* Add SLM support to xpack usage and info APIs
This is a backport of #48096
This adds the missing xpack usage and info information into the
`/_xpack` and `/_xpack/usage` APIs. The output now looks like:
```
GET /_xpack/usage
{
...
"slm" : {
"available" : true,
"enabled" : true,
"policy_count" : 1,
"policy_stats" : {
"retention_runs" : 0,
...
}
}
```
and
```
GET /_xpack
{
...
"features" : {
...
"slm" : {
"available" : true,
"enabled" : true
},
...
}
}
```
Relates to #43663
* Fix missing license
This adds parsing an inference model as a possible
result of the analytics process. When we do parse such a model
we persist a `TrainedModelConfig` into the inference index
that contains additional metadata derived from the running job.
which is backport merge and adds a new ingest processor, named enrich processor,
that allows document being ingested to be enriched with data from other indices.
Besides a new enrich processor, this PR adds several APIs to manage an enrich policy.
An enrich policy is in charge of making the data from other indices available to the enrich processor in an efficient manner.
Related to #32789
max_empty_searches = -1 in a datafeed update implies
max_empty_searches will be unset on the datafeed when
the update is applied. The isNoop() method needs to
take this -1 to null equivalence into account.
This change adds:
- A new option, allow_lazy_open, to anomaly detection jobs
- A new option, allow_lazy_start, to data frame analytics jobs
Both work in the same way: they allow a job to be
opened/started even if no ML node exists that can
accommodate the job immediately. In this situation
the job waits in the opening/starting state until ML
node capacity is available. (The starting state for data
frame analytics jobs is new in this change.)
Additionally, the ML nightly maintenance tasks now
creates audit warnings for ML jobs that are unassigned.
This means that jobs that cannot be assigned to an ML
node for a very long time will show a yellow warning
triangle in the UI.
A final change is that it is now possible to close a job
that is not assigned to a node without using force.
This is because previously jobs that were open but
not assigned to a node were an aberration, whereas
after this change they'll be relatively common.
This PR adds the ability to run the enrich policy execution task in the background,
returning a task id instead of waiting for the completed operation.
Currently, partial snapshots will eventually build up unless they are
manually deleted. Partial snapshots may be useful if there is not a more
recent successful snapshot, but should eventually be deleted if they are
no longer useful.
With this change, partial snapshots are deleted using the following
strategy: PARTIAL snapshots will be kept until the configured
expire_after period has passed, if present, and then be deleted. If
there is no configured expire_after in the retention policy, then they
will be deleted if there is at least one more recent successful snapshot
from this policy (as they may otherwise be useful for troubleshooting
purposes). Partial snapshots are not counted towards either min_count or
max_count.
Adds a new datafeed config option, max_empty_searches,
that tells a datafeed that has never found any data to stop
itself and close its associated job after a certain number
of real-time searches have returned no data.
Backport of #47922
This commit adds two APIs that allow to pause and resume
CCR auto-follower patterns:
// pause auto-follower
POST /_ccr/auto_follow/my_pattern/pause
// resume auto-follower
POST /_ccr/auto_follow/my_pattern/resume
The ability to pause and resume auto-follow patterns can be
useful in some situations, including the rolling upgrades of
cluster using a bi-directional cross-cluster replication scheme
(see #46665).
This commit adds a new active flag to the AutoFollowPattern
and adapts the AutoCoordinator and AutoFollower classes so
that it stops to fetch remote's cluster state when all auto-follow
patterns associate to the remote cluster are paused.
When an auto-follower is paused, remote indices that match the
pattern are just ignored: they are not added to the pattern's
followed indices uids list that is maintained in the local cluster
state. This way, when the auto-follow pattern is resumed the
indices created in the remote cluster in the meantime will be
picked up again and added as new following indices. Indices
created and then deleted in the remote cluster will be ignored
as they won't be seen at all by the auto-follower pattern at
resume time.
Backport of #47510 for 7.x
Joda was using ResolverStyle.STRICT when parsing. This means that date will be validated to be a correct year, year-of-month, day-of-month
However, we also want to make it works with Year-Of-Era as Joda used to, hence custom temporalquery.localdate in DateFormatters.from
Within DateFormatters we use the correct uuuu year instead of yyyy year of era
worth noting: if yyyy(without an era) is used in code, the parsing result will be a TemporalAccessor which will fail to be converted into LocalDate. We mostly use DateFormatters.from so this takes care of this. If possible the uuuu format should be used.
