Root cause analysis
Root cause analysis, performed by an agent
A root cause analysis tool works out why a service broke, not just that it broke. An agentic one goes further: it gathers the signals itself across application, infrastructure, network and cloud, lines them up on a timeline, finds what changed, and writes up the probable cause with the evidence behind it — so the reasoning can be checked rather than trusted.
What automated RCA actually does
The first hour of an incident is the same work every time: open four or five consoles, pull the relevant windows, line them up, find what changed, work out what it affects, write it up. That hour is what the RCA Agent takes on, so the engineers arrive at a formed hypothesis instead of a blank page.
- Gather — collect the metrics, logs, events and traces around the incident window from the tools that already hold them.
- Correlate — group related signals across domains into one incident instead of a hundred alerts.
- Locate — use topology and dependency data to work out which component the symptoms point back to.
- Explain — state the probable cause and show the evidence, including what was ruled out.
- Act — hand off to remediation once a person approves it, and record exactly what ran.
Manual, rule-based and agentic RCA are not the same thing
| Manual RCA | Rule-based correlation | Agentic RCA | |
|---|---|---|---|
| Starts when | An engineer opens the ticket | An alert matches a rule | On an alert, a schedule, or on request |
| Gathers evidence | By hand, console by console | From the sources the rule names | Itself, from every connected domain |
| Scope of reasoning | Whatever the engineer checks | One domain at a time | Across application, infrastructure, network and cloud |
| Output | A written finding, hours later | A grouped alert | A probable cause with its evidence, in minutes |
| Leaves an audit trail | Only what was typed up | Of the rule that fired | Of every tool call, input and conclusion |
The agents behind it
Fabrix.ai ships these as named agents rather than one opaque assistant, so each can be enabled, scoped and audited on its own.
- RCA Agent — performs root cause analysis by correlating signals across the stack.
- Anomaly Detection Agent — detects abnormal patterns across metrics, logs and events, often before a ticket exists.
- Syslog Insights Agent — analyses syslogs to surface the error patterns that explain a failure.
- Network Change Risk Assessment Agent — identifies whether a recent change is the likely cause.
- Remediation Agent — executes the approved fix across apps, infrastructure and cloud.
- Asset Health Reporting Agent — tracks service and asset health so degradation is visible before it becomes an incident.
What makes it safe to run in production
- Read-only by default. Investigation needs no write access. Anything that changes state waits for a person to approve it.
- Your data stays put. Agents query monitoring, logging and ticketing systems where they already run, with no copy and no migration.
- Every run is auditable. Inputs, tool calls, conclusion and approver are recorded, so a decision can be reconstructed months later.
- Your model, your environment. Cloud, Fabrix-managed or on-premises, including sovereign and air-gapped deployments.
Questions we get asked
What is a root cause analysis tool?
A root cause analysis tool identifies the underlying reason a service failed or degraded, rather than reporting the symptom. In IT operations it correlates metrics, logs, events and topology from across the stack, works out which component the symptoms point back to, and presents that conclusion with the evidence supporting it.
How is automated RCA different from alert correlation?
Alert correlation groups related alerts so a flood becomes one incident. That reduces noise but still leaves a human to work out the cause. Automated root cause analysis takes the grouped incident as its starting point, gathers further evidence across domains, and names the probable cause.
How long does agentic root cause analysis take?
Minutes rather than hours, because the gathering and correlating happen in parallel across every connected system instead of console by console. The saving is largest on cross-domain incidents, where the manual version means a call with four teams.
Can it fix the problem as well as find it?
Yes, once a person approves it. The RCA Agent hands off to the Remediation Agent, which executes pre-approved runbooks and API calls across applications, infrastructure and cloud. Investigation is read-only by default; acting is a separate, scoped grant.
What does it need access to?
Read access to the systems holding the evidence: monitoring and observability, logs, ticketing and ITSM, network and cloud. Fabrix.ai connects to those through 2000+ pre-built bots, REST APIs and Model Context Protocol, so nothing has to be replaced or migrated.
See the RCA Agent investigate an incident in your own stack.
Request a demo