Build a Datacenter Rack Airflow Deficit and Workload Evacuation Planner
Analyze multi-chassis intake and exhaust thermal sensor telemetry across server racks. Formulate proactive workload evacuation and fan throttling mitigation plans with hosted Claude.
What you are building
The core problem, expected build, and operating context for this challenge.
Analyze multi-chassis intake and exhaust thermal sensor telemetry across server racks. Formulate proactive workload evacuation and fan throttling mitigation plans with hosted Claude.
Facility Systems and Infrastructure Engineer
Ingest rack-level inlet temperature and server exhaust temperature metrics from DCGM telemetry.
Identify thermal recirculations and localized hot-aisle air dams exceeding design limits.
Use hosted Claude API to formulate an emergency workload redistribution and job migration runbook.
Produce an evacuation schedule JSON prioritizing jobs by checkpoint maturity and node heat.
Thermal heat-map web view displaying rack chassis elevations with evacuation triggers.
Synthetic rack environmental sensor records and node temperatures in standard Prometheus format. Starter examples below are synthetic. They are not downloaded records.
NVIDIA DCGM exporter Leverages DCGM exporter temperature gauges and chassis thermal sensors to assess rack heat.
pydantic-ai, anthropic-claude. Enforces strict schemas for environmental telemetry feeds and evacuation runbooks. Hosted Claude API for technical thermal runbook synthesis; no local execution.
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.
Calculates delta-T between inlet and exhaust across rack U-positions accurately.
Triggers workload evacuation when inlet temperature exceeds ASHRAE envelope limits.
Prioritizes evacuation of high-wattage training jobs before low-wattage inference workloads.
Generates safe execution runbook without modifying physical BMS cooling setpoints.
```json [ { "input": { "rack_id": "RACK-E04", "inlet_ambient_c": 28.5, "servers": [ { "u_slot": "U18-U22", "node_id": "node-18", "inlet_c": 34, "exhaust_c": 68, "active_job": "open-deepseek-train", "power_kw": 9.8 }, { "u_slot": "U24-U28", "node_id": "node-24", "inlet_c": 36.5, "exhaust_c": 72, "active_job": "open-llama-inf", "power_kw": 4.2 } ] }, "expected_output": { "containment_breach": true, "hot_spot_u_slot": "U24-U28", "evacuation_priority_order": [ { "node_id": "node-18", "action": "CHECKPOINT_AND_DRAIN", "reason": "High 9.8kW power contribution to local hot dam" }, { "node_id": "node-24", "action": "MIGRATE_REPLICAS", "reason": "Critically elevated inlet temperature (36.5C)" } ], "estimated_power_reduction_kw": 14, "technician_notice": "Inspect top-of-rack blanking panels and rear heat exchanger flow." } }, { "input": { "rack_id": "RACK-A01", "inlet_ambient_c": 21, "servers": [ { "u_slot": "U10-U14", "node_id": "node-10", "inlet_c": 22, "exhaust_c": 45, "active_job": "open-batch-eval", "power_kw": 5 } ] }, "expected_output": { "containment_breach": false, "hot_spot_u_slot": null, "evacuation_priority_order": [], "estimated_power_reduction_kw": 0, "technician_notice": "Rack operates within normal thermal margins." } } ] ```
Thermal plans are advisory only. Does not actuate datacenter cooling plant or cut server power. Use mock external writes. Require human review before any real deployment.
Participation guide
Thermal plans are advisory only. Does not actuate datacenter cooling plant or cut server power. Use mock external writes and human review.
How work is evaluated
Calculates delta-T between inlet and exhaust across rack U-positions accurately. Triggers workload evacuation when inlet temperature exceeds ASHRAE envelope limits. Prioritizes evacuation of high-wattage training jobs before low-wattage inference workloads. Generates safe execution runbook without modifying physical BMS cooling setpoints.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Ingest rack-level inlet temperature and server exhaust temperature metrics from DCGM telemetry. Identify thermal recirculations and localized hot-aisle air dams exceeding design limits. Use hosted Claude API to formulate an emergency workload redistribution and job migration runbook. Produce an evacuation schedule JSON prioritizing jobs by checkpoint maturity and node heat.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Calculates delta-T between inlet and exhaust across rack U-positions accurately. Triggers workload evacuation when inlet temperature exceeds ASHRAE envelope limits. Prioritizes evacuation of high-wattage training jobs before low-wattage inference workloads. Generates safe execution runbook without modifying physical BMS cooling setpoints.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Thermal heat-map web view displaying rack chassis elevations with evacuation triggers.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Thermal plans are advisory only. Does not actuate datacenter cooling plant or cut server power.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Ingest rack-level inlet temperature and server exhaust temperature metrics from DCGM telemetry.
Identify thermal recirculations and localized hot-aisle air dams exceeding design limits.
Use hosted Claude API to formulate an emergency workload redistribution and job migration runbook.
Produce an evacuation schedule JSON prioritizing jobs by checkpoint maturity and node heat.
Reference links and supporting material
Synthetic rack environmental sensor records and node temperatures in standard Prometheus format. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Pydantic AI
Typed Python agent framework.
Evaluated output
No output checks are configured.
- Ingest rack-level inlet temperature and server exhaust temperature metrics from DCGM telemetry. Identify th...
- Calculates delta-T between inlet and exhaust across rack U-positions accurately. Triggers workload evacuati...
- Thermal heat-map web view displaying rack chassis elevations with evacuation triggers.
- 2 public reference cases
- 2 configured tools
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- Pydantic AI · Optional
- Pydantic AI · 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.