Changes the execution logic to create a new task using the execute request,
and attaches the new task to the policy runner to be updated. Also, a new
response is now returned from the execute api, which contains either the task
id of the execution, or the completed status of the run. The fields are mutually
exclusive to make it easier to discern what type of response it is.
rename internal indexes of transform plugin
- rename audit index and create an alias for accessing it, BWC: add an alias for old indexes to
keep them working, kibana UI will switch to use the read alias
- rename config index and provide BWC to read from old and new ones
* Separate SLM stop/start/status API from ILM
This separates a start/stop/status API for SLM from being tied to ILM's
operation mode. These APIs look like:
```
POST /_slm/stop
POST /_slm/start
GET /_slm/status
```
This allows administrators to have fine-grained control over preventing
periodic snapshots and deletions while performing cluster maintenance.
Relates to #43663
* Allow going from RUNNING to STOPPED
* Align with the OperationMode rules
* Fix slmStopping method
* Make OperationModeUpdateTask constructor private
* Wipe snapshots better in test
Failed snapshots will eventually build up unless they are deleted. While
failures may not take up much space, they add noise to the list of
snapshots and it's desirable to remove them when they are no longer
useful.
With this change, failed snapshots are deleted using the following
strategy: `FAILED` snapshots will be kept until the configured
`expire_after` period has passed, if present, and then be deleted. If
there is no configured `expire_after` in the retention policy, then they
will be deleted if there is at least one more recent successful snapshot
from this policy (as they may otherwise be useful for troubleshooting
purposes). Failed snapshots are not counted towards either `min_count`
or `max_count`.
When exceptions could be returned from another node, the exception
might be wrapped in a `RemoteTransportException`. In places where
we handled specific exceptions using `instanceof` we ought to unwrap
the cause first.
This commit attempts to fix this issue after searching code in the ML
plugin.
Backport of #47676
this commit introduces a geo-match enrich processor that looks up a specific
`geo_point` field in the enrich-index for all entries that have a geo_shape match field
that meets some specific relation criteria with the input field.
For example, the enrich index may contain documents with zipcodes and their respective
geo_shape. Ingesting documents with a geo_point field can be enriched with which zipcode
they associate according to which shape they are contained within.
this commit also refactors some of the MatchProcessor by moving a lot of the shared code to
AbstractEnrichProcessor.
Closes#42639.
Adds the following parameters to `outlier_detection`:
- `compute_feature_influence` (boolean): whether to compute or not
feature influence scores
- `outlier_fraction` (double): the proportion of the data set assumed
to be outlying prior to running outlier detection
- `standardization_enabled` (boolean): whether to apply standardization
to the feature values
Backport of #47600
Use case:
User with `create_doc` index privilege will be allowed to only index new documents
either via Index API or Bulk API.
There are two cases that we need to think:
- **User indexing a new document without specifying an Id.**
For this ES auto generates an Id and now ES version 7.5.0 onwards defaults to `op_type` `create` we just need to authorize on the `op_type`.
- **User indexing a new document with an Id.**
This is problematic as we do not know whether a document with Id exists or not.
If the `op_type` is `create` then we can assume the user is trying to add a document, if it exists it is going to throw an error from the index engine.
Given these both cases, we can safely authorize based on the `op_type` value. If the value is `create` then the user with `create_doc` privilege is authorized to index new documents.
In the `AuthorizationService` when authorizing a bulk request, we check the implied action.
This code changes that to append the `:op_type/index` or `:op_type/create`
to indicate the implied index action.
This commit adds support to retrieve all API keys if the authenticated
user is authorized to do so.
This removes the restriction of specifying one of the
parameters (like id, name, username and/or realm name)
when the `owner` is set to `false`.
Closes#46887
An index with an ILM policy that has a rollover action in one of the
phases was rolled over when the ILM conditions dictated regardless if
it was already rolled over (eg. manually after modifying an index
template in order to force the creation of a new index that uses the new
mappings).
This changes this behaviour and has ILM check if the index it's about to
roll has not been rolled over in the meantime.
