Groundcover review covering its eBPF observability engine, Kubernetes monitoring, node-based pricing tiers, key features, pros and cons, and top alternatives.
Category
DevOps
Pricing
Freemium, usage-based (per monitored Kubernetes node), from Free (Pro from $30 per host per month)
Verified
Not yet
Last updated
July 18, 2026
Founded
2021
Headquarters
Tel Aviv, Israel
Free PlanWeb AppAPIAIFreemiumSelf-Hosted
Overview
Groundcover is a cloud-native observability platform that uses eBPF sensor technology to automatically collect metrics, logs, and distributed traces from Kubernetes workloads without requiring any code changes or manual instrumentation.
Founded in 2021 and based in Tel Aviv, Israel, the company has raised roughly 60 million dollars in venture funding, including a 35 million dollar Series B round in April 2025, to expand its eBPF-based approach to observability into the US market.
Key Features
At the core of Groundcover is its adaptive eBPF sensor, which runs as a lightweight DaemonSet on every Kubernetes node and hooks into the Linux kernel to capture application and infrastructure telemetry the instant a workload runs, eliminating the need for SDKs or code-level instrumentation.
The platform correlates logs, metrics, traces, and Kubernetes events in a single interface, and includes root cause analysis workflows plus dedicated AI observability tooling for monitoring large language model and AI agent workloads alongside conventional application performance data.
Pricing
Groundcover breaks from the industry norm of ingestion-based pricing by charging based on the monthly average number of Kubernetes nodes monitored, regardless of the volume of telemetry those nodes generate.
Plans range from a free tier with 12-hour retention up through Pro at 30 dollars per host per month, Enterprise at 35 dollars per host per month, and a fully self-hosted On-Premise tier at 50 dollars per host per month for organizations with strict data-residency requirements.
Key Features
eBPF-based zero-instrumentation sensor — An adaptive eBPF sensor deployed as a Kubernetes DaemonSet automatically captures metrics, logs, traces, and protocol-level data straight from the Linux kernel, with no SDKs, agents inside application code, or redeploys required.
Bring Your Own Cloud (BYOC) architecture — The data plane and telemetry storage run inside the customer's own cloud account or cluster, so raw logs, metrics, and traces never leave the customer's environment.
Unified logs, metrics and traces — Groundcover correlates infrastructure, application, and Kubernetes event data into a single view so engineers can move from an alert to root cause without switching tools.
AI observability — Purpose-built monitoring for LLM and AI agent workloads tracks prompts, latency, token usage, and failures alongside traditional application and infrastructure telemetry.
Root cause analysis workflows — Automated correlation and guided investigation workflows help engineers pinpoint the offending pod, container, or code path behind an incident faster.
OpenTelemetry support — Native support for OpenTelemetry lets teams combine existing manual instrumentation with the eBPF-collected data in a single pipeline.
Node-based, predictable pricing — Billing is based on the number of monitored Kubernetes nodes rather than data ingestion volume, so cost does not spike as logging or tracing volume grows.
Enterprise access controls — SSO, role-based access control, and, on the On-Premise tier, isolated authentication and a self-hosted UI support security and compliance requirements.
Pros & Cons
Pros
Zero-instrumentation eBPF collection removes the engineering burden of manually adding SDKs or agents to every service.
Node-based pricing is decoupled from data volume, making costs predictable even as logging and tracing grow.
BYOC architecture keeps raw telemetry inside the customer's own cloud account, which appeals to security-conscious teams.
Unified view of logs, metrics, traces, and Kubernetes events reduces tool-switching during incident response.
Dedicated AI observability features address monitoring needs for LLM and agent-based workloads.
Cons
The eBPF-based, Kubernetes-native design means Groundcover is a poor fit for teams running mostly non-containerized infrastructure.
Node-based pricing can be less predictable for clusters that autoscale heavily, since cost tracks node count rather than a flat subscription.
The free tier's 12-hour data retention window is short for teams that need to investigate incidents days after they occur.
As a newer entrant founded in 2021, Groundcover has a smaller ecosystem of integrations and community content than established players like Datadog.
Enterprise and On-Premise pricing requires per-host negotiation, which can complicate budgeting for large, variable-size fleets.
Pricing
Free $0 Monthly
Pro $30 per host Monthly
Enterprise $35 per host Monthly
On Premise $50 per host Monthly
Frequently Asked Questions
What is Groundcover used for?
Groundcover is used by DevOps, platform engineering, and SRE teams to monitor Kubernetes-based applications and infrastructure, collecting logs, metrics, and traces automatically via an eBPF sensor without requiring manual code instrumentation.
Does Groundcover require code changes to install?
No. Groundcover's eBPF sensor deploys as a Kubernetes DaemonSet and captures telemetry directly from the Linux kernel, so no SDKs, agents, or code-level instrumentation need to be added to application services.
How does Groundcover pricing work?
Groundcover charges based on the monthly average number of Kubernetes nodes actively monitored by its sensor, rather than the volume of logs, metrics, or traces ingested, with plans ranging from a free tier to Pro, Enterprise, and On-Premise tiers priced per host per month.
What does BYOC mean for Groundcover customers?
BYOC, or Bring Your Own Cloud, means Groundcover's data plane and telemetry storage run inside the customer's own cloud account or cluster, so raw observability data never has to leave the customer's environment.
Can Groundcover monitor AI and LLM workloads?
Yes. Groundcover includes AI observability features that track prompts, latency, token usage, and failures for large language model and AI agent workloads alongside standard application and infrastructure telemetry.
Who are Groundcover's main competitors?
Groundcover competes primarily with Datadog, New Relic, and Grafana Cloud, positioning its eBPF-based zero-instrumentation approach and node-based pricing as an alternative to their agent-based, ingestion-priced observability models.