OpenSearch/docs/reference/ilm/ilm-tutorial.asciidoc

[role="xpack"]
[testenv="basic"]
[[getting-started-index-lifecycle-management]]
== Tutorial: Automate rollover with {ilm-init}

++++
<titleabbrev>Automate rollover</titleabbrev>
++++

This tutorial demonstrates how to use {ilm} 
({ilm-init}) to manage indices that contain time-series data.

When you continuously index timestamped documents into {es},
you typically use a <<data-streams, data stream>> so you can periodically roll over to a
new index.
This enables you to implement a hot-warm-cold architecture to meet your performance
requirements for your newest data, control costs over time, enforce retention policies,
and still get the most out of your data.

TIP: Data streams are best suited for
<<data-streams-append-only,append-only>> use cases. If you need to frequently
update or delete existing documents across multiple indices, we recommend
using an index alias and index template instead. You can still use ILM to
manage and rollover the alias's indices. Skip to
<<manage-time-series-data-without-data-streams>>.

To automate rollover and management of a data stream with {ilm-init}, you:

. <<ilm-gs-create-policy, Create a lifecycle policy>> that defines the appropriate
phases and actions.
. <<ilm-gs-apply-policy, Create a composable template>> to create the data stream and
apply the ILM policy and the indices settings and mappings configurations for the backing
indices.
. <<ilm-gs-check-progress, Verify indices are moving through the lifecycle phases>>
as expected.

For an introduction to rolling indices, see <<index-rollover>>. 

IMPORTANT: When you enable {ilm} for {beats} or the {ls} {es} output plugin,
lifecycle policies are set up automatically.
You do not need to take any other actions.
You can modify the default policies through
{kibana-ref}/example-using-index-lifecycle-policy.html[{kib} Management]
or the {ilm-init} APIs.

[discrete]
[[ilm-gs-create-policy]]
=== Create a lifecycle policy

A lifecycle policy specifies the phases in the index lifecycle
and the actions to perform in each phase. A lifecycle can have up to four phases:
`hot`, `warm`, `cold`, and `delete`. 

You can define and manage policies through {kib} Management or with the 
<<ilm-put-lifecycle, put policy>> API.

For example, you might define a `timeseries_policy` that has two phases:
 
* A `hot` phase that defines a rollover action to specify that an index rolls over when it 
reaches either a `max_size` of 50 gigabytes or a `max_age` of 30 days.
* A `delete` phase that sets `min_age` to remove the index 90 days after rollover.
Note that this value is relative to the rollover time, not the index creation time. 

The underlying put policy request looks like this:

[source,console]
------------------------
PUT _ilm/policy/timeseries_policy
{
  "policy": {
    "phases": {
      "hot": {                      <1>
        "actions": {
          "rollover": {
            "max_size": "50GB",     <2>
            "max_age": "30d"
          }
        }
      },
      "delete": {
        "min_age": "90d",           <3>
        "actions": {
          "delete": {}              <4>
        }
      }
    }
  }
}
------------------------
<1> The `min_age` defaults to `0ms`, so new indices enter the `hot` phase immediately.
<2> Trigger the `rollover` action when either of the conditions are met.
<3> Move the index into the `delete` phase 90 days after rollover.
<4> Trigger the `delete` action when the index enters the delete phase.

You can also invoke this API directly to add lifecycle policies.

For the complete list of actions that {ilm} can perform, see <<ilm-actions>>.

[discrete]
[[ilm-gs-apply-policy]]
=== Create a composable template to create the data stream and apply the lifecycle policy

To set up a data stream, first create a composable template to specify the lifecycle policy. Because
the template is for a data stream, it must also include a `data_stream` definition.

For example, you might create a `timeseries_template` to use for a future data stream
named `timeseries`.

To enable the {ilm-init} to manage the data stream, the template configures one {ilm-init} setting:

* `index.lifecycle.name` specifies the name of the lifecycle policy to apply to the data stream.

You can use the {kib} Create template wizard to add the template.
This wizard invokes the put _index_template API to create the <<indices-templates,composable index template>>
with the options you specify.

