Groundcover

Groundcover is a Tel Aviv-based company operating in the cloud-native application monitoring market, positioning itself as a challenger to established players like Datadog and New Relic. Founded in 2021 by Shahar Azulay and Yechezkel Rabonivich, the firm aims to address the high costs and integration complexities of traditional Application Performance Monitoring (APM) solutions. The founders' backgrounds, which include experience at Apple and CyberMDX respectively, and service together in an elite Israeli cyber unit, provided them with firsthand experience of the frustrations caused by APM issues, directly informing the company's mission.

The company's core offering is an observability platform built to monitor modern production environments, particularly those using Kubernetes. Groundcover's key technical differentiator is its use of eBPF (extended Berkeley Packet Filter), a Linux kernel technology that allows for data collection with minimal overhead. This enables the platform to tap into application logs, metrics, and traces directly from the Linux kernel without requiring code changes or invasive instrumentation from its clients. This approach provides granular visibility into a company's entire production stack, helping to identify and resolve issues more rapidly.

Groundcover's business model centers on a "Bring Your Own Cloud" (BYOC) approach. This allows clients to maintain their observability data on their own on-premise infrastructure while the platform remains fully managed by Groundcover, addressing security and data privacy concerns. This model, combined with a pricing structure based on the number of nodes rather than data volume, is designed to offer a more predictable and cost-effective solution compared to legacy systems. The company has secured significant venture capital, including a $20 million Series A in 2022 and a $35 million Series B in April 2025, bringing its total funding to $60 million to support product development and U.S. expansion. Recently, the firm has expanded its offerings to include a dedicated observability tool for Large Language Models (LLMs) and AI-driven workflows.

Keywords: eBPF, observability, application performance monitoring, APM, Kubernetes monitoring, cloud-native, infrastructure monitoring, log management, distributed tracing, Bring Your Own Cloud, BYOC, Datadog alternative, New Relic alternative, cloud security, DevOps, site reliability engineering, SRE, LLM observability, AI workflows, kernel-level monitoring, zero-instrumentation