用带规则约束的AI代理自动管理云数据流水线，提升稳定性与效率。
Governing Cloud Data Pipelines with Agentic AI
- 引入受限AI代理实时分析流水线状态并提出调控建议
- 恢复时间缩短45%，运营成本降低25%，人工干预减少70%
- 适合需要合规与自动化运维的企业级数据平台
云数据流水线面临动态负载、模式变化、成本约束和严格治理要求。尽管云原生编排框架有所进步，多数生产环境仍依赖静态配置和被动运维，导致恢复时间长、资源浪费严重且人力成本高。本文提出面向企业级场景的智能云数据工程架构，将具备策略约束的AI代理集成至流水线的治理与控制平面。专用代理分析流水线遥测数据与元信息，基于声明式成本与合规策略进行推理，并提出受控操作，如自适应资源配置、模式对齐和故障自动恢复。所有代理行为均经策略验证，确保可预测且可审计。我们使用公开的企业级数据集构建典型批处理与流式分析工作负载进行评估。实验表明，该平台相比静态编排，平均恢复时间减少45%，运营成本降低约25%，人工干预事件下降超70%，同时保持数据新鲜度与策略合规性。结果证明，策略约束下的智能体控制是企业环境中治理云数据流水线的有效且可行方案。
原文摘要 · Abstract (English)
Cloud data pipelines increasingly operate under dynamic workloads, evolving schemas, cost constraints, and strict governance requirements. Despite advances in cloud-native orchestration frameworks, most production pipelines rely on static configurations and reactive operational practices, resulting in prolonged recovery times, inefficient resource utilization, and high manual overhead. This paper presents Agentic Cloud Data Engineering, a policy-aware control architecture that integrates bounded AI agents into the governance and control plane of cloud data pipelines. In Agentic Cloud Data Engineering platform, specialized agents analyze pipeline telemetry and metadata, reason over declarative cost and compliance policies, and propose constrained operational actions such as adaptive resource reconfiguration, schema reconciliation, and automated failure recovery. All agent actions are validated against governance policies to ensure predictable and auditable behavior. We evaluate Agentic Cloud Data Engineering platform using representative batch and streaming analytics workloads constructed from public enterprise-style datasets. Experimental results show that Agentic Cloud Data Engineering platform reduces mean pipeline recovery time by up to 45%, lowers operational cost by approximately 25%, and decreases manual intervention events by over 70% compared to static orchestration, while maintaining data freshness and policy compliance. These results demonstrate that policy-bounded agentic control provides an effective and practical approach for governing cloud data pipelines in enterprise environments.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。