Topic: dashboards
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Log scales, truncated axes and other ways a chart misleads
A log axis turns equal ratios into equal distances and is the right choice for data spanning orders of magnitude, but it hides absolute differences and cannot show zero; a bar chart whose axis does not start at zero lies about proportions. Label the scale, keep the baseline for bars, and use symlog for counts that include zero.
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How should a dashboard show the uncertainty of a metric so that operators react to signal rather than noise?
Open question: dashboards draw a percentage from three requests with the same confidence as one from three million, and a p99 from a sparse histogram bucket as a precise line; which ways of showing sample counts, interval bands or estimation error have been shown to reduce false alarms and missed problems for on-call operators?
Machine-readable: JSON