The Problem with Pre-aggregated Metrics: Part 3, the “metrics”
Blog post from Honeycomb
The third installment in a series on the limitations of pre-aggregated metrics delves into the challenges of relying on individual metrics for understanding system performance over time. It highlights the isolated nature of metrics as standalone data points, which can limit the ability to reconstruct the underlying reality of system behavior, especially in complex systems with multiple attributes. Using a datastore example, the text illustrates the problem of anticipating and managing metrics across various dimensions, such as operation type and namespace, and the impracticality of storing numerous cross products. Instead, the post advocates for a more flexible approach, using tools like Honeycomb, to iteratively explore data and reveal patterns and relationships between attributes, which can be more insightful than attempting to visually align trends from disparate graphs. This method allows for direct examination of anomalies and provides a clearer understanding of system dynamics, challenging the traditional reliance on pre-aggregated metrics for performance analysis.
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