Improve escalation algorithm for slow increase in events volume
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- Dominant language
- Python
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Description
Problem Statement
A user had an issue that ramped-up in event volume over a month. The volume went from less than a hundred a day, to a few hundred, to a few thousand and ended with more than 10K events per day. See graphs:
This issue is marked as "Archived until escalates":
[User] Archived until it escalates - 3 months ago
The issue was not marked as escalated after the period above.
Solution Brainstorm
From the investigation, the slow increase at the start of July did not reach the limit to trigger a escalation, and also served to increase the limit even more for the next days.
This is a request to make the algorithm more sensitive, because from a user's point of view this issue clearly esclated. But the current algorithm do not see it the same way.
Similar requests:
Product Area
Issues
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No implementation file, test, or entry point is named. Start by tracing the Issues escalation algorithm and reviewing similar requests #76530 and #69179; establish how gradual event-volume growth affects escalation and limits. Done means a reproducible slow-growth case escalates as users expect, with regression coverage and an agreed sensitivity threshold.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- observability-sre
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100