Kibana 8.16.2

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The 8.16.2 release includes the following enhancements and bug fixes.

Enhancements

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In this release, we’ve introduced an image based on the hardened Wolfi image to provide additional security to our self-managed customers, and improve our supply chain security posture. Wolfi-based images require Docker version 20.10.10 or higher.

Bug fixes

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Alerting
  • Fixes Slack API connectors not displayed under Slack connector when adding new connector to rule (#202315).
Dashboards
  • Prevents resetting panel to undefined or empty last saved state (#203158).
Data ingestion and Fleet
  • Allows to create integration policy with no agent policies (#201051).
Elastic Observability solution
  • Preserves kuery filters when switching between Universal Profiling pages in new solution navigation (#203545).
  • Fixes error when opening rule flyout (#202386).
  • Handles ops genie as default connector (#201923).
Elastic Search solution
  • Adds ML as required plugin to Search Assistant (#204009).
  • Fixes web crawler name inconsistencies (#202738).
Elastic Security solution
For the Elastic Security 8.16.2 release information, refer to Elastic Security Solution Release Notes.
Kibana platform
  • Adds search as a term for elasticsearch solution_type (#201688).
  • Adds a11y connector improvements (#201590).
  • Fixes issue with generating short url when copying share link (#201475).
Kibana security
  • Fixes error with opening a point in time query for session deletion by now accounting for partial results (#203413).
  • Adds functionality to restrict unsupported log formats (#202994).
  • Adds functionality to restrict and reject CEF logs in Automatic Import and redirect to CEF integration instead (#201792).
  • Removes fields with @ from the script processor (#201548).
Lens & Visualizations
  • Fixes point visibility regression in TSVB (#202358).
Machine Learning
  • Trained Models: Fixes spaces sync to retrieve 10000 models (#202712).
  • Trained Models: Shows deployment stats for unallocated deployments (#202005).
  • Trained Models: Fixes start deployment with ML autoscaling and 0 active nodes (#201256).
  • Trained Models: Fixes NaN in a progress bar during the download task initialization (#201221).
  • Single Metric Viewer embeddable: Fixes continuous job refetch when errors are encountered (#199726).