This deprecated feature is being removed in 9.0, so the telemetry is
no longer needed.
The usage action is retained to support mixed v8/v9 clusters, with
annotations to remove in V10. But it is no longer registered in
`XPackUsageFeatureAction.ALL` and so the usage data is no longer
reported by `GET _xpack/usage`, and if invoked it always returns a
count of 0.
ES-9736 # comment Removed the telemetry in https://github.com/elastic/elasticsearch/pull/119890
This ensures the usage API docs tests are passing again. We achieve this
by: 1. ignoring the contents of `inference.models` because the models
might not yet have been initialized and 2. adding missing fields to the
`logsdb` usage.
This PR adds telemetry for logsdb. However, this change only tracks the
count of indices using logsdb and those that use synthetic source.
Additional stats, such as shard, indexing, and search stats, will be
added in a follow-up, as they require reaching out to data nodes.
This removes the undocumented `META FUNCTIONS` command that emits
descriptions for all functions. This shouldn't be used because we never
told anyone about it. I'd have preferred if we'd have explicitly
documented it as no public or if we'd have left it snapshot-only. But
sometimes you make a mistake. I'm hopeful no one is relying on it. It
was never reliable and not public.....
Adds a default configuration for the ELSER model. The config uses
adaptive allocations to automatically scale. Min number of allocations
is set to 1 for this PR, a follow up with change that to 0 and enable
scale from 0.
This end point is always visible in the GET API.
```
GET _inference
{
"endpoints": [
{
"inference_id": ".elser-2",
"task_type": "sparse_embedding",
"service": "elser",
"service_settings": {
"num_threads": 1,
"model_id": ".elser_model_2",
"adaptive_allocations": {
"enabled": true,
"min_number_of_allocations": 1,
"max_number_of_allocations": 8
}
},
"task_settings": {}
}
]
}
```
The default configuration can be used against without any prior setup.
If the model is not downloaded it is automatically downloaded. If it is
not deployed it is deployed
```
POST _inference/.elser-2
{
"input": "Automagically deploy and infer"
}
...
{
"sparse_embedding": [
{
"is_truncated": false,
"embedding": {
"##fer": 2.2107008,
"deployment": 2.1624098,
"deploy": 2.144009,
"auto": 1.9384763,
```
### Follow up tasks - [ ] Add default config for the E5 text embedding
model - [ ] Select platform specific version - [ ] Scale from 0 - [ ]
Chunking settings - What happens when the end point is deleted, can it
be deleted? - Can the default config be modified - chunking settings for
example? Probably not
Currently, the data stream lifecycle telemetry has the following
structure:
```
{
....
"data_lifecycle" : {
"available": true,
"enabled": true,
"count": 0,
"default_rollover_used": true,
"retention": {
"minimum_millis": 0,
"maximum_millis": 0,
"average_millis": 0.0
}
}....
```
In the snippet above you can see that we track:
- The amount of data streams managed by the data stream lifecycle by `count`
- If the default rollover has been overwritten by `default_rollover_used`
- The min, max and average of the `data_retention` configured on a data stream level.
In this PR we propose the following extention:
```
....
"data_lifecycle" : {
"available": true,
"enabled": true,
"count": 0,
"default_rollover_used": true,
"effective_retention": { #https://github.com/elastic/dev/issues/2537
"retained_data_streams": 5,
"minimum_millis": 0, # Only if retained data streams > 1
"maximum_millis": 0,
"average_millis": 0.0
},
"data_retention": {
"configured_data_streams": 5,
"minimum_millis": 0, # Only if retained data streams > 1
"maximum_millis": 0,
"average_millis": 0.0
},
"global_retention": {
"default": {
"defined": true/false,
"affected_data_streams": 0,
"millis": 0
},
"max": {
"defined": true/false,
"affected_data_streams": 0,
"millis": 0
}
}
```
With this extension we are tracking:
- The amount of data streams managed by the data stream lifecycle by `count`
- If the default rollover has been overwritten by `default_rollover_used`
- The min, max and average of the `data_retention` configured on a data stream level and the number of data streams that have it configured. We add the min, max and avg only if there are data streams with data retention configuration to avoid messing with the stats in a dashboard.
- The min, max and average of the `effective_retention` and the number of data streams that are retained. We add the min, max and avg only if there are retained data streams to avoid messing with the stats in a dashboard.
- Global retention stats, if they are defined, if the number of the affected data streams and the actual value.
The above metrics allow us to answer questions like:
- How many data streams are affected by global retention.
- How big is the difference between the longest data retention compared to max global retention.
- How much does the effective retention diverging from the data retention, this will show the impact of the global retention.
This change adds `number_of_rollup_jobs` and `number_of_rollup_indices`
to `rollup` usage. The former indicates the number of active rollup
jobs running and the latter indicated the number of rollup indices
(which could be the result of previous rollup jobs).