The underlying request looks like this:

[source,console]
-----------------------
PUT _index_template/timeseries_template
{
  "index_patterns": ["timeseries"],                   <1>
  "data_stream": {
    "timestamp_field": "@timestamp"                   <2>
  },
  "template": {
    "settings": {
      "number_of_shards": 1,
      "number_of_replicas": 1,
      "index.lifecycle.name": "timeseries_policy"     <3>
    },
    "mappings": {
      "properties": {
        "@timestamp": {
          "type": "date"                              <4>
        }
      }
    }
  }
}
-----------------------
// TEST[continued]

<1> Apply the template when a document is indexed into the `timeseries` target.
<2> Identifies the timestamp field for the data source. This field must be present
in all documents indexed into the `timeseries` data stream.
<3> The name of the {ilm-init} policy used to manage the data stream.
<4> A <<date,`date`>> or <<date_nanos,`date_nanos`>> field mapping for the
timestamp field specified in the `timestamp_field` property

You can also invoke this API directly to add templates.

[discrete]
[[ilm-gs-create-the-data-stream]]
=== Create the data stream

To get things started, index a document into the name or wildcard pattern defined
in the `index_patterns` of the <<indices-templates,composable index template>>. As long
as an existing data stream, index, or index alias does not already use the name, the index
request automatically creates a corresponding data stream with a single backing index.
{es} automatically indexes the request's documents into this backing index, which also
acts as the stream's <<data-stream-write-index,write index>>.

For example, the following request creates the `timeseries` data stream and the first generation
backing index called `.ds-timeseries-000001`.

[source,console]
-----------------------
POST timeseries/_doc
{
  "message": "logged the request",
  "@timestamp": "1591890611"
}

-----------------------
// TEST[continued]

When a rollover condition in the lifecycle policy is met, the `rollover` action:

* Creates the second generation backing index, named `.ds-timeseries-000002`.
Because it is a backing index of the `timeseries` data stream, the configuration from the `timeseries_template` composable template is applied to the new index.
* As it is the latest generation index of the `timeseries` data stream, the newly created
backing index `.ds-timeseries-000002` becomes the data stream's write index.

This process repeats each time a rollover condition is met.
You can search across all of the data stream's backing indices, managed by the `timeseries_policy`,
with the `timeseries` data stream name.
Write operations are routed to the current write index. Read operations will be handled by all
backing indices.

[discrete]
[[ilm-gs-check-progress]]
=== Check lifecycle progress

To get status information for managed indices, you use the {ilm-init} explain API.
This lets you find out things like:

* What phase an index is in and when it entered that phase.
* The current action and what step is being performed.
* If any errors have occurred or progress is blocked.

For example, the following request gets information about the `timeseries` data stream's
backing indices:

[source,console]
--------------------------------------------------
GET .ds-timeseries-*/_ilm/explain
--------------------------------------------------
// TEST[continued]

The following response shows the data stream's first generation backing index is waiting for the `hot`
phase's `rollover` action.
It remains in this state and {ilm-init} continues to call `check-rollover-ready` until a rollover condition
is met.

// [[36818c6d9f434d387819c30bd9addb14]]
[source,console-result]
--------------------------------------------------
{
  "indices": {
    ".ds-timeseries-000001": {
      "index": ".ds-timeseries-000001",
      "managed": true,
      "policy": "timeseries_policy",             <1>
      "lifecycle_date_millis": 1538475653281,
      "age": "30s",                              <2>
      "phase": "hot",
      "phase_time_millis": 1538475653317,
      "action": "rollover",
      "action_time_millis": 1538475653317,
      "step": "check-rollover-ready",            <3>
      "step_time_millis": 1538475653317,
      "phase_execution": {
        "policy": "timeseries_policy",
        "phase_definition": {                    <4>
          "min_age": "0ms",
          "actions": {
            "rollover": {
              "max_size": "50gb",
              "max_age": "30d"
            }
          }
        },
        "version": 1,
        "modified_date_in_millis": 1539609701576
      }
    }
  }
}
--------------------------------------------------
// TESTRESPONSE[skip:no way to know if we will get this response immediately]

<1> The policy used to manage the index
<2> The age of the index
<3> The step {ilm-init} is performing on the index
<4> The definition of the current phase (the `hot` phase)

//////////////////////////

[source,console]
--------------------------------------------------
DELETE /_data_stream/timeseries
--------------------------------------------------
// TEST[continued]

//////////////////////////


//////////////////////////

[source,console]
--------------------------------------------------
DELETE /_index_template/timeseries_template
--------------------------------------------------
// TEST[continued]

//////////////////////////

[discrete]
[[manage-time-series-data-without-data-streams]]
=== Manage time-series data without data streams

Even though <<data-streams, data streams>> are a convenient way to scale
and manage time-series data, they are designed to be append-only. We recognise there
might be use-cases where data needs to be updated or deleted in place and the
data streams don't support delete and update requests directly,
so the index APIs would need to be used directly on the data stream's backing indices.

