Root cause intelligence for engineering teams

From noisy alerts
to the real root cause.

Rootline connects signals across services, infrastructure, logs, and deployments into a clear investigation path — so you see what changed, where it started, and what to fix.

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Trusted by engineering teams at
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Cinch
Xverum
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alert-manager · prod-cluster-us-east-1
CRITHigh error rate on api-gateway — p99 latency: 3.8s0s ago
CRITDB connection pool exhausted — payments-svc12s
WARNMemory usage 94% — checkout-worker28s
CRITPod CrashLoopBackOff — inventory-service41s
WARNDisk IOPS saturated — us-east-1c node pool1m
INFONew deploy detected — catalog-svc v2.41.32m
CRITSLO breach — order-fulfillment (97.1% avail.)3m
Showing 7 of 214 active alerts
The problem

Your systems are speaking.
Nobody can hear them.

Modern infrastructure fires hundreds of alerts per incident. Teams spend hours manually correlating logs, metrics, traces, and deploys — across five tools — while the outage clock runs. The real cause is buried inside the noise. Rootline surfaces it.

73%
of MTTR is spent finding the cause, not fixing it
4.8×
more tools used per incident than three years ago
2.4h
average time from first alert to root cause identified
$5.6M
average annual cost of downtime per enterprise
How it works

From signal chaos to clear cause — in minutes

Four deliberate steps from noisy alerts to confident resolution.

01
🔌
Connect your signals

Wire in your existing stack — metrics, logs, traces, deployments, topology — in minutes. No agents, no re-instrumentation.

02
🧠
Correlate automatically

Rootline maps relationships between services and infrastructure, then correlates anomalies across all sources to find common causes.

03
🔍
Trace the path

Every incident gets a ranked, explainable causal chain — from the symptom you observed back to the exact change that triggered it.

04
Resolve and prevent

Close incidents with confidence. Use Rootline's insights to prevent recurrence and build a lasting map of your system's failure modes.

Platform

Everything your team needs
to investigate faster

🗺️
Causal Investigation Paths

Rootline builds a ranked causal graph for every incident — showing not just what's broken, but the chain of events that led there. Every node explains its evidence.

Root cause identifiedcatalog-svc v2.41.3 — misconfigured DB pool (8 → 2)
Deployment event2m before incident — automated rollout to prod
Cascade to payments-svcQueue depth exceeded, timeouts propagated
User-facing impactCheckout SLO breach · p99 latency: 3.8s
📡
Signal Correlation Engine

Metrics, logs, traces, deployments, and topology — all correlated automatically so you never miss a connection.

Anomaly correlated across 6 sources in 8 seconds

🏗️
Topology Awareness

Live service dependency maps that update as your architecture evolves — so Rootline always knows what can affect what.

🚀
Deployment Tracking

Every deploy is automatically linked to the metrics and alerts that followed. Instantly see if a rollout is the cause — or rule it out.

📖
Incident Knowledge Base

Resolved incidents become institutional memory. Rootline surfaces past root causes so your team learns from history, not repeat it.

Alert Noise Reduction

Deduplicate and group hundreds of alerts into a single incident. Oncall engineers see one card, not 200 pages.

🔔
Slack & PagerDuty Native

Rootline lives where your team works. Investigation paths post directly to incident channels with one-click deep-dives.

Rootline — Incident #4821 · Production
Root cause — 94% confidence
catalog-svc deployment misconfiguration
v2.41.3
Root cause
DB pool size misconfigured in deploy
catalog-svc v2.41.3 · 14:02 UTC · config override applied
Cascade
Connection pool exhaustion → payments-svc
Queue depth: 842 · Timeout: 3s · 14:04 UTC
Propagation
api-gateway retry storm
1,400 req/s retries · p99 latency: 3.8s · 14:05 UTC
!
User impact
Checkout SLO breach · 214 alerts fired
Availability: 97.1% · 14:06 UTC · incident declared
Suggested action
Rollback catalog-svc to v2.41.2 or set DB_POOL_SIZE=8 in env config. Pattern matched to incident #3991 — see playbook.
Investigation

One view.
Every answer.

Rootline presents every incident as a clear, ranked causal chain — from the symptom your monitoring caught to the exact change that triggered it. No more tab-hopping.

🔗
Connected to all your data

Pulls signals from Datadog, Prometheus, PagerDuty, GitHub, Kubernetes, and more — no manual correlation required.

🧮
Confidence scoring

Every proposed root cause shows a confidence score and supporting evidence, so engineers can verify and move fast.

📚
Historical pattern matching

Rootline checks your incident history for similar patterns and surfaces past resolutions — often the fastest path to a fix.

Integrations

Works with
your entire stack

Rootline plugs into your existing observability and infrastructure tools. No rip-and-replace.

📊
Datadog
Metrics
🔥
Prometheus
Metrics
📈
Grafana
Dashboards
🐳
Kubernetes
Infra
☁️
AWS
Cloud
🌐
Azure
Cloud
🔵
GCP
Cloud
🔔
PagerDuty
Alerting
💬
Slack
Collab
⚙️
GitHub
Deploys
🔄
Jira
Tickets
30+ more
via API
85%
reduction in mean time to root cause
12×
faster investigation than manual triage
99.9%
uptime on Rootline platform SLA
<5m
to full integration with your existing stack
Customers

Teams who sleep better

"

Before Rootline, production incidents meant all-hands chaos across four tools. Now our oncall engineer has a causal path within 3 minutes of the first alert. It genuinely changed how we operate.

Daniel Amico
Daniel Amico
Data Architect · Xverum
"

The deployment correlation is a game changer. We used to spend 30 minutes figuring out if a deploy caused an incident. Rootline tells us in seconds and links it to the exact config change.

Sarah Jones-McKinley
Sarah Jones-McKinley
Engineering Lead · Rotate
Get started today

See the root.
Solve for good.

Join engineering teams who've replaced alert fatigue with clarity. Start your free trial — no agents, no infrastructure changes, no credit card required.

14-day free trial · SOC 2 Type II certified · GDPR compliant