Repository navigation
Add Kubernetes node pressure anomaly detection notebook - #602
Merged
jarturomora merged 2 commits intoOct 5, 2026
Merged
jarturomora merged 2 commits into
jarturomora merged 2 commits into
Conversation
|
Found 1 changed notebook. Review the changes at https://app.gitnotebooks.com/elastic/elastic-labs/pull/602 |
jarturomora
approved these changes
Oct 5, 2026
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Companion notebook for the Observability Labs article "How to catch a Kubernetes node pressure event before it takes down your pods" (elastic/elastic-labs-blogs#2209).
It checks the EDOT node metrics and conditions, creates a per-node
low_meananomaly detection job, the anomaly detection rule, an ES|QL headroom rule and the two[Kubernetes OTel]pressure rules, then reads the anomaly records and alerts, finds the pod whose memory changed, lists the evictions, measures how early the anomaly alert opened, imports the timeline dashboard, and cleans up. The kind lab underk8s/provides the cluster with a soft eviction threshold, the EDOT Helm override, the NGINX service, two stress pods and a k6 probe.Requires Elasticsearch and Kibana 9.5+ on Elastic Cloud Hosted with machine learning enabled, and Docker, kind, kubectl, Helm and k6.