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Build a Thermal Throttling Incident Timeline and Operator Rebalancing Engine

Analyze time-series DCGM thermal logs during server throttling events. Hosted Claude reconstructs event sequences and drafts operator chassis airflow mitigation recommendations.

EngineeringHosted by Vera

What you are building

Analyze time-series DCGM thermal logs during server throttling events. Hosted Claude reconstructs event sequences and drafts operator chassis airflow mitigation recommendations.

Datacenter Operations Engineer

Parse normalized DCGM time-series telemetry records including GPU temperatures, power draw, and throttle flags.

Reconstruct the chronological timeline of temperature breaches and clock frequency reductions across affected chassis slots.

Send chronological telemetry logs to hosted Claude to isolate thermal runaways and formulate remediation steps.

Produce a structured operator inspection runbook containing fan curves and workload throttling mitigations.

Web dashboard showing thermal excursion graphs and human operator sign-off panels.

Construct synthetic DCGM CSV files recording timestamps, device index, temperature, power draw, and throttling duration. Starter examples below are synthetic. They are not downloaded records.

NVIDIA DCGM exporter Consumes standardized DCGM exporter metric types such as GPU temperature and throttling reason indicators.

mlflow, anthropic, pandas, pydantic. MLflow tracks thermal event runs, metric parameters, and operational remediation artifacts across historical incidents. Hosted Claude API for narrative incident root-cause reconstruction and mitigation generation.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Correctly identifies the exact primary throttle timestamp and initial trigger temperature.

Flags secondary cascading device throttling events occurring within 120 seconds of the primary trigger.

Produces actionable mitigation runbook with rack slot locations verified by human sign-off.

```json [ { "input": { "chassis_id": "rack-4-blade-02", "telemetry_stream": [ { "timestamp": "2025-06-01T10:00:00Z", "gpu_idx": 0, "temp_c": 74, "throttle_active": false, "clock_mhz": 1800 }, { "timestamp": "2025-06-01T10:01:00Z", "gpu_idx": 0, "temp_c": 86, "throttle_active": true, "clock_mhz": 1150 }, { "timestamp": "2025-06-01T10:01:30Z", "gpu_idx": 1, "temp_c": 84, "throttle_active": true, "clock_mhz": 1200 } ] }, "expected_output": { "incident_detected": true, "primary_trigger": { "timestamp": "2025-06-01T10:01:00Z", "gpu_idx": 0, "temp_c": 86 }, "cascading_count": 1, "recommended_action": "INSPECT_BLADE_FAN_BAFFLE" } }, { "input": { "chassis_id": "rack-4-blade-05", "telemetry_stream": [ { "timestamp": "2025-06-01T11:00:00Z", "gpu_idx": 0, "temp_c": 68, "throttle_active": false, "clock_mhz": 1800 }, { "timestamp": "2025-06-01T11:01:00Z", "gpu_idx": 0, "temp_c": 70, "throttle_active": false, "clock_mhz": 1800 } ] }, "expected_output": { "incident_detected": false, "primary_trigger": null, "cascading_count": 0, "recommended_action": "MAINTAIN_CURRENT_COOLING" } } ] ```

Read-only simulated diagnostics. Does not adjust physical fan controllers or alter operational firmware settings. Use mock external writes. Require human review before any real deployment.

Rules

Read-only simulated diagnostics. Does not adjust physical fan controllers or alter operational firmware settings. Use mock external writes and human review.

How work is evaluated

Evaluation

Correctly identifies the exact primary throttle timestamp and initial trigger temperature. Flags secondary cascading device throttling events occurring within 120 seconds of the primary trigger. Produces actionable mitigation runbook with rack slot locations verified by human sign-off.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Parse normalized DCGM time-series telemetry records including GPU temperatures, power draw, and throttle flags. Reconstruct the chronological timeline of temperature breaches and clock frequency reductions across affected chassis slots. Send chronological telemetry logs to hosted Claude to isolate thermal runaways and formulate remediation steps. Produce a structured operator inspection runbook containing fan curves and workload throttling mitigations.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Correctly identifies the exact primary throttle timestamp and initial trigger temperature. Flags secondary cascading device throttling events occurring within 120 seconds of the primary trigger. Produces actionable mitigation runbook with rack slot locations verified by human sign-off.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Web dashboard showing thermal excursion graphs and human operator sign-off panels.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Read-only simulated diagnostics. Does not adjust physical fan controllers or alter operational firmware settings.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Parse normalized DCGM time-series telemetry records including GPU temperatures, power draw, and throttle flags.

  • Reconstruct the chronological timeline of temperature breaches and clock frequency reductions across affected chassis slots.

  • Send chronological telemetry logs to hosted Claude to isolate thermal runaways and formulate remediation steps.

  • Produce a structured operator inspection runbook containing fan curves and workload throttling mitigations.

Resources

Dataset notes

Construct synthetic DCGM CSV files recording timestamps, device index, temperature, power draw, and throttling duration. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Challenge input

Input details are not configured.

MLflow

MLOps

Evaluated output

No output checks are configured.

Evaluation checks
  • Parse normalized DCGM time-series telemetry records including GPU temperatures, power draw, and throttle fl...
  • Correctly identifies the exact primary throttle timestamp and initial trigger temperature. Flags secondary...
  • Web dashboard showing thermal excursion graphs and human operator sign-off panels.
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 1 configured tool

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • MLflow · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Thermal Throttling Incident Timeline and Operator Rebalancing Engine