OBSERVABILITY FOR INTELLIGENT INFRASTRUCTURE
Your infrastructure evolved.
Your observability platform didn't.
Infrastructure observability has a problem: your network changed, your tools didn't. Parlon is the modern replacement, built from the ground up for hybrid, containerized, and AI-driven environments.
~70%
Reduction in alert noise with Alert Auto-Tune™
< 4 hrs
Time to first value — synthetics live same day
90 days
Typical time to fully decommission legacy stack
3–8×
Lower 3-year TCO vs. legacy monitoring platforms
THE PROBLEM
Legacy platforms were built for a world that no longer exists.
Legacy monitoring platforms were designed for static, pre-cloud infrastructure. Your network is now hybrid, containerized, and AI-driven. Their tools weren't — and their new owners aren't moving fast enough to change that.
+200-300%
Renewal Shock
PE acquisitions and corporate consolidation have changed the economics of legacy monitoring. Forced subscription conversions, mandatory bundle tiers, and enterprise contracts running $1M+/yr in license alone — before professional services or hardware.
2-5 FTE
Ops Overhead That Doesn't Scale
Administering legacy platforms requires 2–5 dedicated full-time engineers — people who should be building, not babysitting tooling.
Blind Spots
AI Workloads Are Invisible
Legacy platforms have no visibility into LLM workflows, AI inference latency, or model drift. They were never designed to observe what you're building today.
THE PLATFORM
Built different. From the data model up.
Parlon normalizes telemetry at ingestion — not after the fact. That structural choice makes everything else faster, cheaper, and more reliable.
Normalization as a Core Primitive
Every metric, event, and path is mapped into a consistent schema at ingest. No custom parsers. No brittle correlation scripts. Clean data from day one — across all vendors, environments, and AI workloads.
Active, Behavior-First Observability
Parlon doesn't wait for things to break. LLM-aware synthetic tests continuously validate real paths, AI workflows, and critical endpoints — surfacing latency and drift before users feel it.
Alert Auto-Tune™
Learning-based alerting that earns trust. Alert Auto-Tune analyzes historical behavior, suppresses low-value noise, and correlates alerts into a single escalating stream. When Parlon alerts, it's worth acting on.
Low Switching Friction by Design
SaaS-first, no hardware, open APIs, streaming export. Deploy alongside your existing stack on day one. Run a 30-day proof of value. Decommission the incumbent in 90 days. Parlon is an exit ramp, not a rip-and-replace.
WHY TEAMS SWITCH
Not just cheaper. Fundamentally better.
Legacy platforms collect data. Parlon makes sense of it — and costs a fraction of the alternatives.
HOW IT WORKS
From raw telemetry to actionable foresight.
Data is normalized at ingestion — not correlated after the fact. Five stages, one unified platform.
Collect
Infrastructure, applications, AI/LLM workflows — all sources, all environments.
Synthetic + Telemetry
Normalize
Every metric maps to a unified schema at ingestion. No silos, no custom parsers.
Normalization Engine
Analyze
Anomaly detection, behavioral baselining, and predictive signals surface what matters.
Intelligence Engine
Visualize
Dashboards and Alert Auto-Tune™ deliver signal over noise to the right teams.
Alert Auto-Tune™
Export
Streaming export to SIEMs, compliance tools, and analytics platforms via open APIs.
Flexible by design
CUSTOMER RESULTS
Real outcomes. No hardware. No sprawl.
Early customers replaced legacy stacks and saw results within weeks, not months.