Driving continuous progress in observability technology!
This article explains how Alibaba Cloud's AgentLoop platform continuously audits Dify AI applications by tracing model and tool calls, detecting sensitive data exposure, indirect prompt injection, and privilege misuse, and enabling custom rules to pinpoint root causes in workflow nodes for effective remediation.
Alibaba Cloud details its open-source stack for AgenticOps — LoongSuite/OBI for standardized OpenTelemetry collection, UModel for semantic fault context, and BRiSE for reproducible benchmarking — enabling reliable production-grade AI operations.
At the 2026 Yunqi Conference, Alibaba Cloud's Log Service (SLS) introduced agent-native capabilities including SessionStore for organizing agent run data, a semantic layer for business context, MCP Server for secure standard-protocol access, an orchestration Skills system, and DataAgent for natural-language business analytics, all built on its real-time data foundation.
This article explains how LoongSuite-Pilot collects and structures coding agent execution records into unified event timelines, and how AgentLoop analyzes these records against task context to detect risks like prompt injection and unauthorized file deletions, enabling investigators to trace risky operations back to specific model-tool interactions.
Alibaba Cloud Monitor MCP exposes nearly 200 tools via Model Context Protocol, letting AI agents query alerts, metrics, traces, and dashboards directly from a remote endpoint — eliminating local CLI setup and cutting a real-world checkout latency investigation from hours to 20 minutes.
Lemon, a food retail SaaS provider serving 20,000+ stores, unified logs, metrics, and traces into a full-chain digital twin using Alibaba Cloud CloudMonitor 2.0 and STAROps, deploying four intelligent operations layers that cut alert noise by 70% and reduced incident response and MTTR to minutes.
The article demonstrates how STAROps' full-stack correlation combined with Yaochi Agent's deep database diagnosis enables cross-layer root cause analysis across three real incidents: an RDS missing index, a Redis Lua script blocking the single thread, and an EVAL command causing CPU saturation, showing command-level diagnostic precision.
The article explains how Alibaba Cloud's CMS 2.0 uses Session Replay to record DOM changes and user interactions, and three types of heatmaps—click, area, and scroll—to provide low‑overhead, privacy‑controlled insights that help developers reproduce bugs, analyze conversion funnels, and improve overall front‑end user experience.
OBI uses Linux kernel eBPF instrumentation to automatically capture and parse all AI‑related HTTP traffic—covering LLM, embedding, vector search, rerank and MCP tool calls—producing OpenTelemetry‑compatible traces and metrics without any code changes, enabling full‑stack observability of multi‑provider AI agents across languages with only ~1% CPU overhead.
The article analyzes how modern Node.js services act as a convergence layer for HTTP, databases, caches, RPCs, and AI calls, making performance problems cross‑layer, and introduces Alibaba Cloud ARMS Node.js probe that, with a single integration, automatically gathers APM, AI observability, runtime health, and dynamic configuration to provide full‑stack tracing and simplify troubleshooting.
