Resilient Operations Center · AIOps & Managed Operations

From Alert Noise to
Probable Cause.
In Seconds.

The gap between a 4-hour incident and a 4-minute one isn't more engineers. It's intelligence.

See Case Studies
RCA in 43 seconds
CI-4589 · DB Connection Pool
Change correlated automatically
Deploy 2.1.4 linked to incident
Operations Dashboard
Live
System Health
98.5%
↑ +2.1%
Active Incidents
12
↓ -5
Alerts / Hour
234
↑ +12%
Automation Rate
87%
↑ +3%
Critical Incidents 3 Active
CI-4589P1
Database Connection Pool Exhaustion
Memory pressure on node db-03
CI-4590P1
API Gateway Timeout
Deploy 2.1.4 correlated — change linked
CI-4591P2
Memory Leak in Payment Processor
3 signals correlated · investigating
System Health
Application ServersHealthy
Database ClusterWarning
API GatewayHealthy
Message QueueHealthy
Cache LayerHealthy
Resilient Operations Center

AI-powered root cause analysis (AIOps)

A Resilient Operations Center (ROC) is a managed operations model that unifies your monitoring into a single AIOps engine. It correlates alerts across every tool, pinpoints the probable root cause in seconds, and enriches each incident with change context — turning noisy operations into fast, explainable answers.

The ROC pairs our managed cloud operations and SRE & observability practice with an AI engineering layer — and is proven in regulated financial services environments. Explore the case studies.

< 60s
to probable root cause from first alert fire
All sources
unified — logs, metrics, traces, APM, infra alerts
Any
monitoring stack — we work with whatever tools you have or need
Day 1
change context enriched into every ITSM incident ticket
The Real Problem

The root cause was there. The change that caused it was there. Everything needed to close the ticket — was already there.

It just wasn't connected. Here's why.

Alert Storms & Fatigue
Hundreds of alerts per hour from five different tools — none of them talking to each other. The signal exists. The noise just buries it. Engineers spend the first hour figuring out what fired, not fixing what broke.
No Single Source of Truth
Infra alerts in one place, app logs in another, APM traces somewhere else. Some teams have mature observability. Others have nothing. Incidents span all of it — but no one can see across all of it at once.
The Change That Caused It Was Known
A deployment went out 20 minutes before the incident. A config was changed that morning. It was all there — in your CMDB, your CI/CD logs, your change records. Nobody connected it to the alert. That's the 4 hours you lost.
What We Deliver

Three capabilities built for the ops team that's tired of firefighting.

01
Observability Foundation
We start with an assessment — not a tool recommendation. No monitoring? We build it right. Already on AppDynamics or Dynatrace? We mature it, not replace it. On Prometheus but alerting on the wrong things? We tune it. The goal is full-stack visibility. The tool is whatever's right for your scale, team, and budget.
AppDynamics Dynatrace Prometheus Grafana OpenTelemetry Datadog New Relic
02
AI-Powered Root Cause Analysis
Every alert source — Prometheus, CloudWatch, Datadog, Dynatrace, whatever you have — feeds into a single AI engine. It correlates signals across tools and teams, suppresses duplicates, and returns one probable root cause. In seconds, not hours. No war room. No log trawling. Just an answer.
Multi-source ingestion Alert correlation Noise suppression Probable cause ranking On-premise LLM
03
Change Intelligence Agent
The moment RCA fires, this agent activates. It queries your service topology, scans recent deployments and config changes, and asks: was something touched before this broke? If yes — it writes that context directly into the ITSM ticket. The on-call engineer opens the ticket and the answer is already there.
Topology graph access Change management integration ITSM enrichment ServiceNow · Jira · PagerDuty
How It Works

We connect the dots before anyone has to ask.

Input
Alert Sources
Prometheus / Alertmanager CloudWatch / Azure Monitor Datadog / Dynatrace Logs · Traces · Metrics
AI Layer
RCA Engine
Correlate & deduplicate Rank probable causes Suppress noise
< 60 seconds
Agent
Change Intelligence
Topology graph query Recent deployments scan Config change lookup
Output
Enriched ITSM Ticket
Probable root cause Linked change record Impacted services map Suggested next action
Our Approach

We don't have a favourite tool. We have a favourite outcome.

Assessment Before Prescription
We don't walk in with a pre-decided tool. We assess your environment, your team's maturity, your scale, and your existing investments — then recommend what's actually right. Sometimes that's Dynatrace. Sometimes it's Prometheus. Often it's both.
Works Across the Ecosystem
AppDynamics, Dynatrace, Datadog, New Relic, Prometheus, Grafana — we implement, migrate, and mature all of them. The AI RCA and Change Intelligence layer sits on top and ingests from any of them. Your existing tool choice doesn't block anything.
We Work With What You Have
Already on AppDynamics with years of dashboards built? We're not here to rip it out. We mature what's working, fix what isn't, and add intelligence on top — so the investment you've already made starts paying off more.
How We Engage

From zero to managed, intelligent operations in three stages.

Step 01
Assess & Architect
We audit your current monitoring state — what tools exist, what's missing, what's noisy. We map your service topology, identify observability gaps, and design the OSS stack and AI layer architecture for your environment.
Step 02
Implement & Integrate
We deploy the OSS monitoring foundation, instrument your services with OpenTelemetry, configure the AI RCA engine to ingest from all alert sources, and connect the Change Intelligence Agent to your topology graph and ITSM platform.
Step 03
Operate & Continuously Improve
Post go-live, we run managed ops — tuning alert thresholds, improving RCA accuracy, adding new signal sources, and delivering weekly SLO health reports. Alert quality improves measurably over the first 90 days.
FAQ

Resilient Operations Center & AIOps, answered.

What is a Resilient Operations Center (ROC)?

A ROC is BootLabs' managed operations service that layers AIOps — AI-powered root cause analysis — on top of your existing monitoring. It unifies logs, metrics, traces and alerts, correlates them into a single probable cause, and enriches every incident ticket with change context, so your team resolves incidents in minutes instead of hours.

How is AIOps different from Datadog or Splunk?

Datadog and Splunk are excellent monitoring and data platforms — they show you what is happening. Our AIOps layer sits on top of them (and any other tool) to explain why: it correlates signals across all your tools, suppresses duplicate alerts, and returns a single ranked root cause. We enhance your monitoring stack rather than compete with it.

Do you replace our existing monitoring?

No. The ROC is tool-agnostic and works with whatever you already run — Prometheus, Grafana, Datadog, Dynatrace, AppDynamics, CloudWatch, New Relic and more. If monitoring is missing or misconfigured we'll build or tune it as part of our managed cloud operations, but the goal is to add an intelligence layer on top, not to rip and replace.

What MTTR improvement can we expect?

Most teams move from multi-hour root cause analysis to a probable cause in under 60 seconds from the first alert, with change context waiting in the ticket before the on-call engineer even opens it. Real numbers depend on your environment — see representative outcomes in our case studies.

Get Started

Stop spending hours on RCA.
Let the AI do it.

Whether you need to build monitoring from scratch, migrate off a legacy tool, or add an AI intelligence layer on top of what you have — we'll scope it in a single discovery call.

View Case Studies