* Remove `es-test-dir` book-scoped variable
* Remove `plugins-examples-dir` book-scoped variable
* Remove `:dependencies-dir:` and `:xes-repo-dir:` book-scoped variables
- In `index.asciidoc`, two variables (`:dependencies-dir:` and `:xes-repo-dir:`) were removed.
- In `sql/index.asciidoc`, the `:sql-tests:` path was updated to fuller path
- In `esql/index.asciidoc`, the `:esql-tests:` path was updated idem
* Replace `es-repo-dir` with `es-ref-dir`
* Move `:include-xpack: true` to few files that use it, remove from index.asciidoc
* Add inference counts by NLP model to the machine learning usage stats.
* Update docs/changelog/101915.yaml
* Add inference_counts_by_model to yamlRestTest.
* Strip leading dot from internal model IDs.
* Add last access and task type to the stats by model.
* Change stats_by_model for map to list
* Simplify code.
* Fix style
**Problem:**
For historical reasons, source files for the Elasticsearch Guide's security, watcher, and Logstash API docs are housed in the `x-pack/docs` directory. This can confuse new contributors who expect Elasticsearch Guide docs to be located in `docs/reference`.
**Solution:**
- Move the security, watcher, and Logstash API doc source files to the `docs/reference` directory
- Update doc snippet tests to use security
Rel: https://github.com/elastic/platform-docs-team/issues/208
This adds a `data_lifecycle` section to the _xpack/usage API, giving basic information about data lifecycles in the cluster. The data looks something like:
```
"data_lifecycle": {
"available": true,
"enabled": true,
"lifecycle": {
"count": 1,
"default_rollover_used": true,
"retention": {
"minimum_millis": 360000,
"maximum_millis": 360000,
"average_millis": 360000.0
}
}
}
```
The previous fix (#95565) didn't work since the section was misplaced.
Note that this test runs only on snapshot build so I tested manually and the failure is now related to remote_clusters section missing.
Closes#95603
Every node (post `8.7`) collects stats from every health-api request it receives. We extend the `_xpack/usage` endpoint to expose these stats. When a node receives the request it will fan out to collect data from all other nodes, merge them and expose them. If the cluster is not fully upgraded, it will signal it with the `available` flag set to`false`.
This deprecates estimated_heap_memory_usage_bytes on model put and replaces it with model_size_bytes.
On GET, only model_size_bytes is returned unless v7 rest-api compatibility is requested.
For the ml/info API, only model_size_bytes is returned
A forward-port of: #80545
Removes `testenv` annotations and related code. These annotations originally let you skip x-pack snippet tests in the docs. However, that's no longer possible.
Relates to #79309, #31619
We have already decided not to have xpack usage for field mappers
(see #53076). As mappings stats of all fields is already tracked
in cluster stats.
Moreover xpack usage for vector field is a quite expensive operation
(see #74974).
This removes xpack actions for vector field.
* Warn users if security is implicitly disabled
Elasticsearch has security features implicitly disabled by default for
Basic and Trial licenses, unless explicitly set in the configuration
file.
This may be good for onboarding, but it also lead to unintended insecure
clusters.
This change introduces clear warnings when security features are
implicitly disabled.
- a warning header in each REST response if security is implicitly
disabled;
- a log message during cluster boot.
Runtime fields usage is currently reported as part of the xpack feature usage API. Now that runtime fields are part of server, their corresponding stats can be moved to be part of the ordinary mapping stats exposed by the cluster stats API.
This adds additional statistics into the usage API for data frame analytics
and trained models.
For data frame analytics the added stats are:
- count of jobs by analysis type
- stats for peak_usage_bytes
For trained models the added stats are:
- counts of: total, prepackaged, other (not created by data frame analytics)
- counts by analysis type based on the inference config
- stats for estimated heap usage
- stats for estimated number of operations
* Fixing Painless tests.
* Update runtime field context to fix test cases.
* Remove watcher logging from usage API and replace test.
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
This commit adds the `data_frozen` node role as part of the formalization of data tiers. It also
adds the `"frozen"` phase to ILM, currently allowing the same actions as the existing cold phase.
The frozen phase is intended to be used for data even less frequently searched than the cold phase,
and will eventually be loosely tied to data using partial searchable snapshots (as oppposed to full
searchable snapshots in the cold phase).
Relates to #60848
Adds a multi_terms aggregation support. The multi terms aggregation works
very similarly to the terms aggregation but supports multiple terms. The goal
of this PR is to add the basic functionality so it is not optimized at the
moment. It will be done in follow up PRs.
Closes#65623
* Adds datetime as a date, which is necessary in setup.
* Updating field context example.
* Fixing sample data, updating context example, and updating runtime example.
* Updating field context and changing runtime field to use seats data.
* Update filter context to use the seats data.
* Updating min-should-match context to use seats data.
* Replacing last mentions of TEST[skip].
* Update usage with watcher response for build error.
* Updating usage API again for watcher.
* Third time's a charm for fixing test cases.
* Adding specific test replacement for watcher logging total.
* Change actors to keyword based on review feedback.
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
