diff --git a/_data-prepper/common-use-cases/codec-processor-combinations.md b/_data-prepper/common-use-cases/codec-processor-combinations.md
index 525bc704be..279c7d530b 100644
--- a/_data-prepper/common-use-cases/codec-processor-combinations.md
+++ b/_data-prepper/common-use-cases/codec-processor-combinations.md
@@ -7,7 +7,7 @@ nav_order: 10
 
 # Codec processor combinations
 
-At ingestion time, data received by the [`s3` source]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/sources/s3/) can be parsed by [codecs]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/sources/s3#codec). Codecs compresses and decompresses large data sets in a certain format before ingestion them through a Data Prepper pipeline [processor]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/processors/).
+At ingestion time, data received by the [`s3` source]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/sources/s3/) can be parsed by [codecs]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/sources/s3#codec). Codecs compresses and decompresses large data sets in a certain format before ingestion them through an OpenSearch Data Prepper pipeline [processor]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/processors/).
 
 While most codecs can be used with most processors, the following codec processor combinations can make your pipeline more efficient when used with the following input types.
 
diff --git a/_data-prepper/common-use-cases/common-use-cases.md b/_data-prepper/common-use-cases/common-use-cases.md
index 342a8fc819..adca11418b 100644
--- a/_data-prepper/common-use-cases/common-use-cases.md
+++ b/_data-prepper/common-use-cases/common-use-cases.md
@@ -9,4 +9,4 @@ redirect_from:
 
 # Common use cases
 
-You can use Data Prepper for several different purposes, including trace analytics, log analytics, Amazon S3 log analytics, and metrics ingestion.
\ No newline at end of file
+You can use OpenSearch Data Prepper for several different purposes, including trace analytics, log analytics, Amazon S3 log analytics, and metrics ingestion.
\ No newline at end of file
diff --git a/_data-prepper/common-use-cases/event-aggregation.md b/_data-prepper/common-use-cases/event-aggregation.md
index f6e2757d9a..4e1464b505 100644
--- a/_data-prepper/common-use-cases/event-aggregation.md
+++ b/_data-prepper/common-use-cases/event-aggregation.md
@@ -7,7 +7,7 @@ nav_order: 25
 
 # Event aggregation
 
-You can use Data Prepper to aggregate data from different events over a period of time. Aggregating events can help to reduce unnecessary log volume and manage use cases like multiline logs that are received as separate events. The [`aggregate` processor]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/aggregate/) is a stateful processor that groups events based on the values for a set of specified identification keys and performs a configurable action on each group.
+You can use OpenSearch Data Prepper to aggregate data from different events over a period of time. Aggregating events can help to reduce unnecessary log volume and manage use cases like multiline logs that are received as separate events. The [`aggregate` processor]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/aggregate/) is a stateful processor that groups events based on the values for a set of specified identification keys and performs a configurable action on each group.
 
 The `aggregate` processor state is stored in memory. For example, in order to combine four events into one, the processor needs to retain pieces of the first three events. The state of an aggregate group of events is kept for a configurable amount of time. Depending on your logs, the aggregate action being used, and the number of memory options in the processor configuration, the aggregation could take place over a long period of time.
 
diff --git a/_data-prepper/common-use-cases/log-analytics.md b/_data-prepper/common-use-cases/log-analytics.md
index ceb26ff5b7..242e16dfe9 100644
--- a/_data-prepper/common-use-cases/log-analytics.md
+++ b/_data-prepper/common-use-cases/log-analytics.md
@@ -7,7 +7,7 @@ nav_order: 30
 
 # Log analytics
 
-Data Prepper is an extendable, configurable, and scalable solution for log ingestion into OpenSearch and Amazon OpenSearch Service. Data Prepper supports receiving logs from [Fluent Bit](https://fluentbit.io/) through the [HTTP Source](https://github.com/opensearch-project/data-prepper/blob/main/data-prepper-plugins/http-source/README.md) and processing those logs with a [Grok Processor](https://github.com/opensearch-project/data-prepper/blob/main/data-prepper-plugins/grok-processor/README.md) before ingesting them into OpenSearch through the [OpenSearch sink](https://github.com/opensearch-project/data-prepper/blob/main/data-prepper-plugins/opensearch/README.md).
+OpenSearch Data Prepper is an extendable, configurable, and scalable solution for log ingestion into OpenSearch and Amazon OpenSearch Service. Data Prepper supports receiving logs from [Fluent Bit](https://fluentbit.io/) through the [HTTP Source](https://github.com/opensearch-project/data-prepper/blob/main/data-prepper-plugins/http-source/README.md) and processing those logs with a [Grok Processor](https://github.com/opensearch-project/data-prepper/blob/main/data-prepper-plugins/grok-processor/README.md) before ingesting them into OpenSearch through the [OpenSearch sink](https://github.com/opensearch-project/data-prepper/blob/main/data-prepper-plugins/opensearch/README.md).
 
