Coroot

Coroot is a self-hosted observability platform that brings application and infrastructure signals together for teams operating distributed services. Its breadth—from service maps and tracing to risk detection and incident analysis—makes it a strong fit for operators who need more than metrics alone. The key trade-offs are the Linux kernel floor for eBPF-based collection and Standard’s per-monitored-core pricing.

Overview

Founded in 2021, Coroot collects metrics, logs, traces and profiling data without requiring code changes. It combines that telemetry with service mapping, cloud-cost insights and infrastructure risk detection, aiming to help teams understand both what is happening and where likely causes lie.

Coroot is self-hosted, so data remains within the customer’s infrastructure. Its Community Edition is open source under Apache 2.0 and can run on premises or in a customer’s cloud. That control is valuable for teams with data-residency needs, but the self-hosted model makes the deployment environment a deciding factor.

Key features

Service maps and tracing

Automatic service and dependency maps are advertised with 100% coverage, giving operators a way to see relationships without assembling them manually. Distributed tracing pairs eBPF auto-instrumentation with OpenTelemetry SDK traces, so teams can combine automatic request tracking with traces their applications already emit.

Profiling and incident analysis

Continuous profiling can pinpoint CPU spikes down to a line of code, making it useful when aggregate metrics show a slowdown but not its source. Coroot’s AI root cause analysis correlates metrics, logs, traces, events and profiles to identify likely incident causes, with evidence and suggested fixes. This broad correlation is useful during investigations, though the output is framed as likely causes rather than a guaranteed diagnosis.

Cost, risk and alerts

Cloud-cost tracking works without cloud-account access and supports AWS, GCP, Azure and other cloud or on-premises environments. Risk detection flags conditions such as single-instance applications, unreplicated databases, poor replica placement and publicly exposed services. Notifications can go to Slack, Microsoft Teams, PagerDuty, Opsgenie or webhooks, helping teams route findings into existing alert channels.

Container metrics, resource alerts, image monitoring, runtime events and container log collection are supported. Deployment targets include Kubernetes, OpenShift, Docker, Docker Swarm, Ubuntu, Debian, RHEL, CentOS and Windows agents.

Pricing

Coroot uses a freemium model with a free plan, paid monitoring from $1 per monitored CPU core/month, and a 14-day trial.

Community Edition suits teams that want the core platform without a monitoring bill and can operate a self-hosted deployment. Standard adds paid monitoring and business-hours support; its per-core basis makes monitored infrastructure size directly relevant to cost, while the absence of ingestion fees avoids a separate ingestion charge. Premium is aimed at organizations that need round-the-clock assistance, phone support or air-gapped installation help.

Platforms

Coroot supports self-managed Kubernetes and managed orchestrators including EKS, GKE, AKS and OKE, as well as OpenShift, K3s, MicroK8s and Docker Swarm. It also supports Docker and Linux distributions including Ubuntu, Debian, RHEL and CentOS, with Windows agents. Linux systems need kernel version 5.1 or newer because Coroot relies heavily on eBPF; older kernels are outside its stated requirements.

Who it's for

Coroot is best suited to engineering and operations teams running containerized or distributed services that want a single, self-hosted view of service relationships, performance, costs and operational risks. Its open-source Community Edition can appeal to teams prioritizing source transparency and infrastructure control. It is less suitable for environments whose Linux systems cannot meet the kernel requirement or teams that do not want to manage a self-hosted platform.

Pros and cons

• Pros: Metrics, logs, traces and profiling in one platform, with eBPF collection that does not require code changes.
• Pros: Service maps, risk detection and cross-signal incident analysis extend visibility beyond raw telemetry.
• Pros: Apache 2.0 Community Edition and self-hosting keep deployment and data within the customer’s infrastructure.
• Cons: Linux kernel 5.1 or newer is required for the eBPF-based approach.
• Cons: Standard pricing scales by monitored CPU core, so teams need to account for the size of the monitored estate.
• Cons: Self-hosting is a poor fit for teams seeking a platform that runs outside their own infrastructure.

Alternatives

For a narrower profiling focus, Continuous Profiling Tools is a useful category to explore; eBPF Observability Tools helps compare tools centered on eBPF, while Kubernetes Monitoring and Container Monitoring focus the search on those environments.

Choose Guance Container Monitoring if a free plan capped at 10 hosts, 10,000 metric series per day, 10 million log records per day and seven-day rolling retention fits your container-monitoring needs. Middleware is another freemium option, with its free tier offering up to 100GB of data, 1,000 RUM sessions and 20,000 synthetic checks.

Grafana Cloud Application Observability is worth considering if you want a free cloud plan with 2,232 host hours rather than Coroot’s self-hosted Community Edition. For a free benchmark tool rather than a full observability platform, consider LMbench.

Metoro Kubernetes Profiling may suit a profiling-focused Kubernetes setup: its free Hobby plan covers one cluster, one user, two nodes and 28-day retention. OneUptime is an open-source, Apache 2.0 platform that can also be self-hosted. For an open-source profiling option, Parca is available under Apache 2. For hosted profiling with a free tier, Pyroscope offers 50 GB ingested per month and 14-day retention on its free plan.

Verdict

Choose Coroot if you run distributed or containerized services and want self-hosted observability that connects telemetry with service maps, profiling, cost insights, risk detection and incident analysis. Its strongest case is the breadth of operational context in an Apache 2.0 Community Edition; look elsewhere if your Linux kernels are older than 5.1, you do not want to self-host, or per-core billing is a poor fit.