reorder as suggested in review

Author: marciw

manage-data/data-store/data-streams/reindex-tsds.md

@@ -104,7 +104,7 @@ PUT _index_template/new-tsds-template
 
 ### Create the destination data stream and reindex [tsds-reindex-op]
 
-Run the reindex operation using `op_type: create` to prevent overwrites:
+Run the reindex operation:
 
 ```console
 POST /_reindex

manage-data/data-store/data-streams/time-series-data-stream-tsds.md

@@ -19,33 +19,13 @@ Before setting up a time series data stream, make sure you're familiar with gene
 
 ## When to use a time series data stream [when-to-use-tsds]
 
-Both a regular data stream and a time series data stream can store timestamped metrics data. 
+_Metrics_ consist of data point–timestamp pairs, identified by [dimension fields]() that can be used in aggregation queries. Both a regular data stream and a time series data stream can store metrics data. 
 
 Choose a time series data stream if you typically add metrics data to {{es}} in near real-time and in `@timestamp` order. For other timestamped data, such as logs or traces, use a [logs data stream](logs-data-stream.md) or [regular data stream](/manage-data/data-store/data-streams.md).
 
-### Differences from a regular data stream [differences-from-regular-data-stream]
-
-A time series data stream works like a regular data stream, with some key differences:
-
-* **Time series index mode:** The matching index template for a TSDS must include a `data_stream` object with `index.mode` set to `time_series`. This option enables most TSDS-related functionality.
-* **Required fields:** In a TSDS, each document contains:
-  * A `@timestamp` field
-  * One or more [dimension fields](#time-series-dimension), set with `time_series_dimension: true`  
-  * One or more [metric fields](#time-series-metric) (not strictly required, but typical for a TSDS)
-* **Document IDs:** Time series documents use two IDs: 
-    * An internal [`_tsid`](#tsid) metadata field, generated by {{es}} for each document in a TSDS and used for sorting and compression
-    * The document `_id`, a generated hash of the document's dimensions and `@timestamp` (custom `_id` values are not supported)
-* **Backing indices:** A TSDS uses [time-bound indices](/manage-data/data-store/data-streams/time-bound-tsds.md) to store data from the same time period in the same backing index.
-* **Dimension-based routing:** The matching index template for a TSDS must contain the `index.routing_path` index setting, which specifies dimensions for routing documents to shards.
-* **Sorting:** A TSDS uses internal [index sorting](elasticsearch://reference/elasticsearch/index-settings/sorting.md) to order shard segments by `_tsid` and `@timestamp`, for better compression. Time series data streams do not use `index.sort.*` settings.
-* **Synthetic source:** A TSDS uses [synthetic `_source`](elasticsearch://reference/elasticsearch/mapping-reference/mapping-source-field.md#synthetic-source), which has some [restrictions](elasticsearch://reference/elasticsearch/mapping-reference/mapping-source-field.md#synthetic-source-restrictions) and [modifications](elasticsearch://reference/elasticsearch/mapping-reference/mapping-source-field.md#synthetic-source-modifications).
+To make sure a TSDS is right for your use case, review the list of [differences from a regular data stream](#differences-from-regular-data-stream) on this page.
 
-
-## Query time series data
-
-You can use the {{esql}} [`TS` command](elasticsearch://reference/query-languages/esql/commands/ts.md) to query time series data streams. The `TS` command is optimized for time series data. It also enables the use of aggregation functions that efficiently process metrics per time series, before aggregating results.
-
-## Time series concepts [time-series]
+## Time series overview [time-series]
 
 A time series is a sequence of observations for a specific entity. Together, these observations let you track changes to the entity over time. For example, a time series can track:
 
@@ -91,7 +71,7 @@ You can also simplify dimension definitions by using [pass-through](elasticsearc
 
 #### Metrics [time-series-metric]
 
-Metrics are numeric measurements that change over time. Although metrics are not required, documents in a TSDS typically contain one or more metric fields. 
+Metrics are numeric measurements that change over time. Documents in a TSDS contain one or more metric fields. 
 
 :::{tip}
 Metrics are expected to change (even if rarely or slowly), while dimensions generally remain constant.
@@ -110,9 +90,6 @@ The valid values for `time_series_metric` are `counter` and `gauge`:
 `gauge`
 :   A metric that represents a single numeric that can arbitrarily increase or decrease. For example, a temperature or available disk space. 
 
-
-:::::
-
 #### `_tsid` metadata field [tsid]
 
 The `_tsid` is an automatically generated object containing the document’s dimensions. It's intended for internal {{es}} use, so in most cases you won't need to work with it.
@@ -122,6 +99,27 @@ The `_tsid` is an automatically generated object containing the document’s dim
 - To retrieve the value of `_tsid`, use the fields parameter in a search. The `_tsid` is not included in get document responses.
 - The format of the `_tsid` field is subject to change. 
 
+### Differences from a regular data stream [differences-from-regular-data-stream]
+
+A time series data stream works like a regular data stream, with some key differences:
+
+* **Time series index mode:** The matching index template for a TSDS must include a `data_stream` object with `index.mode` set to `time_series`. This option enables most TSDS-related functionality.
+* **Required fields:** In a TSDS, each document contains:
+  * A `@timestamp` field
+  * One or more [dimension fields](#time-series-dimension), set with `time_series_dimension: true`  
+  * One or more [metric fields](#time-series-metric) (not strictly required, but typical for a TSDS)
+* **Document IDs:** Time series documents use two IDs: 
+    * An internal [`_tsid`](#tsid) metadata field, generated by {{es}} for each document in a TSDS and used for sorting and compression
+    * The document `_id`, a generated hash of the document's dimensions and `@timestamp` (custom `_id` values are not supported)
+* **Backing indices:** A TSDS uses [time-bound indices](/manage-data/data-store/data-streams/time-bound-tsds.md) to store data from the same time period in the same backing index.
+* **Dimension-based routing:** The matching index template for a TSDS must contain the `index.routing_path` index setting, which specifies dimensions for routing documents to shards.
+* **Sorting:** A TSDS uses internal [index sorting](elasticsearch://reference/elasticsearch/index-settings/sorting.md) to order shard segments by `_tsid` and `@timestamp`, for better compression. Time series data streams do not use `index.sort.*` settings.
+* **Synthetic source:** A TSDS uses [synthetic `_source`](elasticsearch://reference/elasticsearch/mapping-reference/mapping-source-field.md#synthetic-source), which has some [restrictions](elasticsearch://reference/elasticsearch/mapping-reference/mapping-source-field.md#synthetic-source-restrictions) and [modifications](elasticsearch://reference/elasticsearch/mapping-reference/mapping-source-field.md#synthetic-source-modifications).
+
+## Query time series data
+
+You can use the {{esql}} [`TS` command](elasticsearch://reference/query-languages/esql/commands/ts.md) to query time series data streams. The `TS` command is optimized for time series data. It also enables the use of aggregation functions that efficiently process metrics per time series, before aggregating results.
+
 
 ## Next steps [tsds-whats-next]