Using Historical Graphs and Time Ranges

Overview

Server Scout's historical graphs provide powerful insights into your server's performance over time. Understanding how to effectively use these graphs can help you identify trends, investigate incidents, and plan for future capacity needs. The system automatically collects and stores metric data at different resolutions to balance detail with performance.

Available Time Ranges

Server Scout offers four distinct time ranges, each optimised for different use cases:

1 Hour View (Raw Data)

• Data Resolution: 5-second intervals
• Best For: Real-time monitoring and immediate troubleshooting
• Use Case: Investigating current performance issues or monitoring live system changes

6 Hours View (Short-term Trends)

• Data Resolution: 30-second averages
• Best For: Recent performance analysis and short-term trend identification
• Use Case: Reviewing performance during specific events or recent deployments

24 Hours View (Daily Overview)

• Data Resolution: 2-minute averages
• Best For: Daily performance patterns and routine monitoring
• Use Case: Identifying daily usage patterns and performance baselines

7 Days View (Weekly Analysis)

• Data Resolution: 15-minute averages
• Best For: Long-term trend analysis and capacity planning
• Use Case: Weekly performance reviews and identifying gradual changes

How Downsampling Works

Server Scout uses intelligent downsampling to maintain graph performance whilst preserving important data characteristics. The system:

1. Collects raw data at 5-second intervals continuously
2. Calculates averages for longer time periods automatically
3. Preserves peak values during the averaging process to ensure spikes aren't lost
4. Maintains data integrity by using statistical methods that represent the true system behaviour

This approach ensures that even when viewing compressed data over longer periods, you still see meaningful representations of your server's performance.

Interactive Graph Features

Canvas-Based Rendering

Server Scout uses HTML5 canvas for smooth, responsive graph rendering that handles large datasets efficiently. The graphs update dynamically and provide crisp visualisation even when displaying thousands of data points.

Hover Crosshair

Position your cursor anywhere on a graph to see:

• Exact timestamp for the data point
• Precise metric values at that moment
• Multiple metrics simultaneously when viewing combined graphs

This feature is particularly useful for pinpointing exact times when issues occurred or performance changed.

Gap Detection

Server Scout automatically identifies and displays gaps in your data when monitoring interruptions occur. Gaps appear when:

• Data collection stops for more than 3× the expected interval
• Network connectivity issues prevent data transmission
• Server Scout agent experiences downtime

These gaps help you understand when monitoring coverage was incomplete and prevent misinterpretation of data during outages.

Practical Applications

Capacity Planning

Use the 7-day view to identify:

• Growth trends in resource usage
• Peak usage periods and their frequency
• Seasonal patterns in your application load
• Resource headroom before hitting limits

Review these patterns monthly to make informed decisions about hardware upgrades or resource allocation.

Incident Investigation

When investigating issues:

1. Start with the 24-hour view to identify when problems began
2. Switch to shorter timeframes to examine the incident in detail
3. Use the hover feature to correlate exact timing across multiple metrics
4. Look for patterns that preceded the incident

Performance Optimisation

Regular graph analysis helps you:

• Establish baselines for normal performance
• Identify bottlenecks before they become critical
• Measure improvement after optimisations
• Correlate metrics to understand system behaviour

Best Practices

• Review daily graphs each morning to catch emerging issues early
• Use multiple time ranges to understand both immediate and long-term trends
• Document significant events to correlate with graph anomalies
• Set up alerts based on patterns you identify in historical data
• Compare similar time periods (e.g., week-over-week) to spot changes

Regular use of Server Scout's historical graphs transforms raw monitoring data into actionable insights, helping you maintain optimal server performance and prevent issues before they impact your users.