Observability

llm.port 帮助你快速看清 AI 系统每天的运行状态。

你可以直接回答这些问题：

• 请求是否稳定、是否够快？
• 哪些模型使用最多？
• 成本主要增长在哪里？
• 谁在什么时间做了什么变更？

What you can observe

• Request activity and outcome trends
• Latency and throughput indicators
• System health and service behavior
• Administrative action trails

Why this matters

• Faster incident detection and troubleshooting
• Better governance and compliance reporting
• Data for capacity planning and optimization

对多数团队来说，这会成为 AI 运维的统一事实来源。

Recommended operating practice

• Define alert thresholds for key service indicators
• Review usage and access trends regularly
• Keep retention policies aligned with compliance requirements

在 Requests 视图中，通常可以最快定位用户反馈的问题。

Public docs focus on observable outcomes and operating guidance, not internal telemetry plumbing.

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