 The following image shows all of the components used for log analytics with Fluent Bit, Data Prepper, and OpenSearch.
 
diff --git a/_data-prepper/common-use-cases/log-enrichment.md b/_data-prepper/common-use-cases/log-enrichment.md
index 0d8ce4ab7d..c09fdec603 100644
--- a/_data-prepper/common-use-cases/log-enrichment.md
+++ b/_data-prepper/common-use-cases/log-enrichment.md
@@ -7,7 +7,7 @@ nav_order: 35
 
 # Log enrichment
 
-You can perform different types of log enrichment with Data Prepper, including:
+You can perform different types of log enrichment with OpenSearch Data Prepper, including:
 
 - Filtering.
 - Extracting key-value pairs from strings.
diff --git a/_data-prepper/common-use-cases/metrics-logs.md b/_data-prepper/common-use-cases/metrics-logs.md
index 3fda8597c7..fc0518ce26 100644
--- a/_data-prepper/common-use-cases/metrics-logs.md
+++ b/_data-prepper/common-use-cases/metrics-logs.md
@@ -7,7 +7,7 @@ nav_order: 15
 
 # Deriving metrics from logs
 
-You can use Data Prepper to derive metrics from logs. 
+You can use OpenSearch Data Prepper to derive metrics from logs. 
 
 The following example pipeline receives incoming logs using the [`http` source plugin]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/sources/http-source) and the [`grok` processor]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/grok/). It then uses the [`aggregate` processor]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/aggregate/) to extract the metric bytes aggregated during a 30-second window and derives histograms from the results.
 
diff --git a/_data-prepper/common-use-cases/metrics-traces.md b/_data-prepper/common-use-cases/metrics-traces.md
index c15eaa099b..2cd0dafbb7 100644
--- a/_data-prepper/common-use-cases/metrics-traces.md
+++ b/_data-prepper/common-use-cases/metrics-traces.md
@@ -7,7 +7,7 @@ nav_order: 20
 
 # Deriving metrics from traces
 
-You can use Data Prepper to derive metrics from OpenTelemetry traces. The following example pipeline receives incoming traces and extracts a metric called `durationInNanos`, aggregated over a tumbling window of 30 seconds. It then derives a histogram from the incoming traces.
+You can use OpenSearch Data Prepper to derive metrics from OpenTelemetry traces. The following example pipeline receives incoming traces and extracts a metric called `durationInNanos`, aggregated over a tumbling window of 30 seconds. It then derives a histogram from the incoming traces.
 
 The pipeline contains the following pipelines:
 
diff --git a/_data-prepper/common-use-cases/s3-logs.md b/_data-prepper/common-use-cases/s3-logs.md
index 8d5a9ce967..2f93c1281d 100644
--- a/_data-prepper/common-use-cases/s3-logs.md
+++ b/_data-prepper/common-use-cases/s3-logs.md
@@ -7,7 +7,7 @@ nav_order: 40
 
 # S3 logs
 
-Data Prepper allows you to load logs from [Amazon Simple Storage Service](https://aws.amazon.com/s3/) (Amazon S3), including traditional logs, JSON documents, and CSV logs.
+OpenSearch Data Prepper allows you to load logs from [Amazon Simple Storage Service](https://aws.amazon.com/s3/) (Amazon S3), including traditional logs, JSON documents, and CSV logs.
 
