Add DAG for verifying TensorCore utilization metrics with jobset monitoring #1119
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…toring This PR introduces a new DAG, `jobset_uptime_validation`, designed to automate the functional testing and verification of JobSet uptime metrics on GKE TPU clusters. - Workload Execution JobSet Deployment: Deploys a JobSet with 4 completions and 1 replica. It uses the tpu-info:v0.5.1 image to run a JAX benchmark. - Metric Validation Logic The validation is split into two phases: Positive Test (Wait for Uptime): Objective: Confirms that the uptime metric is successfully exported to Cloud Monitoring after the JobSet is applied. Negative Test (Verify No Data): Objective: Ensures that no "ghost data" or incorrect historical values persist during stability checks.
chengpinglin
requested review from
alfredyu-cienet,
andrewyct,
severus-ho and
xibinliu
as code owners
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Description
This PR introduces a new DAG, jobset_uptime_validation, designed to automate the functional testing and verification of JobSet uptime metrics on GKE TPU clusters.
Workload Execution
JobSet Deployment: Deploys a JobSet with 4 completions and 1 replica. It uses the tpu-info:v0.5.1 image to run a JAX benchmark.
Metric Validation Logic
The validation is split into two phases:
Positive Test (Wait for Uptime)
Objective: Confirms that the uptime metric is successfully exported to Cloud Monitoring after the JobSet is applied.
Negative Test (Verify No Data)
Objective: Ensures that no "ghost data" or incorrect historical values persist during stability checks.
Tests
cloud-ml-auto-solutions)2.13.1Checklist
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