_userid, grafana_api_key) | ||
print(f"Uploaded {len(current_metrics)} metrics", file=sys.stderr) | ||
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for workflow_metric in reversed(current_metrics): | ||
workflows_to_track[workflow_metric.job_name] = workflow_metric.workflow_id | ||
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time.sleep(SCRAPE_INTERVAL_SECONDS) | ||
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if __name__ == "__main__": | ||
main() |
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