Metric graphs 101: Graphing anti-patterns

This article discusses three anti-patterns in visualizing monitoring data and suggests better solutions. Firstly, the author discourages using stacked area graphs for large groups as they become less effective with increasing size of the group, leading to loss of vertical resolution. Instead, it recommends using an aggregate timeseries graph for the big picture and complementing it with focused looks at individual behavior through heatmaps, host maps, line graphs, and outlier detection graphs. Secondly, the author advises against using one tool for everything and suggests using heatmaps and bar graphs instead of line graphs in certain cases. Lastly, the article warns against summing something that shouldn't be summed and recommends using line graphs or heatmaps depending on whether precision or trends are more important. The key takeaway is to use appropriate graph types for different metrics and scale levels to ensure clarity and readability of monitoring data visualizations.