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groundcover Expands AI Observability to Google Cloud for Agentic Workflows


groundcover Expands AI Observability to Google Cloud for Agentic Workflows
  • by: Business Wire
  • |
  • April 23, 2026

groundcover announced a major expansion of its AI Observability capability, adding native support for agentic AI systems fully compatible with Google Vertex AI. The update is automatically available to all groundcover customers at no additional cost and allows users to trace every LLM interaction. With this release, engineering and platform teams can add observability to production environments at the speed with which language model services are incorporated into modern applications.

Quick Intel

  • Agent trace visibility for every model call, tool invocation, and reasoning path.

  • Accurate cost attribution including prompt caching for regular, cache creation, and cache read tokens.

  • Native Google Vertex AI support with zero instrumentation required.

  • Powered by patented eBPF sensor with all data remaining inside customer's cloud.

  • Configurable focus levels from provider-level aggregates to individual span detail.

  • Automatically deployed to all customers at no additional cost.

The Visibility Gap in AI-Powered Systems

As organizations rapidly integrate LLMs into production systems, they are encountering a new kind of visibility gap. Traditional observability tools were designed for deterministic software, not systems where dynamic prompts drive outputs. As a result, teams often struggle to understand how AI-powered features behave in real-world environments, including what inputs are driving outcomes, how responses vary, and how usage impacts cost. This lack of visibility makes it difficult to ensure reliability, optimize performance, and confidently scale AI-driven applications. Addressing this challenge requires a fundamentally different approach to observability, one that captures the full context of LLM interactions and traces how outputs are generated across increasingly complex, multi-step systems.

What's New in groundcover AI Observability

Since launching LLM Observability in August 2025, groundcover has been running in production AI environments across its customer base, capturing LLM interactions automatically via its patented eBPF sensor with no instrumentation required and all data remaining inside the customer's cloud. This release extends that foundation to address what production deployments revealed as the next unsolved problem: visibility into multi-step agentic systems.

  • Agent trace visibility: groundcover now surfaces complete agent execution traces — every model call, every tool invocation with its arguments and results, and the reasoning path connecting them. Configurable focus levels let engineers work at the right altitude, from provider-level aggregates down to individual span detail.

  • Accurate cost attribution including prompt caching: Token costs are tracked at the span level and account for most edge cases of pricing complexity of modern LLM APIs, correctly distinguishing between regular input tokens, cache creation tokens, and cache read tokens. Teams can see what individual agent runs and sessions actually cost.

  • Google Vertex AI support: groundcover's automatic capture now extends to teams building on Google Cloud's managed AI infrastructure, with all observability data remaining inside the customer's own environment, and zero instrumentation.

Conclusion

As Orr Benjamin, VP of Product at groundcover, stated: "Our customers made it clear that their LLM calls have been invisible to the teams that manage the observability of their production systems. They've been searching for a way to systematically understand their LLM calls by prompts, responses, and cost. They deployed groundcover for its traditional observability features, and we built AI Observability as a direct response to their demands for scale and mission-critical workload monitoring."

Guilhem Tesseyre, CTO and co-founder of Zencore, added: "We have years of experience helping customers with meaningful transformations and modernizations on Google Cloud, and this release from groundcover is particularly exciting. Customers can start with the AI Observability data automatically gathered by the groundcover eBPF sensor, and the OTel native aspect of the platform means any strategic changes they need to their observability is simple to design."

AI Observability is now generally available and automatically deployed to all customers. With this release, groundcover is also now fully compatible with Google Vertex on Google Cloud.

About groundcover

groundcover is a cloud native observability platform powered by eBPF. It runs inside the customer's cloud and provides complete visibility into applications, infrastructure, networks and AI systems without operational overhead. The platform offers unlimited data coverage at a fraction of the cost of legacy observability tools.

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