Build a Cloud Accelerator Preemption and Job Rescheduling Replayer
Simulate spot preemption events and reconstruct KV-cache checkpointing costs for open-weight serving nodes. Formulate dynamic job migration and re-computation schedules to preserve inference SLAs.
What you are building
Simulate spot preemption events and reconstruct KV-cache checkpointing costs for open-weight serving nodes. Formulate dynamic job migration and re-computation schedules to preserve inference SLAs.
Distributed Systems Reliability Engineer
Ingest simulated spot preemption notification timestamps across heterogeneous cloud worker instances.
Calculate KV-cache serialization state and transfer overhead to designated backup workers.
Replay request backlog to estimate latency penalties under varying re-computation strategies.
Invoke hosted Claude via Anthropic API to draft a preemption resiliency runbook.
Interactive preemption chaos simulator UI with worker state diagrams and SLA recovery timelines.
Construct synthetic cluster state records modeling 10 spot GPU worker preemption events over a 24-hour cycle. Starter examples below are synthetic. They are not downloaded records.
vLLM open-model serving Reference vLLM distributed inference parallelism models and KV-cache state preservation concepts.
ray-serve, anthropic, pydantic. ray-serve models multi-worker replica failover topologies and request re-routing state. Hosted Claude API for runbook generation and risk synthesis; simulation targets open-model serving logic.
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.
Models the exact latency tradeoff between cold-restart re-prefill versus snapshot KV-cache loading.
Identifies cluster failover capacity deficits that risk dropping client queries.
Exports structured migration schedules that maintain service availability above 99 percent.
```json [ { "input": { "preempted_node": "worker-spot-08", "active_sessions": 24, "kv_cache_size_mb": 4200, "network_transfer_mbps": 1000, "target_node": "worker-spot-02", "target_node_available_ram_mb": 8000 }, "expected_output": { "migration_strategy": "transfer_cache_snapshot", "transfer_time_sec": 4.2, "sla_breach": false, "target_admissibility": "APPROVED" } }, { "input": { "preempted_node": "worker-spot-03", "active_sessions": 48, "kv_cache_size_mb": 12000, "network_transfer_mbps": 500, "target_node": "worker-spot-04", "target_node_available_ram_mb": 4000 }, "expected_output": { "migration_strategy": "evict_and_cold_recompute", "transfer_time_sec": null, "sla_breach": true, "target_admissibility": "REJECTED_INSUFFICIENT_MEMORY" } } ] ```
Simulates cluster fault tolerance and failover policies purely in software without terminating active cloud nodes. Use mock external writes. Require human review before any real deployment.
Rules
Simulates cluster fault tolerance and failover policies purely in software without terminating active cloud nodes. Use mock external writes and human review.
How work is evaluated
Models the exact latency tradeoff between cold-restart re-prefill versus snapshot KV-cache loading. Identifies cluster failover capacity deficits that risk dropping client queries. Exports structured migration schedules that maintain service availability above 99 percent.
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
Complete workflow
Ingest simulated spot preemption notification timestamps across heterogeneous cloud worker instances. Calculate KV-cache serialization state and transfer overhead to designated backup workers. Replay request backlog to estimate latency penalties under varying re-computation strategies. Invoke hosted Claude via Anthropic API to draft a preemption resiliency runbook.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Models the exact latency tradeoff between cold-restart re-prefill versus snapshot KV-cache loading. Identifies cluster failover capacity deficits that risk dropping client queries. Exports structured migration schedules that maintain service availability above 99 percent.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Interactive preemption chaos simulator UI with worker state diagrams and SLA recovery timelines.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Simulates cluster fault tolerance and failover policies purely in software without terminating active cloud nodes.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Ingest simulated spot preemption notification timestamps across heterogeneous cloud worker instances.
Calculate KV-cache serialization state and transfer overhead to designated backup workers.
Replay request backlog to estimate latency penalties under varying re-computation strategies.
Invoke hosted Claude via Anthropic API to draft a preemption resiliency runbook.
Resources
Construct synthetic cluster state records modeling 10 spot GPU worker preemption events over a 24-hour cycle. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Challenge input
Input details are not configured.
Ray Serve
Action Space in the agent workflow.
Evaluated output
No output checks are configured.
- Ingest simulated spot preemption notification timestamps across heterogeneous cloud worker instances. Calcu...
- Models the exact latency tradeoff between cold-restart re-prefill versus snapshot KV-cache loading. Identif...
- Interactive preemption chaos simulator UI with worker state diagrams and SLA recovery timelines.
- 2 public reference cases
- 1 configured tool
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- Ray Serve · 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.