Alerts · Correlation · Routing Marketplace Agent

147 alerts. One incident. Right team notified.

Correlates alert storms into single incidents, determines severity and business impact, and routes to the right on-call team with full context—in seconds, not minutes. All on your infrastructure.

94%
Alert Noise Reduced
<30sec
Triage Time
99%
Routing Accuracy
🚨
Incident Triage Agent
Live alert processing
● LIVE
🚨 Alert Storm 147 alerts
Multiple services impacted • Started 47 sec ago
52 API latency
41 DB connections
34 Error rates
✓ Consolidated to 1 incident: INC-4521
SEV-1 Customer-Facing Outage • Database Team paged
Alert Noise Reduction 94%
Triage Time 23 seconds

Alerts flood. Signal drowns.

500 alerts per day. Which one matters?

  • Alert fires. Then another. Then 50 more. They're all the same incident, but each one pages someone. By the time you figure out they're related, three teams are working the same problem and getting in each other's way.
  • Alert fatigue is killing your team. 500 alerts a day. 90% are noise—transient blips, known issues, duplicate signals. Engineers start ignoring alerts. The real incident gets lost in the flood.
  • Wrong team gets paged. Database alert, so page the DBA. Except it's actually an application bug flooding the database. DBA escalates to app team. App team escalates to platform. 45 minutes of hot potato before the right person looks at it.
  • No business context. Alert says "API latency high." Is this impacting checkout? Is it costing money? Is it affecting 10 users or 10,000? Engineers have no idea what to prioritize.
  • On-call burnout is real. Your best engineers are exhausted. They get paged 5 times a night, often for the same cascading issue. They're considering other jobs—ones without on-call.
  • War room chaos. Major incident. 15 people join a call. No one knows what anyone else is doing. Duplicate investigation. Conflicting theories. Two hours to resolve what should take 20 minutes.

"We had a database failover. 247 alerts in 3 minutes. Seven different teams got paged. Everyone's looking at their own alerts, no one's looking at the actual problem. It took us 15 minutes just to figure out it was all one incident and that the DBA team should own it. By then, customers had been impacted for 20 minutes. The alerts were supposed to help us. Instead, they made everything worse."

— Director of SRE, Fintech Platform (400+ services)

Correlate. Prioritize. Route. Instantly.

Deploy an AI that correlates alert storms into single incidents, determines severity by business impact, and routes to the right team with full context—before humans even realize something's wrong.

01

Alert Correlation

Groups related alerts using topology awareness, timing analysis, and pattern matching. 147 alerts become 1 incident. One notification. One owner. No duplicate investigations.

02

Impact Analysis

Calculates business impact in real-time. Which customers affected? What's the revenue exposure? Which SLAs at risk? Severity assigned by actual impact, not arbitrary thresholds.

03

Intelligent Routing

Routes to the right team based on root cause hypothesis, not just alert source. Includes full context: what happened, what's impacted, similar past incidents, suggested runbooks.

Every incident type. Every source.

Outages

Service down, partial degradation, region failures. Immediate detection and escalation.

🐢

Performance

Latency spikes, throughput drops, resource exhaustion. Impact-based severity.

💾

Data Issues

Replication lag, corruption, inconsistency. Database team routing with context.

🔐

Security

Suspicious activity, breach indicators, access anomalies. Security team fast-track.

🌐

Network

Connectivity issues, DNS failures, certificate problems. Network team with topology.

☁️

Cloud Provider

AWS/GCP/Azure incidents. Correlates with provider status pages.

🔗

Third-Party

Vendor outages, API failures, dependency issues. External vs internal classification.

📦

Deployment

Bad deploy detection, rollback triggers, canary failures. Change correlation.

Real incidents. Fast response.

Alert Storm Management

147 Alerts → 1 Incident in 23 Seconds

Database connection pool exhausted. Cascading failures across 12 services. Alerts exploding. Old process: 7 teams paged, 15-minute war room. New process: correlated instantly.

Agent Action
🚨Alert storm: 147 alerts in 60 seconds
🔗Correlated: 52 API + 41 DB + 34 errors → postgres-primary
📊Impact: 34% checkout errors • $47K/hr revenue
🎯Consolidated to INC-4521 • SEV-1 assigned
📍Routed to Database Team • Sarah Chen paged
23 seconds vs 15 min war room • 7 teams → 1 team
Intelligent Routing

Right Team First Time

Alert: "Database CPU 95%." Old process: Page DBA → escalate to app → escalate to platform. 45 minutes of hot potato. New process: Root cause analysis routes correctly.