(cherry picked from commit 37d6106feeb9f9369519117c88a9e7e30f3ac797)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This adds a default for the `slm.retention_schedule` setting, setting it
to `0 30 1 * * ?` which is 1:30am every day.
Having retention unset meant that it would never be invoked and clean up
snapshots. We determined it would be better to have a default than never
to be run. When coming to a decision, we weighed the option of an
absolute time (such as 1:30am) versus a periodic invocation (like every
12 hours). In the end we decided on the absolute time because it has
better predictability and consistency than a periodic invocation, which
would rely on when the master node were elected or restarted.
Relates to #43663
When an ML job runs the memory required can be
broken down into:
1. Memory required to load the executable code
2. Instrumented model memory
3. Other memory used by the job's main process or
ancilliary processes that is not instrumented
Previously we added a simple fixed overhead to
account for 1 and 3. This was 100MB for anomaly
detection jobs (large because of the completely
uninstrumented categorization function and
normalize process), and 20MB for data frame
analytics jobs.
However, this was an oversimplification because
the executable code only needs to be loaded once
per machine. Also the 100MB overhead for anomaly
detection jobs was probably too high in most cases
because categorization and normalization don't use
_that_ much memory.
This PR therefore changes the calculation of memory
requirements as follows:
1. A per-node overhead of 30MB for _only_ the first
job of any type to be run on a given node - this
is to account for loading the executable code
2. The established model memory (if applicable) or
model memory limit of the job
3. A per-job overhead of 10MB for anomaly detection
jobs and 5MB for data frame analytics jobs, to
account for the uninstrumented memory usage
This change will enable more jobs to be run on the
same node. It will be particularly beneficial when
there are a large number of small jobs. It will
have less of an effect when there are a small number
of large jobs.
* Remove eclipse conditionals
We used to have some meta projects with a `-test` prefix because
historically eclipse could not distinguish between test and main
source-sets and could only use a single classpath.
This is no longer the case for the past few Eclipse versions.
This PR adds the necessary configuration to correctly categorize source
folders and libraries.
With this change eclipse can import projects, and the visibility rules
are correct e.x. auto compete doesn't offer classes from test code or
`testCompile` dependencies when editing classes in `main`.
Unfortunately the cyclic dependency detection in Eclipse doesn't seem to
take the difference between test and non test source sets into account,
but since we are checking this in Gradle anyhow, it's safe to set to
`warning` in the settings. Unfortunately there is no setting to ignore
it.
This might cause problems when building since Eclipse will probably not
know the right order to build things in so more wirk might be necesarry.
* Add API to execute SLM retention on-demand (#47405)
This is a backport of #47405
This commit adds the `/_slm/_execute_retention` API endpoint. This
endpoint kicks off SLM retention and then returns immediately.
This in particular allows us to run retention without scheduling it
(for entirely manual invocation) or perform a one-off cleanup.
This commit also includes HLRC for the new API, and fixes an issue
in SLMSnapshotBlockingIntegTests where retention invoked prior to the
test completing could resurrect an index the internal test cluster
cleanup had already deleted.
Resolves#46508
Relates to #43663
* Fix AllocationRoutedStepTests.testConditionMetOnlyOneCopyAllocated
These tests were using randomly generated includes/excludes/requires for
routing, however, it was possible to generate mutually exclusive
allocation settings (about 1 out of 50,000 times for my runs).
This splits the test into three different tests, and removes the
randomization (it doesn't add anything to the testing here) to fix the
issue.
Resolves#47142
While it seemed like the PUT data frame analytics action did not
have to be a master node action as the config is stored in an index
rather than the cluster state, there are other subtle nuances which
make it worthwhile to convert it. In particular, it helps maintain
order of execution for put actions which are anyhow user driven and
are expected to have low volume.
This commit converts `TransportPutDataFrameAnalyticsAction` from
a handled transport action to a master node action.
Note this means that the action might fail in a mixed cluster
but as the API is still experimental and not widely used there will
be few moments more suitable to make this change than now.
Bulk requests currently do not allow adding "create" actions with auto-generated IDs.
This commit allows using the optype CREATE for append-only indexing operations. This is
mainly the user facing aspect of it.
