Changes:
- Reworks the ILM tutorial to focus on the Elastic Agent and a built-in ILM policy
- Updates several screenshots in the docs for the new ILM UI
Co-authored-by: debadair <debadair@elastic.co>
This fixes the manage_follow_index builtin privilege so that it can be used
for managing data streams in a follower cluster. In order to successfully
unfollow a data stream the promote data stream and rollover APIs need to be
executed. (This is additional to the close and unfollow APIs).
* [DOCS] Updated data streams list screenshots and delete functionality description
* Update docs/reference/data-streams/set-up-a-data-stream.asciidoc
Co-authored-by: James Rodewig <40268737+jrodewig@users.noreply.github.com>
* Update set-up-a-data-stream.asciidoc
Co-authored-by: James Rodewig <40268737+jrodewig@users.noreply.github.com>
When a data stream is being auto followed then a rollover in a local cluster can break auto following,
if the local cluster performs a rollover then it creates a new write index and if then later the remote
cluster rolls over as well then that new write index can't be replicated, because it has the same name
as in the write index in the local cluster, which was created earlier.
If a data stream is managed by ccr, then the local cluster should not do a rollover for those data streams.
The data stream should be rolled over in the remote cluster and that change should replicate to the local
cluster. Performing a rollover in the local cluster is an operation that the data stream support in ccr should
perform.
To protect against rolling over a replicated data stream, this PR adds a replicate field to DataStream class.
The rollover api will fail with an error in case a data stream is being rolled over and the targeted data stream is
a replicated data stream. When the put follow api creates a data stream in the local cluster then the replicate flag
is set to true. There should be a way to turn a replicated data stream into a regular data stream when for example
during disaster recovery. The newly added api in this pr (promote data stream api) is doing that. After a replicated
data stream is promoted to a regular data stream then the local data stream can be rolled over, so that the new
write index is no longer a follower index. Also if the put follow api is attempting to update this data stream
(for example to attempt to resume auto following) then that with fail, because the data stream is no longer a
replicated data stream.
Today with time based indices behind an alias, the is_write_index property isn't replicated from remote cluster
to the local cluster, so when attempting to rollover the alias in the local cluster the rollover fails, because the
alias doesn't have a write index. The added replicated field in the DataStream class and added validation
achieve the same kind of protection, but in a more robust way.
A followup from #61993.
* Add "synthetics-*-*" templates for synthetics fleet data
For the Elastic Agent we currently have `logs` and `metrics`, however, synthetic data doesn't belong
with those and thus we should have a place for it to live. This would be data reported from
heartbeat and under the 'monitoring' category.
This commit adds a composable index template for `synthetics-*-*` indices similar to the work in
#56709 and #57629.
Resolves#61665
Adds an important admonition for the built-in `metrics-*-*` and `logs-*-*` index
templates.
Updates several put index template snippets to include a priority.
Uses `my-data-stream` in place of `logs` for data stream examples.
This provides a more intuitive experience for users that copy/paste
their own values into snippets.
Removes the `@timestamp` field mapping from several data stream index
template snippets.
With #59317, the `@timestamp` field defaults to a `date` field data type
for data streams.
This makes the data_stream timestamp field specification optional when
defining a composable template.
When there isn't one specified it will default to `@timestamp`.
This adds a low precendece mapping for the `@timestamp` field with
type `date`.
This will aid with the bootstrapping of data streams as a timestamp
mapping can be omitted when nanos precision is not needed.
