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@@ -160,6 +160,10 @@ POST _plugins/_ism/add/index_1
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}
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```
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```
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If you use a wildcard `*` while adding a policy to an index, the ISM plugin interprets `*` as all indices, including system indices like `.opendistro-security`, which stores users, roles, and tenants. A delete action in your policy might accidentally delete all user roles and tenants in your cluster.
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Don't use the broad `*` wildcard, and instead add a prefix, such as `my-logs*`, when specifying indices with the `_ism/add` API.
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{: .warning }
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---
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---
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@@ -12,16 +12,7 @@ If you're ingesting continuously generated time-series data such as logs, events
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- You don’t need to update older documents.
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- You don’t need to update older documents.
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- Your searches generally target the newer documents.
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- Your searches generally target the newer documents.
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A typical workflow to manage time-series data is as follows:
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A typical workflow to manage time-series data consists of setting up an alias, configuring a rollover operation, defining a write index, and creating common mapping fields in an index template. Data streams simplifies this process.
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- To split your data into an index for each day, use the rollover operation.
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- To perform searches on a virtual index name that gets expanded to the underlying indices, create an [index alias]({{site.url}}{{site.baseurl}}/opensearch/index-alias/).
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- To perform a write operation on an index alias, configure the latest index as the write index.
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- To configure new indices, extract common mappings and settings into an [index template]({{site.url}}{{site.baseurl}}/opensearch/index-templates/).
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Even after you perform all these operations, you’re still not enforcing the best practices when dealing with time-series data. For example, you can modify the indices directly. You’re able to ingest documents without a timestamp field, which might result in slower queries.
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Data streams abstract the complexity and enforce the best practices for managing time-series data.
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With data streams, you can store append-only time-series data across multiple indices with a single endpoint for ingesting and searching data. We recommend using data streams in place of index aliases for time-series data.
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With data streams, you can store append-only time-series data across multiple indices with a single endpoint for ingesting and searching data. We recommend using data streams in place of index aliases for time-series data.
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@@ -276,7 +267,7 @@ To manage data streams from OpenSearch Dashboards, open **OpenSearch Dashboards*
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You see a toggle switch for data streams that you can use to show or hide indices belonging to a data stream.
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You see a toggle switch for data streams that you can use to show or hide indices belonging to a data stream.
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When you enable this switch, you see a data stream multi-select dropdown menu that you can use for filtering data streams.
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When you enable this switch, you see a data stream multi-select dropdown menu that you can use for filtering data streams.
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You also see a data stream column that shows you the name of the parent data stream the index is contained in.
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You also see a data stream column that shows you the name of the data stream the index is contained in.
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