The observability landscape for AI agents is rapidly evolving, raising important questions for enterprises about the right tools and strategies to use. Observability startup Groundcover recently raised $100 million in funding, signaling growing momentum in this competitive market. The firm highlights a shift in how telemetry data from AI systems is managed — advocating that this data should reside within the customer’s own cloud infrastructure rather than being processed by vendor-managed systems.
Traditional observability platforms, long dominated by incumbents like Datadog and Splunk, are challenged by the scale and complexity AI introduces. As autonomous AI agents generate increasing telemetry data, the old model of sampling or limiting data is no longer sufficient. Groundcover’s approach is to offer a bring-your-own-cloud (BYOC) model, where telemetry storage and processing happen inside AWS, Azure, or Google Cloud environments owned by the customer, avoiding data ingestion pricing and granting full control over telemetry.
Central to Groundcover’s technology is eBPF, which enables deep monitoring of system behavior without requiring manual application instrumentation. This, combined with BYOC and a host-based pricing model, aims to provide predictable costs and extensive observability coverage.
Groundcover also foresees observability platforms serving AI agents directly, using data to inform autonomous software development and operational decision-making. While the market remains crowded and competitive, the company positions itself as an innovator designing observability for an AI-driven future, betting on a fundamental architectural change rather than incremental AI feature additions.
Summary: Groundcover is reshaping the observability market by keeping AI telemetry within enterprises’ own cloud environments. Their BYOC model, paired with eBPF technology, addresses the growing telemetry demands of AI systems while offering cost predictability and full data control. As AI increasingly influences software operations, Groundcover’s approach signals a shift toward observability designed specifically for autonomous AI-driven workflows.
