> ## Documentation Index
> Fetch the complete documentation index at: https://docs.easyalert.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Recurring Alerts
> Identify noisy alerts for tuning, suppression rules, and alert optimization
## Overview
The Recurring Alerts page provides a comprehensive view of your most frequently triggered alerts. Use this data to identify candidates for tuning, create suppression rules, and reduce alert fatigue across your team.
See which alerts fire most frequently
Identify increasing or decreasing patterns
Export data and send email reports
Create suppression rules directly
***
## Summary Statistics
Four metrics provide an overview of recurring alert patterns:
| Metric | Description |
| --------------------- | ------------------------------------------------- |
| **Unique Alerts** | Number of distinct alert types |
| **Total Occurrences** | Sum of all alert instances |
| **Increasing Trend** | Alerts getting worse over time |
| **Avg Alert Share** | Average percentage of total each alert represents |
High "Increasing Trend" count indicates growing problems that need attention.
***
## Alert List Table
The main table displays detailed information about each recurring alert:
| Column | Description |
| --------------- | --------------------------------- |
| **#** | Rank by occurrence count |
| **Alert Title** | Alert name and associated service |
| **Count** | Number of times alert fired |
| **Trend** | Increasing, stable, or decreasing |
| **Volume** | Percentage of total alerts |
| **MTTA** | Average acknowledgment time |
| **MTTR** | Average resolution time |
| **Severities** | Breakdown by severity level |
| **Actions** | Quick action menu |
### Understanding Trends
| Trend | Icon | Meaning |
| -------------- | ---- | ---------------------------- |
| **Increasing** | 🔴 ↑ | Alert firing more frequently |
| **Stable** | âž– | No significant change |
| **Decreasing** | 🟢 ↓ | Alert firing less frequently |
Alerts with **Increasing** trends require investigation—they often indicate growing underlying problems.
***
## Filtering and Search
### Search
Search across multiple fields:
* Alert title
* Service name
* Host names
* Custom tags
### Trend Filter
Filter to see only:
* **All Trends** — Show everything
* **Increasing** — Alerts getting worse
* **Stable** — Consistent alerts
* **Decreasing** — Improving alerts
### Group by Service
Toggle "Group by Service" to aggregate alerts by service:
| Mode | Use Case |
| ------- | ------------------------------- |
| **Off** | See individual alert patterns |
| **On** | Identify noisy services overall |
Use "Group by Service" to find services that need comprehensive alert review.
***
## Taking Action
### From the Actions Menu
For each alert, you can:
Opens the incidents page filtered to this alert title
Pre-populates an alert rule with this alert's details
### Export Options
Click the download button to export all filtered data to CSV:
**Included Fields:**
* Rank, Alert Title, Service
* Count, Percent of Total
* MTTA, MTTR
* Severity breakdown
* Trend information
* Last occurrence
* Affected services and hosts
Click the email button to send a report to yourself:
**Report includes:**
* Summary statistics
* Top 20 recurring alerts
* Trend highlights
* Recommendations
Reports are sent to your registered email address.
***
## Identifying Tuning Candidates
### High-Priority Candidates
Alerts that should be reviewed first:
**Pattern:** Alert fires frequently but is mostly low/medium severity
**Action Options:**
* Increase threshold to reduce triggers
* Convert to informational alert
* Suppress during non-business hours
**Pattern:** Alert firing more frequently over time
**Action Options:**
* Investigate root cause of increase
* Fix underlying issue
* Temporarily suppress while fixing
**Pattern:** Alert takes long time to resolve
**Action Options:**
* Create or improve runbook
* Automate remediation
* Review if alert is actionable
**Pattern:** Alert fires and resolves quickly without action
**Action Options:**
* Increase alert delay/threshold
* Convert to warning level
* Implement hysteresis
### Creating Effective Suppress Rules
Determine what makes this alert non-actionable:
* Specific time windows?
* Certain environments?
* Below specific threshold?
Create precise conditions that match:
* Alert title patterns
* Source/service
* Severity level
Choose the right response:
* **Suppress** — Don't create incident
* **Reduce Severity** — Lower priority
* **Route Differently** — Send to different team
After implementing, verify:
* Desired alerts are suppressed
* Important alerts still come through
* Overall noise reduced
***
## Best Practices
Schedule weekly or bi-weekly reviews of recurring alerts:
* Monday morning review of previous week
* Include in team standup agenda
* Track progress on noise reduction
Focus on the top 10 recurring alerts:
* These represent most of the noise
* Improvements have biggest impact
* More manageable scope
For each reviewed alert, document:
* Decision made (tune, suppress, keep as-is)
* Reasoning
* Expected outcome
* Review date
Track metrics over time:
* Total unique alerts
* Total occurrences
* Percentage of alerts suppressed
* Team feedback on noise levels
Before suppressing, ask:
* Has this alert ever caught a real issue?
* Could we miss something important?
* Is there a better alternative (tuning vs. suppressing)?
Suppressions can become stale:
* Services change
* Thresholds should be reconsidered
* Set reminders to review suppression rules quarterly
***
## Common Patterns and Solutions
**Pattern:** Frequent disk space warnings that self-resolve
**Solutions:**
* Increase threshold (e.g., 80% → 90%)
* Implement auto-cleanup scripts
* Add hysteresis (alert only after X minutes)
* Separate critical partition alerts from non-critical
**Pattern:** Brief spikes in connection pool usage
**Solutions:**
* Increase pool size if appropriate
* Add averaging/smoothing to alert
* Alert on sustained high usage, not spikes
**Pattern:** Same job fails and succeeds on retry
**Solutions:**
* Improve job retry logic
* Alert only after N failures
* Separate transient vs. persistent failures
**Pattern:** Health checks failing/recovering rapidly
**Solutions:**
* Add dead time between alerts
* Require multiple consecutive failures
* Review health check timeout settings
**Pattern:** Alerts during deployments
**Solutions:**
* Implement deployment windows with suppression
* Use canary/gradual deployments
* Improve deployment health checks
***
## Pagination and Large Datasets
For organizations with many alerts:
### Pagination Controls
* **Rows per page:** 10, 25, 50, or 100
* **Navigation:** Previous/Next page buttons
* **Position indicator:** "1-25 of 150"
### Working with Large Lists
* Use search and filters to narrow down
* Export to CSV for offline analysis
* Focus on top performers by incident count
* Use "Group by Service" to aggregate
***
## Troubleshooting
* Verify incidents exist in the selected date range
* Check that incidents have title information
* Ensure incidents are assigned to your tenant
* Trends compare current period to previous period
* Short date ranges may show variable trends
* Try longer date range for more accurate trends
* Verify incidents have service metadata
* Check integration is sending service information
* Review alert payload configuration
* Exports include current filter results
* Clear filters to export all data
* Maximum export is 100 alerts
* Check spam/junk folders
* Verify email address in profile
* Contact admin if email delivery issues persist
***
## URL Parameters
The page supports URL parameters for deep linking:
| Parameter | Description | Example |
| ---------------- | ----------------------- | ---------------------- |
| `days` | Date range in days | `?days=14` |
| `groupByService` | Enable service grouping | `?groupByService=true` |
| `search` | Pre-fill search | `?search=database` |
| `trend` | Filter by trend | `?trend=increasing` |
Bookmark filtered views for quick access to specific alert categories.
***
## Related Pages
Create suppression rules
Detailed incident metrics
Configure alert sources