 ## Architecture
 
diff --git a/_data-prepper/common-use-cases/sampling.md b/_data-prepper/common-use-cases/sampling.md
index 7c77e8c3f2..47bead4649 100644
--- a/_data-prepper/common-use-cases/sampling.md
+++ b/_data-prepper/common-use-cases/sampling.md
@@ -7,7 +7,7 @@ nav_order: 45
 
 # Sampling
 
-Data Prepper provides the following sampling capabilities:
+OpenSearch Data Prepper provides the following sampling capabilities:
 
 - Time sampling
 - Percentage sampling
diff --git a/_data-prepper/common-use-cases/text-processing.md b/_data-prepper/common-use-cases/text-processing.md
index 041ca63ab2..1fc81c5d98 100644
--- a/_data-prepper/common-use-cases/text-processing.md
+++ b/_data-prepper/common-use-cases/text-processing.md
@@ -7,7 +7,7 @@ nav_order: 55
 
 # Text processing
 
-Data Prepper provides text processing capabilities with the [`grok processor`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/grok/). The `grok` processor is based on the [`java-grok`](https://mvnrepository.com/artifact/io.krakens/java-grok) library and supports all compatible patterns. The `java-grok` library is built using the [`java.util.regex`](https://docs.oracle.com/javase/8/docs/api/java/util/regex/package-summary.html) regular expression library.
+OpenSearch Data Prepper provides text processing capabilities with the [`grok processor`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/grok/). The `grok` processor is based on the [`java-grok`](https://mvnrepository.com/artifact/io.krakens/java-grok) library and supports all compatible patterns. The `java-grok` library is built using the [`java.util.regex`](https://docs.oracle.com/javase/8/docs/api/java/util/regex/package-summary.html) regular expression library.
 
 You can add custom patterns to your pipelines by using the `patterns_definitions` option. When debugging custom patterns, the [Grok Debugger](https://grokdebugger.com/) can be helpful.
 
diff --git a/_data-prepper/common-use-cases/trace-analytics.md b/_data-prepper/common-use-cases/trace-analytics.md
index 1a961077fe..a91f37823c 100644
--- a/_data-prepper/common-use-cases/trace-analytics.md
+++ b/_data-prepper/common-use-cases/trace-analytics.md
@@ -7,7 +7,7 @@ nav_order: 60
 
 # Trace analytics
 
-Trace analytics allows you to collect trace data and customize a pipeline that ingests and transforms the data for use in OpenSearch. The following provides an overview of the trace analytics workflow in Data Prepper, how to configure it, and how to visualize trace data.
+Trace analytics allows you to collect trace data and customize a pipeline that ingests and transforms the data for use in OpenSearch. The following provides an overview of the trace analytics workflow in OpenSearch Data Prepper, how to configure it, and how to visualize trace data.
 
 ## Introduction
 
diff --git a/_data-prepper/getting-started.md b/_data-prepper/getting-started.md
index 624cd5fcbc..5dc90316d0 100644
--- a/_data-prepper/getting-started.md
+++ b/_data-prepper/getting-started.md
@@ -1,14 +1,14 @@
 ---
 layout: default
-title: Getting started
+title: Getting started with OpenSearch Data Prepper
 nav_order: 5
 redirect_from:
   - /clients/data-prepper/get-started/
 ---
 
-# Getting started with Data Prepper
+# Getting started with OpenSearch Data Prepper
 
-Data Prepper is an independent component, not an OpenSearch plugin, that converts data for use with OpenSearch. It's not bundled with the all-in-one OpenSearch installation packages.
+OpenSearch Data Prepper is an independent component, not an OpenSearch plugin, that converts data for use with OpenSearch. It's not bundled with the all-in-one OpenSearch installation packages.
 
 If you are migrating from Open Distro Data Prepper, see [Migrating from Open Distro]({{site.url}}{{site.baseurl}}/data-prepper/migrate-open-distro/). 
 {: .note}
diff --git a/_data-prepper/index.md b/_data-prepper/index.md
index e418aa1966..63ff2fd07c 100644
--- a/_data-prepper/index.md
+++ b/_data-prepper/index.md
@@ -1,6 +1,6 @@
 ---
 layout: default
-title: Data Prepper 
+title: OpenSearch Data Prepper 
 nav_order: 1
 has_children: false
 has_toc: false
@@ -12,9 +12,9 @@ redirect_from:
   - /data-prepper/index/
 ---
 
-# Data Prepper
+# OpenSearch Data Prepper
 
-Data Prepper is a server-side data collector capable of filtering, enriching, transforming, normalizing, and aggregating data for downstream analysis and visualization. Data Prepper is the preferred data ingestion tool for OpenSearch. It is recommended for most data ingestion use cases in OpenSearch and for processing large, complex datasets.
+OpenSearch Data Prepper is a server-side data collector capable of filtering, enriching, transforming, normalizing, and aggregating data for downstream analysis and visualization. Data Prepper is the preferred data ingestion tool for OpenSearch. It is recommended for most data ingestion use cases in OpenSearch and for processing large, complex datasets.
 
