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.
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.
“Our customers made it clear that their LLM calls have been invisible to the teams that manage the observability of their production systems,” said Orr Benjamin, VP of Product at groundcover. “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.”
What’s new:
- 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.
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.
The Latest
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...