Coroot - eBPF Observability with AI Root Cause Analysis

TL;DR

TL;DR: Coroot is an open-source observability platform that uses eBPF to automatically collect metrics, logs, traces, and profiles without code changes, featuring AI-powered root cause analysis that reduces mean time to resolution by 80%.

Source and Accuracy Notes

• Project page: coroot.com
• Source repository: github.com/coroot/coroot
• License: Apache-2.0 (verified via GitHub API license.spdx_id)
• GitHub stars: 7,757 (verified via GitHub API, 2026-06-17)
• HN launch thread: news.ycombinator.com/item?id=44725306
• Source last checked: 2026-06-17 (commit pushed 2026-06-15)

What Is Coroot?

Coroot is an open-source observability and Application Performance Monitoring (APM) tool that combines metrics, logs, traces, continuous profiling, and SLO-based alerting into a single platform. Unlike traditional observability tools that require extensive instrumentation, Coroot leverages eBPF (Extended Berkeley Packet Filter) technology to automatically capture telemetry data from your applications without requiring any code changes.

The platform is designed to solve a fundamental problem in modern observability: collecting data is easy, but turning that data into actionable insights is hard. Coroot addresses this with built-in expertise that automatically identifies over 80% of issues and provides AI-powered root cause analysis.

Key Features

Zero-Instrumentation Observability

Coroot uses eBPF to automatically gather:

• Metrics
• Logs
• Traces
• Continuous profiling data

This approach provides 100% system coverage with no blind spots, eliminating the need for manual instrumentation or SDK integration.

AI-Powered Root Cause Analysis

The platform’s AI engine analyzes telemetry data across all dimensions (metrics, logs, traces) to identify the root cause of issues. When an application fails to meet its Service Level Objectives (SLOs), Coroot sends a single alert that includes the results of all relevant inspections, reducing the noise from traditional alerting systems.

Service Map and Health Summary

Coroot automatically generates a service map that visualizes dependencies between your applications. The Application Health Summary dashboard provides:

• Status overview of all services
• SLO tracking
• Log pattern analysis without manual inspection
• One-click access to outlier requests

Distributed Tracing

The platform supports vendor-neutral instrumentation via OpenTelemetry and can capture requests from legacy or third-party services using eBPF-based instrumentation. This allows you to investigate anomalies with a single click, even in services you cannot modify.

Continuous Profiling

Profile any application to analyze unexpected spikes in CPU or memory usage down to the specific line of code. Coroot compares anomalies against the system’s baseline behavior, making it easy to investigate performance regressions.

Deployment Tracking and Cost Monitoring

Coroot automatically discovers and monitors every application rollout in your Kubernetes cluster without requiring CI/CD pipeline integration. Each release is compared with the previous one to detect performance degradation. The integrated Cost Monitoring feature tracks how each change affects your cloud bill across AWS, GCP, and Azure.

Setup Workflow

Step 1: Installation

Coroot can run as a Docker container or be deployed to any Kubernetes cluster. The recommended approach for most users is Docker Compose:

# Clone the repository
git clone https://github.com/coroot/coroot.git
cd coroot

# Start Coroot with Docker Compose
docker-compose up -d

For Kubernetes deployments, Coroot provides Helm charts. Check the Installation guide for detailed instructions.

Step 2: Access the Dashboard

Once deployed, access the Coroot dashboard at http://localhost:8080 (default port). The platform will automatically discover your applications and start collecting telemetry data.

Step 3: Configure Data Sources

Coroot integrates with existing monitoring infrastructure:

• Prometheus for metrics
• OpenTelemetry Collector for traces
• ClickHouse for log storage

The platform provides predefined dashboards and inspections that work out of the box without configuration.

Step 4: Set Up SLOs

Define Service Level Objectives for your critical services. Coroot will automatically track compliance and send alerts when SLOs are at risk.

Deeper Analysis

eBPF vs Traditional Instrumentation

Traditional observability tools require you to instrument your code with SDKs or agents. This approach has several limitations:

• Requires code changes for every service
• Cannot instrument third-party or legacy services
• Creates blind spots in your observability coverage
• Adds maintenance overhead

Coroot’s eBPF-based approach operates at the kernel level, capturing telemetry data without modifying application code. This provides complete coverage of your system, including services you cannot or do not want to modify.

