NEW Ceburu AI 2.0 — root-cause analysis in seconds

Every signal. One platform.

Ceburu unifies metrics, logs, traces, and events into a single AI-driven observability layer — so your team stops jumping between dashboards and starts shipping.

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SOC 2 Type II HIPAA ready Cloud & On Prem 130+ integrations
app.ceburu.io/incidents/INC-3492
Overview Incidents Detectors Topology
INC-3492 · checkout p99 spike LIVE · 04:21
p99 latency
2,318ms
↑ 412% vs baseline
Error rate
14.2%
↑ 8.1pp
Saturation
92%
↑ 38pp
Affected users
3,482
↓ stabilizing
Incident timeline · 4 services involved AI annotated
14:02:11
Detector fired: checkout p99 > 800ms
prod-us-east · severity = critical · pod checkout-7df
14:02:18
Ceburu AI correlated 3 events into one root cause
linked: deploy api@4.18.2 · trace 0x7af2… · 412 log spikes
14:03:04
Saturation alarm: connection pool 92% on prod-db-07
cluster = prod-us-east · max_conns = 200
14:04:22
PagerDuty notified · #sre-oncall paged
on-call = priya.a · response SLA = 5m
Connects to the stack you already run · 130+ integrations
AWS
Azure
Kubernetes
Docker
Slack
PagerDuty
ServiceNow
GitHub
Jira
Okta
Prometheus
Grafana
The unified observability platform

Stop connecting the dots.
We absorbed them.

Other tools force you to stitch metrics, logs, traces, and deploys across 5 vendors. Ceburu ingests every signal into one model — so the correlation is the platform, not your weekend.

Metrics
Logs
Traces
Topology
Alerts
Deploys
Ceburu Core
Unified signal model
One schema. Every signal correlated by service, deploy, request, and user — automatically.
1.2M
events/s
87ms
p99 ingest
94%
auto-correlate
5 vendors1 platform · 38m MTTR6m MTTR · 4 dashboards1 incident view
Platform capabilities

Everything your IT team needs.
Nothing it doesn't.

From AI-powered anomaly detection to bank-grade secure data transfers — built for enterprise scale.

AIOps in action

From reactive firefighting
to proactive intelligence

AI algorithms analyze your entire stack in real time — surfacing actionable insights, not noise.

Predictive anomaly detection before incidents occur
ML-driven alert correlation — eliminate alert fatigue
Automated remediation workflows at enterprise scale
Self-optimizing systems that learn and continuously adapt
Live intelligence feed
[AI] Anomaly node-07 — auto-resolved
[SIEM] Threat 198.51.x.x — investigating
[PATCH] 47 endpoints — complete
[NET] Edge latency — auto-rerouted
[BACKUP] 14.2TB verified —
0
Critical alerts
99.97%
Uptime (30d)
1.4ms
Avg response
What's inside

Built for the 3am page,
not the quarterly review.

Every primitive — detectors, correlation, AI summaries, runbooks — designed for the moment your phone buzzes and the dashboard's already a mess.

Adaptive detectors
Anomaly detection that learns your baselines per-service, per-region, per-deploy. No more p99 > 800ms hardcoded thresholds that fire every Tuesday at noon.
checkout-svc · p99last 6h
baseline · 612msspike · 2,318ms (3.8σ)
Live SLO board
Track every error budget, every region, in one view. Burn-rate alerts that pre-empt the 3am page.
api availability99.96%
checkout latency98.2%
db connection pool94.1%
queue lag99.99%
Ceburu AI · root cause
Correlate metrics, logs, traces, and deploys to one prose explanation. Cite every event. Suggest a fix.
"Connection pool exhaustion on prod-db-07 introduced by api@4.18.2, 11min before first breach."
87% confidence · 3 evidences
Distributed tracing
OpenTelemetry-native. Drop into a span, see the request, the deploy, the user. Mean session replay built in.
api-gateway · 2,318ms
checkout-svc · 1,940ms
db.query · 1,210ms
pool.acquire · 920ms
Auto-remediation
Define guarded actions — rollback, scale, drain. Ceburu proposes; on-call approves; production heals.
Roll back api@4.18.2 → 4.18.1 approved
Scale db pool → 400 queued
Page #sre-oncall done · 14:04
From signal to ship

Three steps. Zero glue code.

01 / Connect

Point us at your stack.

One agent. One Helm chart. One OTel collector. Whatever you already run, Ceburu ingests — without re-instrumenting.

# Helm install helm install ceburu \ oci://reg.ceburu.io/agent \ --set token=$CEBURU_TOKEN
02 / Define

Detectors as code.

TypeScript SDK. PR-reviewable. Your detectors live in the repo with the service they protect — not in someone's saved view.

const d = ceburu.detector({ query: "db.latency.p99{prod}", baseline: "7d.median", threshold: "2σ", });
03 / Resolve

Let the AI close the loop.

Detect. Correlate. Recommend. Approve. Remediate. The page gets shorter — and so does the runbook.

// On fire await ceburu.ai.correlate(e); await ceburu.remediate("rb-022"); // MTTR: 6m → resolved.
Customer outcomes

Built for the teams that
keep the world running

"

"Ceburu has changed the way we approach cybersecurity. Their intuitive platform lets us focus on patient care, knowing our IT environment is protected."

IT Director
Nicklaus Children's Hospital
Healthcare
"

"AI-powered monitoring has significantly reduced downtime and improved operational efficiency. It's essential infrastructure across our fleet operations."

Infrastructure Lead
Ryder Systems, Inc.
Transportation
"

"We needed something powerful yet user-friendly. Ceburu delivered exactly that — streamlined technology management at a scale we didn't think possible."

Operations Manager
Miami Dolphins
Sports & Entertainment
Nicklaus Children's Hospital
Palm Medical
Ryder Systems
Miami Dolphins
Baptist Health

Ship faster.
Sleep through the night.

Join the enterprises running APM, NPM, AIOps, Infrastructure, and Security in one single platform.