Due to #47003 many clusters will have built up a
large backlog of expired results. On upgrading to
a version where that bug is fixed users could find
that the first ML daily maintenance task deletes
a very large amount of documents.
This change introduces throttling to the
delete-by-query that the ML daily maintenance uses
to delete expired results to limit it to deleting an
average 200 documents per second. (There is no
throttling for state/forecast documents as these
are expected to be lower volume.)
Additionally a rough time limit of 8 hours is applied
to the whole delete expired data action. (This is only
rough as it won't stop part way through a single
operation - it only checks the timeout between
operations.)
Relates #47103
This commit restores the model state if available in data
frame analytics jobs.
In addition, this changes the start API so that a stopped job
can be restarted. As we now store the progress in the state index
when the task is stopped, we can use it to determine what state
the job was in when it got stopped.
Note that in order to be able to distinguish between a job
that runs for the first time and another that is restarting,
we ensure reindexing progress is reported to be at least 1
for a running task.
Due to a regression bug the metadata Active Directory realm
setting is ignored (it works correctly for the LDAP realm type).
This commit redresses it.
Closes#45848
* [ML][Inference] adding .ml-inference* index and storage (#47267)
* [ML][Inference] adding .ml-inference* index and storage
* Addressing PR comments
* Allowing null definition, adding validation tests for model config
* fixing line length
* adjusting for backport
As a result of #45689 snapshot finalization started to
take significantly longer than before. This may be a
little unfortunate since it increases the likelihood
of failing to finalize after having written out all
the segment blobs.
This change parallelizes all the metadata writes that
can safely run in parallel in the finalization step to
speed the finalization step up again. Also, this will
generally speed up the snapshot process overall in case
of large number of indices.
This is also a nice to have for #46250 since we add yet
another step (deleting of old index- blobs in the shards
to the finalization.
Currently the policy config is placed directly in the json object
of the toplevel `policies` array field. For example:
```
{
"policies": [
{
"match": {
"name" : "my-policy",
"indices" : ["users"],
"match_field" : "email",
"enrich_fields" : [
"first_name",
"last_name",
"city",
"zip",
"state"
]
}
}
]
}
```
This change adds a `config` field in each policy json object:
```
{
"policies": [
{
"config": {
"match": {
"name" : "my-policy",
"indices" : ["users"],
"match_field" : "email",
"enrich_fields" : [
"first_name",
"last_name",
"city",
"zip",
"state"
]
}
}
}
]
}
```
This allows us in the future to add other information about policies
in the get policy api response.
The UI will consume this API to build an overview of all policies.
The UI may in the future include additional information about a policy
and the plan is to include that in the get policy api, so that this
information can be gathered in a single api call.
An example of the information that is likely to be added is:
* Last policy execution time
* The status of a policy (executing, executed, unexecuted)
* Information about the last failure if exists
These settings were using get raw to fallback to whether or not SSL is
enabled. Yet, we have a formal mechanism for falling back to a
setting. This commit cuts over to that formal mechanism.
Backport of #45794 to 7.x. Convert most `awaitBusy` calls to
`assertBusy`, and use asserts where possible. Follows on from #28548 by
@liketic.
There were a small number of places where it didn't make sense to me to
call `assertBusy`, so I kept the existing calls but renamed the method to
`waitUntil`. This was partly to better reflect its usage, and partly so
that anyone trying to add a new call to awaitBusy wouldn't be able to find
it.
I also didn't change the usage in `TransportStopRollupAction` as the
comments state that the local awaitBusy method is a temporary
copy-and-paste.
Other changes:
* Rework `waitForDocs` to scale its timeout. Instead of calling
`assertBusy` in a loop, work out a reasonable overall timeout and await
just once.
* Some tests failed after switching to `assertBusy` and had to be fixed.
* Correct the expect templates in AbstractUpgradeTestCase. The ES
Security team confirmed that they don't use templates any more, so
remove this from the expected templates. Also rewrite how the setup
code checks for templates, in order to give more information.
* Remove an expected ML template from XPackRestTestConstants The ML team
advised that the ML tests shouldn't be waiting for any
`.ml-notifications*` templates, since such checks should happen in the
production code instead.
* Also rework the template checking code in `XPackRestTestHelper` to give
more helpful failure messages.
