text stringlengths 0 101 |
|---|
- counterfactual: Agent vs optimal action delta per step |
endpoints: |
reset: |
method: POST |
path: /reset |
params: |
difficulty: query[easy|medium|hard] |
step: |
method: POST |
path: /step |
params: |
difficulty: query[easy|medium|hard] |
body: Action |
state: |
method: GET |
path: /state |
params: |
difficulty: query[easy|medium|hard] |
health: |
method: GET |
path: /health |
tasks: |
method: GET |
path: /tasks |
deployment: |
platform: huggingface-spaces |
runtime: docker |
port: 7860 |
health_check: /health |
name: autonomous-enterprise-chaosops-arena |
version: "1.0.0" |
description: > |
AI training environment simulating an enterprise DevOps + Incident Response |
engineer operating under dynamic, chaotic conditions. Agents must triage |
incidents, diagnose failures, and stabilize production systems under pressure. |
author: ACEA Team |
license: MIT |
environment: |
class: ACEAEnvironment |
module: env.environment |
api_version: "openenv-1.0" |
api: |
reset: |
description: Reset environment to initial state for given difficulty |
returns: Observation |
step: |
description: Execute one action step |
input: Action |
returns: |
observation: Observation |
reward: float |
done: bool |
info: dict |
state: |
description: Return full internal environment state |
returns: dict |
observation_space: |
type: structured |
schema: env.models.Observation |
fields: |
alerts: |
type: list[Alert] |
description: Active system alerts with severity and service attribution |
logs: |
type: list[LogEntry] |
description: Recent system logs (AWS/Kubernetes style) |
tickets: |
type: list[Ticket] |
description: Customer support tickets including escalations |
system_health: |
type: SystemHealth |
description: Real-time system metrics (CPU, memory, latency, uptime, error_rate) |
active_incidents: |
type: list[Incident] |
description: Currently active incidents requiring resolution |
risk_level: |
type: enum[low, medium, high, critical] |
description: Overall system risk classification |
time_elapsed: |
type: int |
description: Seconds elapsed since episode start |
chaos_events: |
type: list[ChaosEvent] |
description: Chaos events injected this step |
step_count: |
type: int |
description: Current step index |
action_space: |
type: structured |
schema: env.models.Action |
fields: |
type: |
type: enum |
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