groundcover, the BYOC-driven observability platform for modern architectures, today announced its presence at Google Cloud Next 2026, taking place April 22-24 at Mandalay Bay Convention Center in Las Vegas. Attendees can visit groundcover at Booth 5301 to experience its AI-native observability platform and the expansion of its Agent Mode to support Google Vertex AI, deepening its native AI capabilities for teams on Google Cloud Platform (GCP). At the event, groundcover will demonstrate how engineering teams can leverage Agent Mode to investigate production incidents, analyze infrastructure behavior, and accelerate root cause analysis, all while keeping telemetry data fully inside their own cloud environments.
groundcover showcases Agent Mode powered by Google Vertex AI at Google Cloud Next 2026 (April 22-24, Las Vegas).
Agent Mode enables AI-powered production incident investigation while keeping telemetry data inside customers' cloud environments.
gcQL (groundcover Query Language) enables precise queries across logs, traces, metrics, and events.
New enhancements include environment-aware prompt recommendations, trigger-based agentic background workflows, and Cursor integration for AI-assisted code remediation.
Native Vertex AI support allows GCP customers to run Agent Mode within their own Vertex AI infrastructure.
The platform uses eBPF-based telemetry collection for full-fidelity visibility without manual instrumentation.
Originally announced earlier this year, groundcover Agent Mode represents a new approach to observability, with AI built directly into the platform experience. Designed to run within customers' own cloud environments, Agent Mode enables teams to troubleshoot faster without exporting sensitive telemetry data, helping maintain security, compliance and cost control.
At the core of Agent Mode is gcQL (groundcover Query Language), a purpose-built query language that enables the agent to construct precise, complex queries across logs, traces, metrics and events. By pushing deterministic computation directly to the backend rather than relying on the LLM to interpret raw data, gcQL significantly improves the accuracy and reliability of AI-driven investigations which is a meaningful technical distinction from approaches that simply layer a chatbot on top of existing observability data. With its expansion to Google Vertex AI support, groundcover extends Agent Mode to run AI-powered observability workflows natively against existing Vertex AI infrastructure without routing data outside their environment.
Attendees visiting groundcover at Google Cloud Next 2026 can expect:
Live demonstrations of Agent Mode on GCP, showcasing real-time incident investigation and cross-service analysis.
A deep dive into eBPF-based telemetry collection, delivering full-fidelity visibility without manual instrumentation.
Practical guidance on reducing observability costs while increasing speed and depth of analysis.
Opportunities to meet with groundcover engineers and product leaders.
groundcover will also preview new enhancements to Agent Mode, including:
Intelligent, environment-aware prompt recommendations that surface the most relevant investigation starting points automatically based on live telemetry data from the customer's own environment.
Trigger-based agentic background workflows that continuously monitor environment signals and autonomously initiate investigations, alerts and remediation actions without requiring an engineer to prompt the agent manually.
Cursor integration for AI-assisted code remediation, enabling engineers to move directly from a production issue detected in groundcover to an automated pull request in their repository without switching tools or losing context.
Native Google Vertex AI support, enabling GCP customers to run Agent Mode's full investigative and agentic workflow capabilities directly within their own Vertex AI infrastructure.
Unlike standalone AI investigation tools that sit outside the observability stack and stitch together data from multiple sources, groundcover's Agent Mode operates from within the platform — with full access to correlated telemetry data, workload context and environment history. This architecture means the agent can surface richer, more accurate insights without the blind spots that come from fragmented data sources. By combining AI-driven insights with groundcover's in-cloud architecture, organizations gain faster incident resolution, reduced operational overhead, full control over data privacy and usage, and seamless integration with modern cloud-native stacks.
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.