* Fix issue in `DataFrameSurvivesUpgradeIT` when upgrading from < 7.4
Drop the usage of `SimpleDateFormat` and use the `DateFormatter` instead
(cherry picked from commit 7cf509a7a11ecf6c40c44c18e8f03b8e81fcd1c2)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This change also slightly modifies the stats response,
so that is can easier consumer by monitoring and other
users. (coordinators stats are now in a list instead of
a map and has an additional field for the node id)
Relates to #32789
In the current implementation, the validation of the role query
occurs at runtime when the query is being executed.
This commit adds validation for the role query when creating a role
but not for the template query as we do not have the runtime
information required for evaluating the template query (eg. authenticated user's
information). This is similar to the scripts that we
store but do not evaluate or parse if they are valid queries or not.
For validation, the query is evaluated (if not a template), parsed to build the
QueryBuilder and verify if the query type is allowed.
Closes#34252
* ILM: parse origination date from index name (#46755)
Introduce the `index.lifecycle.parse_origination_date` setting that
indicates if the origination date should be parsed from the index name.
If set to true an index which doesn't match the expected format (namely
`indexName-{dateFormat}-optional_digits` will fail before being created.
The origination date will be parsed when initialising a lifecycle for an
index and it will be set as the `index.lifecycle.origination_date` for
that index.
A user set value for `index.lifecycle.origination_date` will always
override a possible parsable date from the index name.
(cherry picked from commit c363d27f0210733dad0c307d54fa224a92ddb569)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
* Drop usage of Map.of to be java 8 compliant
* Wait for snapshot completion in SLM snapshot invocation
This changes the snapshots internally invoked by SLM to wait for
completion. This allows us to capture more snapshotting failure
scenarios.
For example, previously a snapshot would be created and then registered
as a "success", however, the snapshot may have been aborted, or it may
have had a subset of its shards fail. These cases are now handled by
inspecting the response to the `CreateSnapshotRequest` and ensuring that
there are no failures. If any failures are present, the history store
now stores the action as a failure instead of a success.
Relates to #38461 and #43663
Using arrays of objects with embedded IDs is preferred for new APIs over
using entity IDs as JSON keys. This commit changes the SLM stats API to
use the preferred format.
* [ML][Inference] Feature pre-processing objects and functions (#46777)
To support inference on pre-trained machine learning models, some basic feature encoding will be necessary. I am using a named object serialization approach so new encodings/pre-processing steps could be added in the future.
This PR lays down the ground work for 3 basic encodings:
* HotOne
* Target Mean
* Frequency
More feature encodings or pre-processings could be added in the future:
* Handling missing columns
* Standardization
* Label encoding
* etc....
* fixing compilation for namedxcontent tests
This change allows for the caller of the `saml/prepare` API to pass
a `relay_state` parameter that will then be part of the redirect
URL in the response as the `RelayState` query parameter.
The SAML IdP is required to reflect back the value of that relay
state when sending a SAML Response. The caller of the APIs can
then, when receiving the SAML Response, read and consume the value
as it see fit.
Previously, queries on the _index field were not able to specify index aliases.
This was a regression in functionality compared to the 'indices' query that was
deprecated and removed in 6.0.
Now queries on _index can specify an alias, which is resolved to the concrete
index names when we check whether an index matches. To match a remote shard
target, the pattern needs to be of the form 'cluster:index' to match the
fully-qualified index name. Index aliases can be specified in the following query
types: term, terms, prefix, and wildcard.
This commit changes the GET REST api so it will accept an optional comma
separated list of enrich policy ids. This change also modifies the
behavior of the GET API in that it will not error if it is passed a bad
enrich id anymore, but will instead just return an empty list.
This commit reuses the same state processor that is used for autodetect
to parse state output from data frame analytics jobs. We then index the
state document into the state index.
Backport of #46804
* [ML][Transforms] remove `force` flag from _start (#46414)
* [ML][Transforms] remove `force` flag from _start
* fixing expected error message
* adjusting bwc version
* Give kibana user reserved role privileges on .apm-* to create APM agent configuration index.