In these cases, you can use an index alias to manage indices containing the time-series data
and periodically roll over to a new index.

To automate rollover and management of time-series indices with {ilm-init} using an index
alias, you:

. Create a lifecycle policy that defines the appropriate phases and actions.
See <<ilm-gs-create-policy, Create a lifecycle policy>> above.
. <<ilm-gs-alias-apply-policy, Create an index template>> to apply the policy to each new index.
. <<ilm-gs-alias-bootstrap, Bootstrap an index>> as the initial write index.
. <<ilm-gs-alias-check-progress, Verify indices are moving through the lifecycle phases>>
as expected.

[discrete]
[[ilm-gs-alias-apply-policy]]
=== Create a legacy index template to apply the lifecycle policy

To automatically apply a lifecycle policy to the new write index on rollover,
specify the policy in the index template used to create new indices.

For example, you might create a `timeseries_template` that is applied to new indices
whose names match the `timeseries-*` index pattern.

To enable automatic rollover, the template configures two {ilm-init} settings:

* `index.lifecycle.name` specifies the name of the lifecycle policy to apply to new indices
that match the index pattern.
* `index.lifecycle.rollover_alias` specifies the index alias to be rolled over
when the rollover action is triggered for an index.

You can use the {kib} Create template wizard to add the template.
This wizard invokes the put template API to create the template with the options you specify.

The underlying request looks like this:

[source,console]
-----------------------
PUT _template/timeseries_template
{
  "index_patterns": ["timeseries-*"],                 <1>
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 1,
    "index.lifecycle.name": "timeseries_policy",      <2>
    "index.lifecycle.rollover_alias": "timeseries"    <3>
  }
}
-----------------------
// TEST[continued]

<1> Apply the template to a new index if its name starts with `timeseries-`.
<2> The name of the lifecycle policy to apply to each new index.
<3> The name of the alias used to reference these indices.
Required for policies that use the rollover action.

You can also invoke this API directly to add templates.


//////////////////////////

[source,console]
--------------------------------------------------
DELETE /_template/timeseries_template
--------------------------------------------------
// TEST[continued]

//////////////////////////

[discrete]
[[ilm-gs-alias-bootstrap]]
=== Bootstrap the initial time-series index with a write index alias

To get things started, you need to bootstrap an initial index and
designate it as the write index for the rollover alias specified in your index template.
The name of this index must match the template's index pattern and end with a number.
On rollover, this value is incremented to generate a name for the new index.

For example, the following request creates an index called `timeseries-000001`
and makes it the write index for the `timeseries` alias.

[source,console]
-----------------------
PUT timeseries-000001
{
  "aliases": {
    "timeseries": {
      "is_write_index": true
    }
  }
}
-----------------------
// TEST[continued]

When the rollover conditions are met, the `rollover` action:

* Creates a new index called `timeseries-000002`.
This matches the `timeseries-*` pattern, so the settings from `timeseries_template` are applied to the new index.
* Designates the new index as the write index and makes the bootstrap index read-only.

This process repeats each time rollover conditions are met.
You can search across all of the indices managed by the `timeseries_policy` with the `timeseries` alias.
Write operations are routed to the current write index.

[discrete]
[[ilm-gs-alias-check-progress]]
=== Check lifecycle progress

Retrieving the status information for managed indices is very similar to the data stream case.
See the data stream <<ilm-gs-check-progress, check progress section>> for more information.
The only difference is the indices namespace, so retrieving the progress will entail the following
api call:

[source,console]
--------------------------------------------------
GET timeseries-*/_ilm/explain
--------------------------------------------------
// TEST[continued]

//////////////////////////

[source,console]
--------------------------------------------------
DELETE /timeseries-000001
--------------------------------------------------
// TEST[continued]
//////////////////////////