Mar 24
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Modern enterprise infrastructure has outpaced traditional monitoring. Organizations now operate across on-premise networks, multi-cloud environments, containerized workloads, and AI and agentic systems — environments that legacy tools like SolarWinds, ScienceLogic, and SevOne were never designed to observe. Parlon is an infrastructure observability platform built for this complexity. It unifies telemetry across the full stack — networks, applications, cloud, and AI workflows — through a real-time Normalization Engine that tags and contextualizes every metric, event, and synthetic result at ingestion. The result is clean, structured, AI-ready data from the moment it enters the platform. Parlon's synthetic monitoring goes beyond endpoint checks. From ICMP to web testing and MCP-based validation of AI and LLM-driven applications, Parlon continuously validates full end-to-end path performance — detecting latency, drift, and failure before users or revenue are impacted. Unlike reactive monitoring tools, Parlon shifts operations from firefighting to foresight — giving SRE, platform engineering, and infrastructure teams a single, trusted view of how their systems actually behave. Key capabilities: — Real-time telemetry normalization across heterogeneous environments — Synthetic monitoring including ICMP, web, and MCP testing for AI applications — Alert Auto-Tune: learning-based alerting that reduces noise by approximately 70% — Built for hybrid, multi-cloud, and LLM-aware infrastructure from day one — Open APIs and streaming export for tool consolidation without lock-in Parlon is designed for VP Infrastructure, SRE leads, and platform engineering teams managing complex, distributed environments where downtime costs exceed $1M per hour for 41% of enterprises. See everything. Miss nothing.