* fixed test to include checking all .apm-* permissions
* changed pattern from ".apm-*" to the more specific ".apm-agent-configuration"
* Write metadata during snapshot finalization after segment files to prevent outdated metadata in case of dynamic mapping updates as explained in #41581
* Keep the old behavior of writing the metadata beforehand in the case of mixed version clusters for BwC reasons
* Still overwrite the metadata in the end, so even a mixed version cluster is fixed by this change if a newer version master does the finalization
* Fixes#41581
* [ILM] Add date setting to calculate index age
Add the `index.lifecycle.origination_date` to allow users to configure a
custom date that'll be used to calculate the index age for the phase
transmissions (as opposed to the default index creation date).
This could be useful for users to create an index with an "older"
origination date when indexing old data.
Relates to #42449.
* [ILM] Don't override creation date on policy init
The initial approach we took was to override the lifecycle creation date
if the `index.lifecycle.origination_date` setting was set. This had the
disadvantage of the user not being able to update the `origination_date`
anymore once set.
This commit changes the way we makes use of the
`index.lifecycle.origination_date` setting by checking its value when
we calculate the index age (ie. at "read time") and, in case it's not
set, default to the index creation date.
* Make origination date setting index scope dynamic
* Document orignation date setting in ilm settings
(cherry picked from commit d5bd2bb77ee28c1978ab6679f941d7c02e389d32)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
Since the `IndicesSegmentsRequest` scatters to all shards for the index,
it's possible that some of the shards may fail. This adds failure
handling and logging (since this is a best-effort step in the first
place) for this case.
This commit replaces the `SearchContext` with the `QueryShardContext` when building aggregator factories. Aggregator factories are part of the `SearchContext` so they shouldn't require a `SearchContext` to create them.
The main changes here are the signatures of `AggregationBuilder#build` that now takes a `QueryShardContext` and `AggregatorFactory#createInternal` that passes the `SearchContext` to build the `Aggregator`.
Relates #46523
rename data frame transform plugin to transform:
- rename plugin data-frame to transform
- change all package names from o.e.*.dataframe.* to o.e.*.transform.*
- necessary changes to fix loading/testing
* More Efficient Ordering of Shard Upload Execution (#42791)
* Change the upload order of of snapshots to work file by file in parallel on the snapshot pool instead of merely shard-by-shard
* Inspired by #39657
* Cleanup BlobStoreRepository Abort and Failure Handling (#46208)
The enrich api returns enrich coordinator stats and
information about currently executing enrich policies.
The coordinator stats include per ingest node:
* The current number of search requests in the queue.
* The total number of outstanding remote requests that
have been executed since node startup. Each remote
request is likely to include multiple search requests.
This depends on how much search requests are in the
queue at the time when the remote request is performed.
* The number of current outstanding remote requests.
* The total number of search requests that `enrich`
processors have executed since node startup.
The current execution policies stats include:
* The name of policy that is executing
* A full blow task info object that is executing the policy.
Relates to #32789
This change adds an IndexSearcher and the node's BigArrays in the QueryShardContext.
It's a spin off of #46527 as this change is required to allow aggregation builder to solely use the
query shard context.
Relates #46523
* Add retention to Snapshot Lifecycle Management (#46407)
This commit adds retention to the existing Snapshot Lifecycle Management feature (#38461) as described in #43663. This allows a user to configure SLM to automatically delete older snapshots based on a number of criteria.
An example policy would look like:
```
PUT /_slm/policy/snapshot-every-day
{
"schedule": "0 30 2 * * ?",
"name": "<production-snap-{now/d}>",
"repository": "my-s3-repository",
"config": {
"indices": ["foo-*", "important"]
},
// Newly configured retention options
"retention": {
// Snapshots should be deleted after 14 days
"expire_after": "14d",
// Keep a maximum of thirty snapshots
"max_count": 30,
// Keep a minimum of the four most recent snapshots
"min_count": 4
}
}
```
SLM Retention is run on a scheduled configurable with the `slm.retention_schedule` setting, which supports cron expressions. Deletions are run for a configurable time bounded by the `slm.retention_duration` setting, which defaults to 1 hour.
Included in this work is a new SLM stats API endpoint available through
``` json
GET /_slm/stats
```
That returns statistics about snapshot taken and deleted, as well as successful retention runs, failures, and the time spent deleting snapshots. #45362 has more information as well as an example of the output. These stats are also included when retrieving SLM policies via the API.
