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feat(extrapolation): add guidance on when to switch to sample mode in…
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… extrapolation (#11986)
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shellmayr authored Nov 28, 2024
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Expand Up @@ -72,6 +72,12 @@ In new product surfaces, the question of whether to use extrapolated vs. non-ext
- Does the user care more about a truthful estimate of the aggregate data or about the actual events that happened?
- Some scenarios, like visualizing metrics over time, are based on aggregates, whereas a case of debugging a specific user's problem hinges on actually seeing the specific events. The best mode depends on the intended usage of the product.

### Switching to Sample Mode
Sample mode is designed to help users investigate specific events. Here are two common scenarios where it makes the most sense:

1. **When both sample rate and event volume are low**: Extrapolation becomes less reliable in these cases. You can either increase your sample rate to improve accuracy, or switch to sample mode to examine the actual events - both are valid approaches depending on the user's needs.
2. **When you have a high sample rate but still see low event volumes**: In this case, increasing the sample rate won't help capture more data, and sample mode will give you a clearer picture of the events you do have.

### Opting Out of Extrapolation
Users may want to opt out of extrapolation for different reasons. It is always possible to set the sample rate for specific events to 100% and therefore send all data to Sentry, implicitly opting out of extrapolation and behaving in the same way as sample mode. Depending on their configuration, users may need to change Dynamic Sampling settings or their SDK's traces sampler callback for this.

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