Co-Developing an AI Native Observability Platform
Summary
The article examines Selector AI’s AI-native observability and AIOps platform and argues that it fits the rising complexity of hybrid and distributed enterprise environments. It highlights the platform’s data-centric design, which unifies telemetry from metrics, logs, configs, alerts, and topology into one analytics layer. It also emphasizes the Network Language Model and agent workflows that translate natural language into operational actions and automated responses. The piece positions co-development and per-customer platform instances as a way to speed deployment, reduce alert fatigue, and tailor analytics to each customer’s needs. It concludes that organizations should adopt such platforms in phases and measure results against operational and cost goals.
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