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Comparison

BitSentry vs Coroot: Two Ways to Get to Root Cause

Coroot traces dependencies with eBPF. We read logs over SSH. Same goal, different route.

Agustinus Theodorus April 9, 2026 Updated April 13, 2026 4 min read

Coroot and BitSentry both promise faster root cause analysis. Coroot gets there through eBPF instrumentation and service dependency maps. We get there through SSH and log interpretation. Same destination, completely different route.

If you’ve been looking at open source RCA tools, you’ve probably seen Coroot. 7,300+ GitHub stars, used by Walmart and Comcast, installs in minutes with zero code changes. It’s a legitimate product. The question is which approach to root cause fits your infrastructure better.


How Coroot finds root cause

Coroot is an observability platform. It collects metrics, logs, traces, and continuous profiling data, mostly through eBPF (which means no SDK or code instrumentation needed). It maps your service dependencies automatically and builds a visual topology of what talks to what.

When something breaks, Coroot’s AI traces the problem through the dependency graph. Service A is slow because Service B is timing out because the database connection pool is saturated. The RCA follows the dependency chain.

This works well in containerized environments where services have clear network boundaries. eBPF captures everything at the kernel level, so Coroot sees traffic patterns that application-level monitoring might miss.

They also have SLO-based alerting, which means you set targets (“99.9% of requests under 500ms”) and Coroot alerts when you’re burning through your error budget. That’s a different philosophy from threshold-based alerts.

How we find root cause

We don’t instrument your services or map dependencies. SuperTerminal connects to your servers over SSH, runs diagnostic commands, and has the AI read the output.

The workflow in SuperTerminal: you describe the incident (“payment processing is failing”), the tool SSHes into the relevant servers, runs commands (log queries, service checks, resource monitoring), and the AI interprets each step’s output before deciding what to check next. It’s closer to what a senior engineer does manually, except the AI handles the log reading.

We also sell a separate product, the BitSentry Dashboard, which runs this in the background continuously. It pulls from error sources like Sentry and Wazuh, investigating anomalies before they page anyone.

No eBPF, no agents, no instrumentation. Uses your existing SSH access.

Where they actually differ

CorootBitSentry
Data collectioneBPF + OpenTelemetry (automatic)SSH commands (on-demand or scheduled)
SetupInstall agent, zero code changesPoint at SSH config, ~5 minutes
RCA methodDependency graph tracingLog interpretation + AI reasoning
Best environmentKubernetes, containerized microservicesAny server with SSH (VMs, bare metal, containers)
VisualizationService maps, dashboards, SLO chartsRoot cause reports with evidence
Open sourceYes (7,300+ GitHub stars)SuperTerminal desktop app (free beta)
Continuous monitoringYes (always collecting)Dashboard: yes. SuperTerminal: on-demand.
AI modelCoroot’s built-inYour choice (6 providers, your keys)
PricingFree (open source) / Cloud pricing for hosted$7,200/year (Pro)

The infrastructure question

This comes down to what your servers look like.

If you’re running Kubernetes with dozens of microservices and the root cause usually lives in the interactions between services (latency cascades, connection pool exhaustion, upstream failures), Coroot’s dependency-based RCA is strong. eBPF captures the network-level signals that tell you which service is actually the source of the problem vs which service is just a victim.

If you’re running traditional servers (VMs, bare metal, or a mix), or if the root cause tends to live in application logs and server state rather than in service-to-service traffic, our SSH approach gets to the answer more directly. You don’t need to instrument anything. You don’t need Kubernetes. You need SSH access and logs.

Most real infrastructure is a mix. Some teams run both approaches for different parts of their stack.

The open source angle

Coroot being open source is a genuine advantage for teams that want to self-host everything and control their data. You can run the whole thing on your infrastructure, inspect the code, and contribute fixes.

SuperTerminal is free during beta but not open source. The local-first architecture means your data stays on your machine, but the tool itself is closed source. The Dashboard has a self-hosted option on the Enterprise plan.

If “open source or nothing” is your policy, Coroot wins by default.

When to use which

Coroot if your infrastructure is mostly Kubernetes, you want continuous observability with service maps, and you prefer open source. It’s also free to self-host, which matters if budget is the constraint.

SuperTerminal if your infrastructure includes traditional servers, you want AI to read logs and reason about root cause, and you want investigation to start from an SSH terminal.

Both if you have a mixed environment. Coroot watches the containerized services. SuperTerminal investigates the VMs and bare metal when something goes wrong that eBPF doesn’t explain.


Try SuperTerminal

Free while in beta. Uses your SSH config and your own AI keys. Set it up in 5 minutes.

Try SuperTerminal free

Uses your existing SSH config and your own AI keys. Set up in under 5 minutes.

Tags

SuperTerminal Dashboard Coroot comparison root cause analysis observability eBPF open source