 With Data Prepper you can build custom pipelines to improve the operational view of applications. Two common use cases for Data Prepper are trace analytics and log analytics. [Trace analytics]({{site.url}}{{site.baseurl}}/data-prepper/common-use-cases/trace-analytics/) can help you visualize event flows and identify performance problems. [Log analytics]({{site.url}}{{site.baseurl}}/data-prepper/common-use-cases/log-analytics/) equips you with tools to enhance your search capabilities, conduct comprehensive analysis, and gain insights into your applications' performance and behavior.
 
@@ -74,6 +74,6 @@ In the given pipeline configuration, the `source` component reads string events
 
 ## Next steps
 
-- [Get started with Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/).
+- [Getting started with OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/).
 - [Get familiar with Data Prepper pipelines]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/pipelines/).
 - [Explore common use cases]({{site.url}}{{site.baseurl}}/data-prepper/common-use-cases/common-use-cases/). 
diff --git a/_data-prepper/managing-data-prepper/configuring-data-prepper.md b/_data-prepper/managing-data-prepper/configuring-data-prepper.md
index e42a9e9449..ab5f3aa066 100644
--- a/_data-prepper/managing-data-prepper/configuring-data-prepper.md
+++ b/_data-prepper/managing-data-prepper/configuring-data-prepper.md
@@ -1,16 +1,16 @@
 ---
 layout: default
-title: Configuring Data Prepper
-parent: Managing Data Prepper
+title: Configuring OpenSearch Data Prepper
+parent: Managing OpenSearch Data Prepper
 nav_order: 5
 redirect_from:
  - /clients/data-prepper/data-prepper-reference/
  - /monitoring-plugins/trace/data-prepper-reference/
 ---
 
-# Configuring Data Prepper
+# Configuring OpenSearch Data Prepper
 
-You can customize your Data Prepper configuration by editing the `data-prepper-config.yaml` file in your Data Prepper installation. The following configuration options are independent from pipeline configuration options. 
+You can customize your OpenSearch Data Prepper configuration by editing the `data-prepper-config.yaml` file in your Data Prepper installation. The following configuration options are independent from pipeline configuration options. 
 
 
 ## Data Prepper configuration
diff --git a/_data-prepper/managing-data-prepper/configuring-log4j.md b/_data-prepper/managing-data-prepper/configuring-log4j.md
index 175c754abf..fe256e0da5 100644
--- a/_data-prepper/managing-data-prepper/configuring-log4j.md
+++ b/_data-prepper/managing-data-prepper/configuring-log4j.md
@@ -1,13 +1,13 @@
 ---
 layout: default
 title: Configuring Log4j
-parent: Managing Data Prepper
+parent: Managing OpenSearch Data Prepper
 nav_order: 20
 ---
 
 # Configuring Log4j
 
-You can configure logging using Log4j in Data Prepper. 
+You can configure logging using Log4j in OpenSearch Data Prepper. 
 
 ## Logging 
 
diff --git a/_data-prepper/managing-data-prepper/core-apis.md b/_data-prepper/managing-data-prepper/core-apis.md
index b810c7b15e..eecc4ee73b 100644
--- a/_data-prepper/managing-data-prepper/core-apis.md
+++ b/_data-prepper/managing-data-prepper/core-apis.md
@@ -1,13 +1,13 @@
 ---
 layout: default
 title: Core APIs
-parent: Managing Data Prepper
+parent: Managing OpenSearch Data Prepper
 nav_order: 15
 ---
 
