AI RESEARCH
SREGym: A Live Benchmark for AI SRE Agents with High-Fidelity Failure Scenarios
arXiv CS.AI
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ArXi:2605.07161v1 Announce Type: new AI agents are increasingly used to diagnose and mitigate failures in production systems, known as agentic Site Reliability Engineering (SRE). Current SRE benchmarks are limited to oversimplistic SRE tasks and are unfortunately hard to extend due to bespoke designs. We present SREGym, a high-fidelity benchmark for SRE agents. SREGym exposes a live system environment built atop real-world cloud-native system stacks, where high-fidelity failure scenarios are simulated through fault injectors.