Agent Action
🚨Alert: Database CPU 95%
🔍Query analysis: 89% from recommendations-service
🔗Trace: Feature flag 'new-recs-algorithm' enabled 23m ago
🎯Hypothesis: Flag misconfiguration (87% confidence)
📍Routed to Platform Team (flag owner) • Not DBA
6 min resolution vs 45 min escalation chain
Business Impact Scoring

Prioritize What Matters

Two incidents simultaneously. Admin tool slow vs mobile checkout failing. Old process: Whoever pages louder. New process: Business impact decides.

Agent Action
📊Incident A: Admin tool • 12 internal users • $0/hr
📊Incident B: Mobile checkout • 3,400 users • $23K/hr
🎯Incident A → SEV-4 (backlog ticket)
🚨Incident B → SEV-2 (page Checkout Team)
Revenue-impacting issue prioritized correctly
Right priority Critical issues first • Noise doesn't page
Context-Rich Handoffs

Engineers Land Running

3 AM page. Engineer wakes up groggy. Old process: 20 minutes understanding the situation. New process: Full context delivered with page.

Agent Action
📋WHAT: Payment 503s • 12% failing • $8.2K/hr loss
⏱️TIMELINE: Started 4 min ago • Cache TTL expiry
💡HYPOTHESIS: Redis cache miss storm
📎SIMILAR: INC-2847 resolved with cache warm
🛠️RUNBOOK: Cache warm procedure linked
0 min context vs 20 min gathering • Engineers act immediately

Everything you need for faster incident response.

🔗

Alert Correlation

Groups related alerts by topology, timing, and pattern. Reduces noise by 90%+. One incident, one owner.

💰

Business Impact

Calculates revenue impact, user exposure, SLA risk. Severity based on what matters, not arbitrary thresholds.

🎯

Smart Routing

Routes by root cause hypothesis, not alert source. Right team first time. No escalation chains.

📋

Context Packets

Full context delivered with every page: what, impact, timeline, hypothesis, similar incidents, runbooks.

🔄

Change Correlation

Correlates incidents with recent deployments, config changes, feature flags. Identifies bad deploys instantly.

📊

Topology Awareness

Understands service dependencies. Knows upstream vs downstream. Traces impact paths.

📈

Pattern Matching

Identifies similar past incidents. Surfaces what worked before. Accelerates resolution.

🔕

Noise Suppression

Filters transient alerts, known issues, and expected behavior. Only actionable signals page.

Escalation Management

Automatic escalation if no acknowledgment. Respects schedules and time zones. Backup paths configured.

Connects with your alerting stack.

PagerDuty
Opsgenie
VictorOps
Datadog
New Relic
Prometheus
Grafana
Splunk
CloudWatch
Azure Monitor
Sentry
Slack
Microsoft Teams
ServiceNow
Jira
Statuspage

Know exactly what you're deploying.

Agent Goal

Transform alert chaos into actionable incidents through intelligent correlation, business impact scoring, and context-rich routing to the right team

Priority 1
Key Metrics
94% alert noise reduction <30 sec triage time 99% routing accuracy
Inputs & Outputs

Inputs: Alerts from monitoring tools, service topology, on-call schedules, historical incidents, deployment events, business impact mappings

Outputs: Correlated incidents, severity assignments, team routing, context packets, escalation triggers, status updates

Skills & Capabilities
  • Alert correlation by topology and timing
  • Business impact calculation (revenue, users)
  • Root cause hypothesis generation
  • Intelligent team routing
  • Similar incident matching
Decision Authority
Assign incident severity (SEV 1-4)
Route to on-call teams
Suppress noise and duplicate alerts
Escalate to leadership (SEV-1 only)
Modify alert thresholds
Change on-call schedules
Fallback / Escalation

Escalate to incident commander when: correlation confidence below 70%, unknown service detected, no on-call defined for team, page not acknowledged within SLA, SEV-1 incident declared

📋

Full Job Description

Complete BCG-aligned specification with correlation rules, severity criteria, and routing logic.

Download .docx

What's Inside

  • ◈ Complete agent description
  • ◈ Alert correlation rules
  • ◈ Worked examples by incident type
  • ◈ Required capabilities
  • ◈ Risk controls & guardrails
  • ◈ Permission boundaries
  • ◈ Monitoring integrations

Customize with Weaver

Connect your monitoring tools, define service topology, configure team routing rules, and set escalation policies for your organization.

Your incidents. Your data. Your infrastructure.

🤖

Agent (One-Time)

Pay once. Own the asset. Full source code on Google ADK. Deploy, modify, extend.

🔒

Alert Data Stays Yours

Alerts, incidents, and correlation patterns never leave your infrastructure. Full privacy.

🛡️

Annual Assurance

New integration support, correlation improvements, and pattern updates. You own agents; you subscribe to safety.

🔧

Weaver Customization

Configure correlation rules, severity criteria, and team routing for your organization.

Stop drowning in alerts. Start responding to incidents.

Deploy the Incident Triage Agent on your infrastructure. Correlated alerts. Smart routing. Teams that sleep.

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