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Enterprise Project Architecture

Monorepo Foundation

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Apps and Delivery

Next.js PatternsVercel DeploymentCI/CD PipelineTesting Strategy

Agents and Operations

Agentic DevelopmentSkills EcosystemSecurity GovernanceMonitoring and Incident

Appendix

TemplatesReferencesUpdatesVerification
Handbook›Enterprise Project Architecture›Monitoring and Incident
한국어English

Monitoring and Incident

Operate logs, metrics, traces, alerts, runbooks, and post-incident learning.

Key takeaways

  • Observability stacks six layers: logs (what happened), metrics (how much/fast), traces (where), alerts (what needs attention now), dashboards (current health), and runbooks (what to do next).
  • Incident flow runs detect, triage, contain, resolve, communicate, postmortem, and prevent.
  • A runbook captures symptom, scope, checks, mitigation (rollback, flag, rate limit, workaround), escalation, and follow-up.
  • Postmortems focus on system improvement over individual blame, recording timeline, impact, root causes, and concrete owned follow-up tasks.
  • Both monitoring and incident response need ownership and rehearsal before production pressure arrives.

Monitoring tells the team whether the system is healthy. Incident practice tells the team what to do when it is not. Both need ownership and rehearsal before production pressure arrives.

Observability Layers

LayerQuestion answered
LogsWhat happened?
MetricsHow much, how often, and how fast?
TracesWhere did time or failure occur?
AlertsWhat needs attention now?
DashboardsWhat is the current health picture?
RunbooksWhat should the responder do next?

Incident Flow

Runbook Template

SectionContents
SymptomWhat alert or customer issue appears
ScopeAffected app, route, service, or customer segment
ChecksLogs, dashboard, recent deployments, dependencies
MitigationRollback, feature flag, rate limit, manual workaround
EscalationOwner, platform contact, business stakeholder
Follow-upTests, alerts, documentation, architecture fix

Postmortem Rules

  • Focus on system improvement, not individual blame.
  • Record timeline, impact, root causes, and contributing factors.
  • Create concrete follow-up tasks with owners.
  • Update runbooks and alerts when detection was weak.
  • Review whether deployment or review gates should change.

Related docs

Ch8. Incident Management Runbook

LLMOps and AgentOps in Production · Operate a unified standard for quality regressions, cost spikes, and policy bypass incidents

Incident Response

AI Security and Compliance Operations · Prepare AI-specific incident detection, containment, recovery, and communication.

References

Reference categories for adapting the enterprise project handbook to a specific organization.

Audit Readiness

AI Security and Compliance Operations · Build evidence pipelines for AI controls before formal audits begin.

Verification

Vercel Enterprise AI Platform · A checklist for validating an enterprise AI platform on Vercel.

Security Governance

Manage secrets, access, dependencies, permissions, and approval rules in enterprise projects.

Templates

Copy-ready operating templates for enterprise Next.js monorepos.

On this page

Observability LayersIncident FlowRunbook TemplatePostmortem Rules