[llvm] [CI] Support multiple jobs in metrics container (PR #124457)

[Aiden Grossman via llvm-commits]

https://github.com/boomanaiden154 created https://github.com/llvm/llvm-project/pull/124457

This patch makes it so that the metrics script can support multiple jobs in a single workflow. This is needed so that we do not crash on an assertion now that the windows job has been enabled within the premerge workflow.

>From 71c132d21dbd966762de906d18dd9a228475843a Mon Sep 17 00:00:00 2001
From: Aiden Grossman <aidengrossman at google.com>
Date: Sun, 26 Jan 2025 09:34:35 +0000
Subject: [PATCH] [CI] Support multiple jobs in metrics container

This patch makes it so that the metrics script can support multiple jobs
in a single workflow. This is needed so that we do not crash on an
assertion now that the windows job has been enabled within the premerge
workflow.
---
 .ci/metrics/metrics.py | 85 ++++++++++++++++++++----------------------
 1 file changed, 41 insertions(+), 44 deletions(-)

diff --git a/.ci/metrics/metrics.py b/.ci/metrics/metrics.py
index 48d2aa2f330ec7..2fa726d45c708e 100644
--- a/.ci/metrics/metrics.py
+++ b/.ci/metrics/metrics.py
@@ -130,34 +130,6 @@ def get_per_workflow_metrics(
         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}"
-            )
-
-        created_at = workflow_jobs[0].created_at
-        started_at = workflow_jobs[0].started_at
-        completed_at = workflow_jobs[0].completed_at
-
-        job_result = int(workflow_jobs[0].conclusion == "success")
-        if job_result:
-            # We still might want to mark the job as a failure if one of the steps
-            # failed. This is required due to use setting continue-on-error in
-            # the premerge pipeline to prevent sending emails while we are
-            # testing the infrastructure.
-            # TODO(boomanaiden154): Remove this once the premerge pipeline is no
-            # longer in a testing state and we can directly assert the workflow
-            # result.
-            for step in workflow_jobs[0].steps:
-                if step.conclusion != "success":
-                    job_result = 0
-                    break
-
-        queue_time = started_at - created_at
-        run_time = completed_at - started_at
-
-        if run_time.seconds == 0:
-            continue
 
         if (
             workflows_to_track[workflow_run.name] is None
@@ -170,20 +142,45 @@ def get_per_workflow_metrics(
         ):
             break
 
-        # The timestamp associated with the event is expected by Grafana to be
-        # in nanoseconds.
-        created_at_ns = int(created_at.timestamp()) * 10**9
-
-        workflow_metrics.append(
-            JobMetrics(
-                workflow_run.name,
-                queue_time.seconds,
-                run_time.seconds,
-                job_result,
-                created_at_ns,
-                workflow_run.id,
+        for workflow_job in workflow_jobs:
+            created_at = workflow_job.created_at
+            started_at = workflow_job.started_at
+            completed_at = workflow_job.completed_at
+
+            job_result = int(workflow_job.conclusion == "success")
+            if job_result:
+                # We still might want to mark the job as a failure if one of the steps
+                # failed. This is required due to use setting continue-on-error in
+                # the premerge pipeline to prevent sending emails while we are
+                # testing the infrastructure.
+                # TODO(boomanaiden154): Remove this once the premerge pipeline is no
+                # longer in a testing state and we can directly assert the workflow
+                # result.
+                for step in workflow_job.steps:
+                    if step.conclusion != "success":
+                        job_result = 0
+                        break
+
+            queue_time = started_at - created_at
+            run_time = completed_at - started_at
+
+            if run_time.seconds == 0:
+                continue
+
+            # The timestamp associated with the event is expected by Grafana to be
+            # in nanoseconds.
+            created_at_ns = int(created_at.timestamp()) * 10**9
+
+            workflow_metrics.append(
+                JobMetrics(
+                    workflow_run.name + "-" + workflow_job.name,
+                    queue_time.seconds,
+                    run_time.seconds,
+                    job_result,
+                    created_at_ns,
+                    workflow_run.id,
+                )
             )
-        )
 
     return workflow_metrics
 
@@ -263,9 +260,9 @@ def main():
 
         for workflow_metric in reversed(current_metrics):
             if isinstance(workflow_metric, JobMetrics):
-                workflows_to_track[
-                    workflow_metric.job_name
-                ] = workflow_metric.workflow_id
+                workflows_to_track[workflow_metric.job_name] = (
+                    workflow_metric.workflow_id
+                )
 
         time.sleep(SCRAPE_INTERVAL_SECONDS)