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Your window into the Elastic Stack
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* Adds helper to normalize legacy ML rule field to an array This will be used on read of rules, to normalize legacy rules while avoiding an explicit migration. * Fix our detection-specific ML search function Luckily this was just a translation layer to our anomaly call, and the underlying functions already accepted an array of strings. * WIP: Run rules against multiple ML Job IDs We don't yet support creation of rules with multiple job ids, either on the API or the UI, but when we do they will work. Note: the logic was previously to generate an error if the underlying job was not running, but to still query and generate alerts. Extending that logic to multiple jobs: if any are not running, we generate an error but continue querying and generating alerts. * WIP: updating ml rule schemas to support multiple job IDs * Simplify normalization method We don't care about null or empty string values here; those were holdovers from copying the logic of normalizeThreshold and don't apply to this situation. * Move normalized types to separate file to fix circular dependency Our use of NonEmptyArray within common/schemas seemed to be causing the above; this fixes it for now. * Normalize ML job_ids param at the API layer Previous changes to the base types already covered the majority of routes; this updates the miscellaneous helpers that don't leverage those shared utilities. At the DB level, the forthcoming migration will ensure that we always have "normalized" job IDs as an array. * Count stopped ML Jobs as partial failure during ML Rule execution Since we continue to query anomalies and potentially generate alerts, a "failure" status is no longer the most accurate for this situation. * Update 7.13 alerts migration to allow multi-job ML Rules This ensures that we can assume string[] for this field during rule execution. * Display N job statuses on rule details * WIP: converts MLJobSelect to a multiselect Unfortunately, the SuperSelect does not allow multiselect so we need to convert this to a combobox. Luckily we can reuse most of the code here and remain relatively clean. Since all combobox options must be the same (fixed) height, we're somewhat more limited than before for displaying the rows. The truncation appears fine, but I need to figure out a way to display the full description as well. * Update client-side logic to handle an array of ML job_ids * Marginally more legible error message * Conditionally call our normalize helper only if we have a value This fixes a type error where TS could not infer that the return value would not be undefined despite knowing that the argument was never undefined. I tried some fancy conditional generic types, but that didn't work. This is more analogous to normalizeThresholdObject now, anyway. * Fix remaining type error * Clean up our ML executor tests with existing contract mocks * Update ML Executor tests with new logic We now record a partial failure instead of an error. * Add and update tests for new ML normalization logic * Add and update integration tests for ML Rules Ensures that dealing with legacy job formats continues to work in the API. * Fix a type error These params can no longer be strings. * Update ML cypress test to create a rule with 2 ML jobs If we can create a rule with 2 jobs, we should also be able to create a rule with 1 job. * Remove unused constant * Persist a partial failure message written by a rule executor We added the result.warning field as a way to indicate that a partial failure was written to the rule, but neglected to account for that in the main rule execution code, which caused a success status to immediately overwrite the partial failure if the rule execution did not otherwise fail/short-circuit. |
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Kibana
Kibana is your window into the Elastic Stack. Specifically, it's a browser-based analytics and search dashboard for Elasticsearch.
- Getting Started
- Documentation
- Version Compatibility with Elasticsearch
- Questions? Problems? Suggestions?
Getting Started
If you just want to try Kibana out, check out the Elastic Stack Getting Started Page to give it a whirl.
If you're interested in diving a bit deeper and getting a taste of Kibana's capabilities, head over to the Kibana Getting Started Page.
Using a Kibana Release
If you want to use a Kibana release in production, give it a test run, or just play around:
- Download the latest version on the Kibana Download Page.
- Learn more about Kibana's features and capabilities on the Kibana Product Page.
- We also offer a hosted version of Kibana on our Cloud Service.
Building and Running Kibana, and/or Contributing Code
You might want to build Kibana locally to contribute some code, test out the latest features, or try out an open PR:
- CONTRIBUTING.md will help you get Kibana up and running.
- If you would like to contribute code, please follow our STYLEGUIDE.md.
- For all other questions, check out the FAQ.md and wiki.
Documentation
Visit Elastic.co for the full Kibana documentation.
For information about building the documentation, see the README in elastic/docs.
Version Compatibility with Elasticsearch
Ideally, you should be running Elasticsearch and Kibana with matching version numbers. If your Elasticsearch has an older version number or a newer major number than Kibana, then Kibana will fail to run. If Elasticsearch has a newer minor or patch number than Kibana, then the Kibana Server will log a warning.
Note: The version numbers below are only examples, meant to illustrate the relationships between different types of version numbers.
| Situation | Example Kibana version | Example ES version | Outcome |
|---|---|---|---|
| Versions are the same. | 5.1.2 | 5.1.2 | 💚 OK |
| ES patch number is newer. | 5.1.2 | 5.1.5 | ⚠️ Logged warning |
| ES minor number is newer. | 5.1.2 | 5.5.0 | ⚠️ Logged warning |
| ES major number is newer. | 5.1.2 | 6.0.0 | 🚫 Fatal error |
| ES patch number is older. | 5.1.2 | 5.1.0 | ⚠️ Logged warning |
| ES minor number is older. | 5.1.2 | 5.0.0 | 🚫 Fatal error |
| ES major number is older. | 5.1.2 | 4.0.0 | 🚫 Fatal error |
Questions? Problems? Suggestions?
- If you've found a bug or want to request a feature, please create a GitHub Issue. Please check to make sure someone else hasn't already created an issue for the same topic.
- Need help using Kibana? Ask away on our Kibana Discuss Forum and a fellow community member or Elastic engineer will be glad to help you out.