Hi everyone,
I’m looking for advice on managing and controlling query costs in DQL, especially when working with spans.
In my recent experiments, I’ve been querying spans for about 1–2 hours, even with a 500GB limit in a notebook, and I’ve already incurred more than €70 in costs. At that rate, this could scale to roughly €25K per year, which feels quite high for platform usage. Therefore I'm guessing there is a better way to achieve certain informational needs.
I’d love to understand how others are handling this more efficiently. Specifically:
- What are best practices to control or reduce query costs when working with spans?
- Do you rely on approaches like pre-aggregation (e.g., creating metrics or business events) instead of querying raw spans?
- How do you structure or use buckets to reduce the amount of data scanned?
- Are there recommended strategies for limiting data (time ranges, filters, sampling, etc.)?
- How do you monitor and optimize expensive queries effectively? Do we need to create anomaly detectors?
- Any insights, patterns, or real-world examples would be greatly appreciated.
Thanks in advance!
Michiel
#Performance matter!
