Monitoring and Alerting Policy Template
A policy template that defines how alerts are configured, routed, escalated, and reviewed across services and infrastructure.
Note: This guide follows English-language naming conventions and terminology standards common in international development teams. Examples use English identifiers and comments to maximize compatibility across codebases and tooling.
Overview
A Monitoring and Alerting Policy defines how an organization detects problems, notifies the right people, and escalates when issues are not resolved quickly. Without a clear policy, teams suffer from alert fatigue, missed incidents, or inconsistent response times. This template provides a structured framework for alert thresholds, severity levels, routing rules, escalation paths, and regular review.
When to Use
- Setting up a new observability platform or monitoring stack.
- Onboarding a new service or team into the alerting system.
- Reviewing alert quality after a period of noise or missed incidents.
- Defining on-call responsibilities and escalation paths.
- Preparing for an audit of operational maturity or incident response.
Prerequisites
- A monitoring and observability platform such as Prometheus, Datadog, Grafana, New Relic, or PagerDuty.
- A list of critical services and infrastructure components.
- Defined on-call rotations and escalation contacts.
- A communication channel for alerts, such as Slack, Microsoft Teams, or email.
- An incident response process that alerts will trigger.
Solution
Policy Template
1. Alert Severity Levels
| Severity | Response Time | Example | Notification Channel |
|---|---|---|---|
| P1 - Critical | Immediate (5 min) | Service down, data loss, revenue impact | Page on-call + executive notification |
| P2 - High | 15 minutes | Degraded performance, failed backups | Page on-call + Slack alert |
| P3 - Medium | 1 hour | High error rate, resource pressure | Slack or email to owning team |
| P4 - Low | Next business day | Capacity warning, non-urgent drift | Email or dashboard notice |
| P5 - Informational | None | Usage metrics, trend data | Dashboard only |
2. Alert Categories
| Category | Purpose | Examples |
|---|---|---|
| Availability | Detect service unreachability | HTTP 5xx, connection timeout, health check failure |
| Performance | Detect latency and throughput issues | p99 latency > 500ms, queue depth high |
| Capacity | Detect resource exhaustion | CPU > 85%, disk > 80%, memory pressure |
| Error rate | Detect unusual failure rates | Error rate > 1% for 5 minutes |
| Security | Detect suspicious activity | Failed logins, rate limit hits, blocked traffic |
| Business | Detect revenue or workflow impact | Failed payments, order drop, signup failure |
| Data health | Detect pipeline or data quality issues | Stale data, missing partitions, sync lag |
3. Alert Routing Matrix
| Team | Primary Hours | On-Call Hours | Channels | Escalation Path |
|---|---|---|---|---|
| Platform team | 08:00 - 18:00 UTC | 24/7 | PagerDuty, #platform-alerts | Manager, then VP Engineering |
| Application team | 08:00 - 18:00 UTC | 24/7 | PagerDuty, #app-alerts | Team lead, then Engineering manager |
| Security team | 24/7 | 24/7 | PagerDuty, #security-alerts | Security lead, then CISO |
| Database team | 08:00 - 18:00 UTC | 24/7 | PagerDuty, #db-alerts | DBA lead, then Platform manager |
| Business operations | Business hours | None | Email, Slack | Operations manager |
4. Alert Threshold Guidelines
| Signal | Warning Threshold | Critical Threshold | Evaluation Window |
|---|---|---|---|
| HTTP error rate | > 1% for 5 min | > 5% for 2 min | Rolling 5 min |
| Response latency p99 | > 500ms for 10 min | > 1s for 5 min | Rolling 10 min |
| CPU utilization | > 70% for 10 min | > 90% for 5 min | Rolling 5 min |
| Disk utilization | > 75% for 1 hour | > 90% for 15 min | Rolling 15 min |
| Memory utilization | > 80% for 10 min | > 95% for 5 min | Rolling 5 min |
| Queue depth | > 1000 for 10 min | > 5000 for 5 min | Rolling 5 min |
| Failed backup | N/A | Any failed backup | Per job run |
| SSL certificate expiry | < 30 days | < 7 days | Daily check |
5. Escalation Rules
| Severity | Initial Alert | No Acknowledgment | Still Unresolved | Final Escalation |
|---|---|---|---|---|
| P1 | Page on-call immediately | 5 min | 15 min | Executive notification + war room |
| P2 | Page on-call | 15 min | 30 min | Manager page |
| P3 | Slack to owning team | 1 hour | 4 hours | Manager notification |
| P4 | Email or dashboard | Next business day | N/A | Weekly review |
6. Alert Review and Maintenance
| Activity | Frequency | Owner | Output |
|---|---|---|---|
| Alert quality review | Weekly | On-call engineer | Top noisy alerts, tuning actions |
| Alert runbook review | Monthly | SRE team | Updated runbooks for each alert |
| Threshold calibration | Quarterly | Observability team | Threshold adjustments with evidence |
| On-call retro | After major incident | Incident commander | Alert improvements, follow-up tasks |
| Policy review | Annually | Engineering leadership | Updated policy document |
Explanation
This policy turns raw monitoring signals into actionable alerts. By assigning severity, routing, and escalation rules, the organization ensures that critical problems get fast attention while low-priority warnings do not disrupt on-call engineers. The review and maintenance section prevents alert fatigue by continuously tuning thresholds and removing noisy alerts.
Variants
- Cloud-native alerting policy: Uses Prometheus Alertmanager, Grafana Oncall, or PagerDuty for container and serverless environments.
- Enterprise IT monitoring policy: Focuses on infrastructure, network, and service desk integration.
- Security alerting policy: Emphasizes SIEM rules, threat detection, and incident response triggers.
- Business operations alerting: Tracks KPIs, revenue, and customer-facing metrics with business-hour notifications.
- Developer self-service alerting: Allows teams to define their own alert rules within guardrails.
Best Practices
- Alert on symptoms that affect users, not just internal metrics.
- Use multi-window or multi-burn rate thresholds to reduce false positives.
- Require every alert to have an associated runbook or troubleshooting link.
- Route alerts to the team that can fix the problem, not a central queue.
- Keep alert messages concise and include context such as severity, service, and impact.
- Review noisy alerts weekly and tune or delete them.
- Test escalation paths during regular drills.
- Document alert thresholds and the rationale for changes.
Common Mistakes
- Alerting on every metric threshold without considering user impact.
- Sending all alerts to a single channel with no routing.
- Using the same severity for every alert.
- Not requiring acknowledgment or tracking resolution time.
- Ignoring alerts that fire repeatedly without action.
- Missing escalation paths for severe incidents.
- Failing to review and retire stale alerts after system changes.
FAQs
What is alert fatigue and how do we avoid it?
Alert fatigue happens when on-call engineers receive too many low-value alerts. Avoid it by tuning thresholds, grouping related alerts, suppressing known issues, and regularly deleting alerts that do not lead to action.
Should every alert page someone?
No. Only P1 and P2 alerts should page the on-call engineer. Lower-severity alerts should use Slack, email, or dashboard notifications to avoid disrupting response time for critical issues.
How do we know if our thresholds are right?
Track the ratio of actionable alerts to total alerts, measure mean time to acknowledge and resolve, and review false-positive rates. If an alert fires frequently without action, it is a candidate for tuning or removal.