* Add base framework for snapshot retention (#43605)
* Add base framework for snapshot retention
This adds a basic `SnapshotRetentionService` and `SnapshotRetentionTask`
to start as the basis for SLM's retention implementation.
Relates to #38461
* Remove extraneous 'public'
* Use a local var instead of reading class var repeatedly
* Add SnapshotRetentionConfiguration for retention configuration (#43777)
* Add SnapshotRetentionConfiguration for retention configuration
This commit adds the `SnapshotRetentionConfiguration` class and its HLRC
counterpart to encapsulate the configuration for SLM retention.
Currently only a single parameter is supported as an example (we still
need to discuss the different options we want to support and their
names) to keep the size of the PR down. It also does not yet include version serialization checks
since the original SLM branch has not yet been merged.
Relates to #43663
* Fix REST tests
* Fix more documentation
* Use Objects.equals to avoid NPE
* Put `randomSnapshotLifecyclePolicy` in only one place
* Occasionally return retention with no configuration
* Implement SnapshotRetentionTask's snapshot filtering and delet… (#44764)
* Implement SnapshotRetentionTask's snapshot filtering and deletion
This commit implements the snapshot filtering and deletion for
`SnapshotRetentionTask`. Currently only the expire-after age is used for
determining whether a snapshot is eligible for deletion.
Relates to #43663
* Fix deletes running on the wrong thread
* Handle missing or null policy in snap metadata differently
* Convert Tuple<String, List<SnapshotInfo>> to Map<String, List<SnapshotInfo>>
* Use the `OriginSettingClient` to work with security, enhance logging
* Prevent NPE in test by mocking Client
* Allow empty/missing SLM retention configuration (#45018)
Semi-related to #44465, this allows the `"retention"` configuration map
to be missing.
Relates to #43663
* Add min_count and max_count as SLM retention predicates (#44926)
This adds the configuration options for `min_count` and `max_count` as
well as the logic for determining whether a snapshot meets this criteria
to SLM's retention feature.
These options are optional and one, two, or all three can be specified
in an SLM policy.
Relates to #43663
* Time-bound deletion of snapshots in retention delete function (#45065)
* Time-bound deletion of snapshots in retention delete function
With a cluster that has a large number of snapshots, it's possible that
snapshot deletion can take a very long time (especially since deletes
currently have to happen in a serial fashion). To prevent snapshot
deletion from taking forever in a cluster and blocking other operations,
this commit adds a setting to allow configuring a maximum time to spend
deletion snapshots during retention. This dynamic setting defaults to 1
hour and is best-effort, meaning that it doesn't hard stop a deletion
at an hour mark, but ensures that once the time has passed, all
subsequent deletions are deferred until the next retention cycle.
Relates to #43663
* Wow snapshots suuuure can take a long time.
* Use a LongSupplier instead of actually sleeping
* Remove TestLogging annotation
* Remove rate limiting
* Add SLM metrics gathering and endpoint (#45362)
* Add SLM metrics gathering and endpoint
This commit adds the infrastructure to gather metrics about the different SLM actions that a cluster
takes. These actions are stored in `SnapshotLifecycleStats` and perpetuated in cluster state. The
stats stored include the number of snapshots taken, failed, deleted, the number of retention runs,
as well as per-policy counts for snapshots taken, failed, and deleted. It also includes the amount
of time spent deleting snapshots from SLM retention.
This commit also adds an endpoint for retrieving all stats (further commits will expose this in the
SLM get-policy API) that looks like:
```
GET /_slm/stats
{
"retention_runs" : 13,
"retention_failed" : 0,
"retention_timed_out" : 0,
"retention_deletion_time" : "1.4s",
"retention_deletion_time_millis" : 1404,
"policy_metrics" : {
"daily-snapshots2" : {
"snapshots_taken" : 7,
"snapshots_failed" : 0,
"snapshots_deleted" : 6,
"snapshot_deletion_failures" : 0
},
"daily-snapshots" : {
"snapshots_taken" : 12,
"snapshots_failed" : 0,
"snapshots_deleted" : 12,
"snapshot_deletion_failures" : 6
}
},
"total_snapshots_taken" : 19,
"total_snapshots_failed" : 0,
"total_snapshots_deleted" : 18,
"total_snapshot_deletion_failures" : 6
}
```
This does not yet include HLRC for this, as this commit is quite large on its own. That will be
added in a subsequent commit.
