Which sessions experienced the slowest load times, and why?
By comparing load time data across sessions, we can identify which sessions are slower and investigate why. The grouped bar chart shows load times per session categorized by browser, making it easy to visually spot outliers or trends. The accompanying grid provides numeric values for each session, including browser type, network connection, and error counts, which is helpful for precise analysis and cross-referencing against the chart.
Different browsers handle rendering, JavaScript execution, and caching differently. From the chart, we can observe sessions on certain browsers (e.g., Safari or Firefox) showing slightly slower load times.
A known issue is that Safari and Firefox do not support navigator.connection.effectiveType, so the network type may not always be captured for these browsers.
The chart quickly highlights the browser-related performance differences, while the grid allows detailed examination of each session to understand the cause.
Network speed and location can impact load times. Users with slower connections (e.g., 4G) tend to have longer load times. Since the server is in San Francisco and my location is near UCSD, local users may see faster load times compared to users in other regions. The chart visually summarizes trends across multiple sessions, and the grid allows checking individual session metrics to correlate slow load times with network types.
While most sessions show minimal activity or errors, error counts can indicate potential performance bottlenecks. The chart shows aggregate performance differences, whereas the grid helps pinpoint sessions where errors or idle periods might have contributed to longer load times. This combination allows both high-level and detailed insights into how user behavior affects page performance.
The small VPS and MongoDB free-tier instance may contribute to slower load times, especially for dynamic content or database queries. The chart allows monitoring trends across sessions to detect patterns, while the grid provides session-level details for deeper investigation into server or database impacts.
The chart helps quickly visualize performance trends by session, browser, and network type, giving an intuitive overview of potential bottlenecks. The grid complements this by offering precise numeric data that supports validation and deeper analysis of individual sessions. While the current data collection provides useful insights, limitations include missing network information for Safari/Firefox, coarse activity timing, and lack of server-side metrics.
The combination of grouped bar chart and grid provides both a visual overview and precise numeric detail, making it easier to identify slow sessions, understand contributing factors, and guide performance optimizations.