Every incident
has a root cause.
Server, Docker and Kubernetes monitoring that tells you exactly what broke, what it is causing, and how to fix it. 223 built-in root-cause signatures.
What is Kllyroo?
Kllyroo is infrastructure monitoring software that identifies the root cause of an incident rather than simply reporting alerts. Built by Kirshi Technologies, it monitors servers, Docker containers and Kubernetes clusters through a single lightweight agent on Linux and Windows.
It uses 223 root-cause detection signatures, causal alert correlation, predictive ETA alerts, 40 security exploit signatures, built-in SSH session recording and an AI chat assistant grounded in live data. Pricing starts at $8 per server per month and scales by server count, not data volume.
Nine capabilities.
One agent.
Root-cause signatures
223 detectors across web, app, database and queue layers — each with a specific fix, not a generic anomaly score.
Causal correlation
Cascading failures collapse into one incident with a named root cause, not five disconnected pages.
Containers & Kubernetes
Docker lifecycle and health, plus node, pod and deployment monitoring. Same agent, same dashboard.
Predictive alerts
ETA-to-threshold forecasting and baseline anomaly detection on CPU, memory and restart rate.
Security detection
40 signatures catch exploit scans in real time — RCE, SSRF, Log4Shell, webshells and more.
Session recording
Every SSH session recorded and searchable by command. Audit trail built in, no separate tool.
Not trying to out-feature Datadog.
Trying to out-explain it.
They have a decade of integrations we do not, and code-level APM we do not have yet. What we do better is name the actual cause — and we include SSH session recording, which they do not offer, at per-server pricing rather than per-host plus per-gigabyte.
Simple, per-server pricing.
Growth
Adds correlation, Kubernetes, AI chat and session recording.
Book a demoPrices shown are starting points for planning. Final pricing is confirmed during your demo based on fleet size and deployment model.
See your own infrastructure, explained.
Point one agent at a handful of servers and watch the first correlated incident happen.