[ER] Node Hot Threads
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- Dominant language
- Rust
- Stars
- 30
- Forks
- 9
- Avg merge
- 1h 53m
- Merged PRs (30d)
- 15
Description
👋 Since you have a whole ecosystem going, would you kindly consider cross-pollinating analysis into your automation from [github/support/streamlit/hot_threads](https://github.com/elastic/support/blob/master/agentTools/streamlit/pages/es_hot_threads.py)? [Theory explanation](https://medium.com/@stefnestor/elastic-node-hot-threads-370111fab4e7).
The core part that matters is this after splitting the TXT file into per-node thread, then you do [this tag analysis](https://github.com/elastic/support/blob/master/agentTools/streamlit/helpers/es_hot_threads.py#L15-L223) to determine what different threads are about.
Support uses this in particular to dissect different search (aggregation, merge during prefilter, ESQL, etc) problems.
Some version much ago looked like
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
Start by reading the linked support implementation in agentTools/streamlit/pages/es_hot_threads.py and helpers/es_hot_threads.py, along with the theory explanation. Trace how the TXT file is split into per-node threads, then determine how the tag analysis should be incorporated into esdiag; done means the automation categorizes the different hot-thread topics, including search-related cases.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, rust, streamlit
- Domain
- observability
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100