AI Root Cause Analysis

The AI-powered RCA engine is what sets Coroot apart from other observability platforms. Instead of requiring you to manually correlate metrics, logs, and traces to find the root cause, Coroot’s AI engine does this automatically. When an issue occurs, the platform:

1. Identifies all affected services
2. Correlates telemetry data across all dimensions
3. Pinpoints the root cause
4. Provides actionable recommendations

This reduces the mean time to resolution (MTTR) by up to 80%, according to the project’s benchmarks.

Cost Monitoring

One of Coroot’s unique features is its ability to track cloud costs at the application level without requiring access to your cloud account. The platform analyzes resource usage patterns and correlates them with your cloud provider’s pricing model to show exactly how much each service costs to run.

Practical Evaluation Checklist

When evaluating Coroot for your organization, consider:

Strengths:

• Zero-instrumentation observability reduces setup time
• AI-powered RCA significantly reduces MTTR
• Works with existing infrastructure (Prometheus, OpenTelemetry, ClickHouse)
• Open-source with Apache-2.0 license
• Active development (7,757 GitHub stars, last commit 2026-06-15)
• Enterprise edition available for advanced features

Limitations:

• eBPF requires Linux kernel 4.14 or later
• ClickHouse storage can be resource-intensive for large deployments
• Some advanced features require Enterprise Edition
• Learning curve for teams new to observability concepts

Best for:

• Teams running Kubernetes or containerized workloads
• Organizations looking to replace expensive APM tools (Datadog, New Relic)
• SRE teams focused on SLO-driven development
• Companies needing to monitor legacy systems without code changes

Security Notes

Coroot is SOC 2 Type I certified, demonstrating compliance with security best practices. The platform is self-hosted, meaning all telemetry data stays within your infrastructure and never leaves your environment.

Key security considerations:

• Coroot requires read access to your Kubernetes cluster for deployment tracking
• eBPF operates at the kernel level but only captures telemetry data, not application data
• The platform does not require access to your cloud provider accounts for cost monitoring
• All data is stored in ClickHouse, which you control

For production deployments, review the security documentation and consider the Enterprise Edition for advanced security features.

FAQ

Q: Does Coroot work with non-Kubernetes environments? A: Yes, Coroot works with any Linux-based environment. While it has deep Kubernetes integration for deployment tracking, it can monitor applications running on VMs, bare metal, or other orchestration platforms.

Q: What kernel versions are supported for eBPF? A: Coroot requires Linux kernel 4.14 or later for eBPF-based telemetry collection. Most modern Linux distributions (Ubuntu 18.04+, CentOS 8+, Debian 10+) meet this requirement.

Q: How does Coroot compare to Datadog or New Relic? A: Coroot provides similar observability capabilities but is self-hosted and open-source. The main differences are: (1) Coroot uses eBPF for zero-instrumentation, while Datadog/New Relic require agents or SDKs; (2) Coroot is free (Community Edition) vs. per-host pricing; (3) Coroot keeps all data in your infrastructure vs. vendor cloud.

Q: Can Coroot monitor legacy applications? A: Yes, Coroot’s eBPF-based approach can capture telemetry from any application running on Linux, including legacy systems where you cannot modify the code or add instrumentation.

Q: What is the difference between Community and Enterprise Edition? A: The Community Edition includes core observability features (metrics, logs, traces, profiling, SLOs). The Enterprise Edition adds advanced features like multi-cluster support, enhanced security, priority support, and additional integrations. Check the editions comparison for details.

Q: How much resources does Coroot require? A: For small deployments (under 100 services), Coroot requires approximately 2 CPU cores and 4GB RAM. Larger deployments scale horizontally. ClickHouse storage requirements depend on your data retention policy and ingestion rate.

Conclusion

Coroot represents a significant shift in how teams approach observability. By combining eBPF-based zero-instrumentation with AI-powered root cause analysis, it eliminates the traditional trade-offs between coverage, setup complexity, and cost. The platform’s ability to automatically identify issues and provide actionable insights makes it particularly valuable for teams running complex, distributed systems.

For organizations currently paying for commercial APM tools like Datadog or New Relic, Coroot offers a compelling open-source alternative that keeps data in-house while providing comparable (and in some cases superior) capabilities. The active development community and enterprise support options make it a viable choice for both startups and large enterprises.

If you’re looking to improve your observability posture without the overhead of manual instrumentation or the cost of commercial tools, Coroot is worth evaluating. The live demo at demo.coroot.com provides a hands-on way to explore the platform’s capabilities before deployment.