Trends

Analyze error patterns over time to understand the health of your application.

Overview

The Trends view helps you:

• Identify error spikes
• Track error rates over time
• Compare releases
• Understand user impact

Error Timeline

Chart Types

• Area chart - Total errors over time
• Line chart - Compare metrics
• Bar chart - Errors by category

Time Ranges

• Last hour (1-minute intervals)
• Last 24 hours (1-hour intervals)
• Last 7 days (daily intervals)
• Last 30 days (daily intervals)
• Custom range

Metrics

Metric	Description
Events	Total error occurrences
Issues	Unique error types
Users	Affected users
Rate	Errors per request

Grouping

By Issue

See which issues contribute most errors:

Issue                               Events    %
─────────────────────────────────────────────────
TypeError: Cannot read 'name'       1,234    45%
ConnectionError: Timeout            567      21%
ValidationError: Invalid email      234       9%
Other (15 issues)                   678      25%

By Release

Compare error rates across releases:

Release    Events    Error Rate    Change
───────────────────────────────────────────
v2.1.0     234       0.12%        +0.03%
v2.0.5     456       0.09%        -0.01%
v2.0.4     789       0.10%         base

By Environment

Environment    Events    Users    Error Rate
────────────────────────────────────────────
production     1,234     456      0.08%
staging        567       123      0.12%
development    2,345     12       0.45%

By Browser/Device

Browser         Events    %
────────────────────────────
Chrome 120      567      45%
Safari 17       234      19%
Firefox 120     123      10%
Other           321      26%

Identifying Patterns

Spike Detection

When error rate increases significantly:

1. Alert triggered - If alert configured
2. Timeline marked - Visual indicator on chart
3. Related changes - Deployments, config changes

Time-Based Patterns

Identify recurring issues:

• Daily peaks (business hours)
• Weekly patterns (Monday deployments)
• Monthly cycles (billing, reports)

Release Correlation

See if errors correlate with releases:

1. Deploy markers on timeline
2. Before/after comparison
3. Error delta per release

Drill Down

From Trend to Issues

1. Click on a time point
2. See issues active during that period
3. Filter dashboard to that time range

From Group to Details

1. Click on a release/browser/etc.
2. See all issues for that group
3. Compare with other groups

Comparison

Compare Time Periods

• This week vs last week
• This release vs previous
• Before/after a change

Compare Projects

If you have multiple projects:

• Side-by-side metrics
• Relative error rates
• Shared issues

Reports

Scheduled Reports

Receive email reports:

1. Go to Settings → Reports
2. Configure frequency (daily, weekly)
3. Select recipients
4. Choose metrics

Export Data

Export trend data:

• CSV for spreadsheets
• JSON for programmatic access
• PDF for presentations

Alerts Based on Trends

Create alerts for:

• Error rate exceeds threshold
• New issue in release
• Spike detection
• Regression detection

Configure alerts →

Best Practices

Regular Review

• Daily: Check for spikes
• Weekly: Review top issues
• Monthly: Trend analysis
• Per release: Before/after comparison

Setting Baselines

1. Establish normal error rate
2. Set alert thresholds above baseline
3. Adjust as you fix issues

Tracking Improvements

• Mark when fixes are deployed
• Compare before/after
• Track error rate reduction

Next Steps

• Alerts - Set up notifications
• Issues - Manage issues