Relates to #43663
* Version qualify serialization
* Initialize counters outside constructor
* Use computeIfAbsent instead of being too verbose
* Move part of XContent generation into subclass
* Fix REST action for master merge
* Unused import
* Record history of SLM retention actions (#45513)
This commit records the deletion of snapshots by the retention component
of SLM into the SLM history index for the purposes of reviewing operations
taken by SLM and alerting.
* Retry SLM retention after currently running snapshot completes (#45802)
* Retry SLM retention after currently running snapshot completes
This commit adds a ClusterStateObserver to wait until the currently
running snapshot is complete before proceeding with snapshot deletion.
SLM retention waits for the maximum allowed deletion time for the
snapshot to complete, however, the waiting time is not factored into
the limit on actual deletions.
Relates to #43663
* Increase timeout waiting for snapshot completion
* Apply patch
From 2374316f0d.patch
* Rename test variables
* [TEST] Be less strict for stats checking
* Skip SLM retention if ILM is STOPPING or STOPPED (#45869)
This adds a check to ensure we take no action during SLM retention if
ILM is currently stopped or in the process of stopping.
Relates to #43663
* Check all actions preventing snapshot delete during retention (#45992)
* Check all actions preventing snapshot delete during retention run
Previously we only checked to see if a snapshot was currently running,
but it turns out that more things can block snapshot deletion. This
changes the check to be a check for:
- a snapshot currently running
- a deletion already in progress
- a repo cleanup in progress
- a restore currently running
This was found by CI where a third party delete in a test caused SLM
retention deletion to throw an exception.
Relates to #43663
* Add unit test for okayToDeleteSnapshots
* Fix bug where SLM retention task would be scheduled on every node
* Enhance test logging
* Ignore if snapshot is already deleted
* Missing import
* Fix SnapshotRetentionServiceTests
* Expose SLM policy stats in get SLM policy API (#45989)
This also adds support for the SLM stats endpoint to the high level rest client.
Retrieving a policy now looks like:
```json
{
"daily-snapshots" : {
"version": 1,
"modified_date": "2019-04-23T01:30:00.000Z",
"modified_date_millis": 1556048137314,
"policy" : {
"schedule": "0 30 1 * * ?",
"name": "<daily-snap-{now/d}>",
"repository": "my_repository",
"config": {
"indices": ["data-*", "important"],
"ignore_unavailable": false,
"include_global_state": false
},
"retention": {}
},
"stats": {
"snapshots_taken": 0,
"snapshots_failed": 0,
"snapshots_deleted": 0,
"snapshot_deletion_failures": 0
},
"next_execution": "2019-04-24T01:30:00.000Z",
"next_execution_millis": 1556048160000
}
}
```
Relates to #43663
* Rewrite SnapshotLifecycleIT as as ESIntegTestCase (#46356)
* Rewrite SnapshotLifecycleIT as as ESIntegTestCase
This commit splits `SnapshotLifecycleIT` into two different tests.
`SnapshotLifecycleRestIT` which includes the tests that do not require
slow repositories, and `SLMSnapshotBlockingIntegTests` which is now an
integration test using `MockRepository` to simulate a snapshot being in
progress.
Relates to #43663Resolves#46205
* Add error logging when exceptions are thrown
* Update serialization versions
* Fix type inference
* Use non-Cancellable HLRC return value
* Fix Client mocking in test
* Fix SLMSnapshotBlockingIntegTests for 7.x branch
* Update SnapshotRetentionTask for non-multi-repo snapshot retrieval
* Add serialization guards for SnapshotLifecyclePolicy
The previous transport action was a read action, which under the right
set of circumstances can execute on a coordinating node. This commit
ensures that cannot happen.
Besides a rename, this changes allows to processor to attach multiple
enrich docs to the document being ingested.
Also in order to control the maximum number of enrich docs to be
included in the document being ingested, the `max_matches` setting
is added to the enrich processor.
Relates #32789
As per #45852 comment we no longer need to log stack-traces in
SecurityTransportExceptionHandler and SecurityHttpExceptionHandler even
if trace logging is enabled.
(cherry picked from commit c99224a32d26db985053b7b36e2049036e438f97)