Clean up broken links

_dashboards/install/tar.md

@@ -27,4 +27,4 @@ nav_order: 30
    ./bin/opensearch-dashboards
    ```
 
-1. See the [OpenSearch Dashboards documentation]({{site.url}}{{site.baseurl}}/opensearch-dashboards/).
+1. See the [OpenSearch Dashboards documentation]({{site.url}}{{site.baseurl}}/dashboards/index/).

_im-plugin/ism/index.md

@@ -89,7 +89,6 @@ Make sure that the alias that you enter already exists. For more information abo
 
 After you attach a policy to an index, ISM creates a job that runs every 5 minutes by default to perform policy actions, check conditions, and transition the index into different states. To change the default time interval for this job, see [Settings]({{site.url}}{{site.baseurl}}/im-plugin/ism/settings/).
 
-If you want to use an OpenSearch operation to create an index with a policy already attached to it, see [create index]({{site.url}}{{site.baseurl}}/im-plugin/ism/api#create-index).
 
 ### Step 3: Manage indices
 

_monitoring-plugins/ad/index.md

@@ -13,7 +13,7 @@ An anomaly in OpenSearch is any unusual behavior change in your time-series data
 
 It can be challenging to discover anomalies using conventional methods such as creating visualizations and dashboards. You could configure an alert based on a static threshold, but this requires prior domain knowledge and isn't adaptive to data that exhibits organic growth or seasonal behavior.
 
-Anomaly detection  automatically detects anomalies in your OpenSearch data in near real-time using the Random Cut Forest (RCF) algorithm. RCF is an unsupervised machine learning algorithm that models a sketch of your incoming data stream to compute an `anomaly grade` and `confidence score` value for each incoming data point. These values are used to differentiate an anomaly from normal variations. For more information about how RCF works, see [Random Cut Forests](https://pdfs.semanticscholar.org/8bba/52e9797f2e2cc9a823dbd12514d02f29c8b9.pdf?_ga=2.56302955.1913766445.1574109076-1059151610.1574109076).
+Anomaly detection  automatically detects anomalies in your OpenSearch data in near real-time using the Random Cut Forest (RCF) algorithm. RCF is an unsupervised machine learning algorithm that models a sketch of your incoming data stream to compute an `anomaly grade` and `confidence score` value for each incoming data point. These values are used to differentiate an anomaly from normal variations. For more information about how RCF works, see [Random Cut Forests](https://api.semanticscholar.org/CorpusID:927435).
 
 You can pair the anomaly detection plugin with the [alerting plugin]({{site.url}}{{site.baseurl}}/monitoring-plugins/alerting/) to notify you as soon as an anomaly is detected.
 

_opensearch/data-streams.md

@@ -255,7 +255,7 @@ POST logs-redis/_rollover
 
 If you now perform a `GET` operation on the `logs-redis` data stream, you see that the generation ID is incremented from 1 to 2.
 
-You can also set up an [Index State Management (ISM) policy]({{site.url}}{{site.baseurl}}/ism/policies/) to automate the rollover process for the data stream.  
+You can also set up an [Index State Management (ISM) policy]({{site.url}}{{site.baseurl}}/im-plugin/ism/policies/) to automate the rollover process for the data stream.  
 The ISM policy is applied to the backing indices at the time of their creation. When you associate a policy to a data stream, it only affects the future backing indices of that data stream.
 
 You also don’t need to provide the `rollover_alias` setting, because the ISM policy infers this information from the backing index.

_opensearch/query-dsl/term.md

@@ -144,7 +144,7 @@ The search query “To be, or not to be” is analyzed and tokenized into an arr
 ...
 ```
 
-For a list of all full-text queries, see [Full-text queries]({{site.url}}{{site.baseurl}}/opensearch/full-text/).
+For a list of all full-text queries, see [Full-text queries]({{site.url}}{{site.baseurl}}/opensearch/query-dsl/full-text/).
 
 If you want to query for an exact term like “HAMLET” in the speaker field and don't need the results to be sorted by relevance scores, a term-level query is more efficient:
 

_search-plugins/sql/index.md

@@ -10,7 +10,7 @@ redirect_from:
 
 # SQL
 
-OpenSearch SQL lets you write queries in SQL rather than the [OpenSearch query domain-specific language (DSL)]({{site.url}}{{site.baseurl}}/opensearch/full-text). If you're already familiar with SQL and don't want to learn the query DSL, this feature is a great option.
+OpenSearch SQL lets you write queries in SQL rather than the [OpenSearch query domain-specific language (DSL)]({{site.url}}{{site.baseurl}}/opensearch/query-dsl/full-text). If you're already familiar with SQL and don't want to learn the query DSL, this feature is a great option.
 
 
 ## Workbench

_search-plugins/sql/sql-full-text.md

@@ -9,7 +9,7 @@ nav_order: 8
 
 Use SQL commands for full-text search. The SQL plugin supports a subset of the full-text queries available in OpenSearch.
 
-To learn about full-text queries in OpenSearch, see [Full-text queries]({{site.url}}{{site.baseurl}}/opensearch/full-text/).
+To learn about full-text queries in OpenSearch, see [Full-text queries]({{site.url}}{{site.baseurl}}/opensearch/query-dsl/full-text/).
 
 ## Match
 

_upgrade-to/docker-upgrade-to.md

@@ -8,6 +8,6 @@ nav_order: 25
 
 If you use a container orchestration system like Kubernetes (or manage your containers manually) and want to avoid downtime, think of the process not as an upgrade of each node, but as a decommissioning and replacement of each node. One by one, add OpenSearch nodes to the cluster and remove Elasticsearch OSS nodes, pointing to existing data volumes as necessary and allowing time for all indices to return to a green status prior to proceeding.
 
-If you use Docker Compose, we highly recommend that you perform what amounts to a [cluster restart upgrade]({{site.url}}{{site.baseurl}}/migrate/upgrade-migrate/). Update your cluster configuration with new images, new settings, and new environment variables, and test it. Then stop and start the cluster. This process requires downtime, but takes very few steps and lets you continue to treat the cluster as a single entity that you can reliably deploy and redeploy.
+If you use Docker Compose, we highly recommend that you perform what amounts to a [cluster restart upgrade]({{site.url}}{{site.baseurl}}/upgrade-to/upgrade-to/). Update your cluster configuration with new images, new settings, and new environment variables, and test it. Then stop and start the cluster. This process requires downtime, but takes very few steps and lets you continue to treat the cluster as a single entity that you can reliably deploy and redeploy.
 
 The most important step is to leave your data volumes intact. **Don't** run `docker-compose down -v`.

_upgrade-to/upgrade-to.md

@@ -6,7 +6,7 @@ nav_order: 15
 
 # Upgrade from Elasticsearch OSS to OpenSearch
 
-If you want to upgrade from an existing Elasticsearch OSS cluster to OpenSearch and find the [snapshot approach]({{site.url}}{{site.baseurl}}/migrate/snapshot-migrate/) unappealing, you can upgrade your existing nodes from Elasticsearch OSS to OpenSearch.
+If you want to upgrade from an existing Elasticsearch OSS cluster to OpenSearch and find the [snapshot approach]({{site.url}}{{site.baseurl}}/upgrade-to/snapshot-migrate/) unappealing, you can upgrade your existing nodes from Elasticsearch OSS to OpenSearch.
 
 If your existing cluster runs an older version of Elasticsearch OSS, the first step is to upgrade to version 6.x or 7.x. Elasticsearch OSS supports two types of upgrades: rolling and cluster restart.