This commit adds telemetry for our data tier formalization. This telemetry helps determine the
topology of the cluster with regard to the content, hot, warm, & cold tiers/roles.
An example of the telemetry looks like:
```
GET /_xpack/usage?human
{
...
"data_tiers" : {
"available" : true,
"enabled" : true,
"data_warm" : {
...
},
"data_cold" : {
...
},
"data_content" : {
"node_count" : 1,
"index_count" : 6,
"total_shard_count" : 6,
"primary_shard_count" : 6,
"doc_count" : 71,
"total_size" : "59.6kb",
"total_size_bytes" : 61110,
"primary_size" : "59.6kb",
"primary_size_bytes" : 61110,
"primary_shard_size_avg" : "9.9kb",
"primary_shard_size_avg_bytes" : 10185,
"primary_shard_size_median" : "8kb",
"primary_shard_size_median_bytes" : 8254,
"primary_shard_size_mad" : "7.2kb",
"primary_shard_size_mad_bytes" : 7391
},
"data_hot" : {
...
}
}
}
```
The fields are as follows:
- node_count :: number of nodes with this tier/role
- index_count :: number of indices on this tier
- total_shard_count :: total number of shards for all nodes in this tier
- primary_shard_count :: number of primary shards for all nodes in this tier
- doc_count :: number of documents for all nodes in this tier
- total_size_bytes :: total number of bytes for all shards for all nodes in this tier
- primary_size_bytes :: number of bytes for all primary shards on all nodes in this tier
- primary_shard_size_avg_bytes :: average shard size for primary shard in this tier
- primary_shard_size_median_bytes :: median shard size for primary shard in this tier
- primary_shard_size_mad_bytes :: [median absolute deviation](https://en.wikipedia.org/wiki/Median_absolute_deviation) of shard size for primary shard in this tier
Relates to #60848
This commit adds data stream info to the `/_xpack` and `/_xpack/usage` APIs. Currently the usage is
pretty minimal, returning only the number of data streams and the number of indices currently
abstracted by a data stream:
```
...
"data_streams" : {
"available" : true,
"enabled" : true,
"data_streams" : 3,
"indices_count" : 17
}
...
```
This aggregation will perform normalizations of metrics
for a given series of data in the form of bucket values.
The aggregations supports the following normalizations
- rescale 0-1
- rescale 0-100
- percentage of sum
- mean normalization
- z-score normalization
- softmax normalization
To specify which normalization is to be used, it can be specified
in the normalize agg's `normalizer` field.
For example:
```
{
"normalize": {
"buckets_path": <>,
"normalizer": "percent"
}
}
```
Closes#51005.
Similar to what the moving function aggregation does, except merging windows of percentiles
sketches together instead of cumulatively merging final metrics
The current consensus is that we don't need info actions for smaller items like
field mappers. We can also remove the usage action since the cluster stats API
now tracks information about mappings, like what field types are defined.
