Datadog

Observability as sensory nervous system: Datadog's $3.3 billion 2025 revenue (28% year-over-year growth) comes from selling enterprises their own proprietary nervous system. The platform monitors infrastructure, applications, logs, security events, and now AI model performance—aggregating signals from 47,431 customers into unified dashboards that detect anomalies before humans notice symptoms. This mirrors the evolution from simple stimulus-response to centralized neural processing.

At 51.82% data center management market share and 20% IT operations management share, Datadog demonstrates network effects in monitoring: the more systems feeding data into the platform, the better its anomaly detection algorithms perform. Like distributed sensory organs converging signals into coordinated responses, Datadog's AI identifies threats by correlating patterns across infrastructure. The company's fifth consecutive year as Gartner Magic Quadrant Leader reflects this: superior infrastructure visualization creates lock-in through cognitive dependency.

The biological parallel is centralized versus distributed sensing: organisms evolved from scattered receptors (point monitoring tools) to integrated nervous systems (unified observability platforms) because central processing enables faster, more coordinated responses. Datadog's LLM observability—tracking AI model performance, token usage, and output quality—represents the latest sensory adaptation: enterprises can't manage what they can't measure, and AI opacity demands new instrumentation.

But sensory monopolies face succession pressure. New Relic, Dynatrace, and Splunk offer competing nervous systems, while cloud providers bundle native monitoring. Datadog's 11% AI-native revenue growth shows platform expansion, yet the $79 billion TAM attracts convergent evolution. The lesson: selling infrastructure visibility creates sticky revenue (monitoring is metabolically essential), but every nervous system eventually faces competing architectures as ecosystems mature.