Metric graphs 101: Graphing anti-patterns

This post highlights common pitfalls in graphing monitoring data and provides guidance on how to avoid them. It discusses the use of phyllo graphs, which are often misused due to their inability to handle large groups effectively, leading to visual overload. The solution is to use aggregate timeseries graphs for big-picture views, complemented by focused graphs such as heatmaps, host maps, and line graphs that track performance envelopes or outlier detection. Additionally, the post cautions against using one tool for everything, as this can lead to "spaghettification" of data, and instead recommends using bar graphs for sparse metrics, aggregating metrics when precision matters most, and employing heatmaps when trends are paramount. The key takeaway is that careful consideration of graph types and design can improve the clarity and usability of monitoring dashboards.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.