 # Core APIs
 
-All Data Prepper instances expose a server with some control APIs. By default, this server runs on port 4900. Some plugins, especially source plugins, may expose other servers that run on different ports. Configurations for these plugins are independent of the core API. For example, to shut down Data Prepper, you can run the following curl request:
+All OpenSearch Data Prepper instances expose a server with some control APIs. By default, this server runs on port 4900. Some plugins, especially source plugins, may expose other servers that run on different ports. Configurations for these plugins are independent of the core API. For example, to shut down Data Prepper, you can run the following curl request:
 
 ```
 curl -X POST http://localhost:4900/shutdown
diff --git a/_data-prepper/managing-data-prepper/extensions/extensions.md b/_data-prepper/managing-data-prepper/extensions/extensions.md
index 8cbfc602c7..80da40767e 100644
--- a/_data-prepper/managing-data-prepper/extensions/extensions.md
+++ b/_data-prepper/managing-data-prepper/extensions/extensions.md
@@ -1,14 +1,14 @@
 ---
 layout: default
 title: Extensions
-parent: Managing Data Prepper
+parent: Managing OpenSearch Data Prepper
 has_children: true
 nav_order: 18
 ---
 
 # Extensions
 
-Data Prepper extensions provide Data Prepper functionality outside of core Data Prepper pipeline components.
+OpenSearch Data Prepper extensions provide Data Prepper functionality outside of core Data Prepper pipeline components.
 Many extensions provide configuration options that give Data Prepper administrators greater flexibility over Data Prepper's functionality.
 
 Extension configurations can be configured in the `data-prepper-config.yaml` file under the `extensions:` YAML block.
diff --git a/_data-prepper/managing-data-prepper/extensions/geoip-service.md b/_data-prepper/managing-data-prepper/extensions/geoip-service.md
index 53c21a08ff..157367dce1 100644
--- a/_data-prepper/managing-data-prepper/extensions/geoip-service.md
+++ b/_data-prepper/managing-data-prepper/extensions/geoip-service.md
@@ -3,12 +3,12 @@ layout: default
 title: geoip_service
 nav_order: 5
 parent: Extensions
-grand_parent: Managing Data Prepper
+grand_parent: Managing OpenSearch Data Prepper
 ---
 
 # geoip_service
 
-The `geoip_service` extension configures all [`geoip`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/geoip) processors in Data Prepper.
+The `geoip_service` extension configures all [`geoip`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/geoip) processors in OpenSearch Data Prepper.
 
 ## Usage
 
diff --git a/_data-prepper/managing-data-prepper/managing-data-prepper.md b/_data-prepper/managing-data-prepper/managing-data-prepper.md
index ea2d1f111c..204510be24 100644
--- a/_data-prepper/managing-data-prepper/managing-data-prepper.md
+++ b/_data-prepper/managing-data-prepper/managing-data-prepper.md
@@ -1,10 +1,10 @@
 ---
 layout: default
-title: Managing Data Prepper
+title: Managing OpenSearch Data Prepper
 has_children: true
 nav_order: 20
 ---
 
-# Managing Data Prepper
+# Managing OpenSearch Data Prepper
 
-You can perform administrator functions for Data Prepper, including system configuration, interacting with core APIs, Log4j configuration, and monitoring. You can set up peer forwarding to coordinate multiple Data Prepper nodes when using stateful aggregation. 
\ No newline at end of file
+You can perform administrator functions for OpenSearch Data Prepper, including system configuration, interacting with core APIs, Log4j configuration, and monitoring. You can set up peer forwarding to coordinate multiple Data Prepper nodes when using stateful aggregation. 
\ No newline at end of file
diff --git a/_data-prepper/managing-data-prepper/monitoring.md b/_data-prepper/managing-data-prepper/monitoring.md
index 691f376b33..cb29e49a51 100644
--- a/_data-prepper/managing-data-prepper/monitoring.md
+++ b/_data-prepper/managing-data-prepper/monitoring.md
@@ -1,13 +1,13 @@
 ---
 layout: default
 title: Monitoring
-parent: Managing Data Prepper
+parent: Managing OpenSearch Data Prepper
 nav_order: 25
 ---
  
-# Monitoring Data Prepper with metrics
+# Monitoring OpenSearch Data Prepper with metrics
 
-You can monitor Data Prepper with metrics using [Micrometer](https://micrometer.io/). There are two types of metrics: JVM/system metrics and plugin metrics. [Prometheus](https://prometheus.io/) is used as the default metrics backend.
+You can monitor OpenSearch Data Prepper with metrics using [Micrometer](https://micrometer.io/). There are two types of metrics: JVM/system metrics and plugin metrics. [Prometheus](https://prometheus.io/) is used as the default metrics backend.
 
 ## JVM and system metrics
 
diff --git a/_data-prepper/managing-data-prepper/peer-forwarder.md b/_data-prepper/managing-data-prepper/peer-forwarder.md
index f6a0f9890a..9d54aef87c 100644
--- a/_data-prepper/managing-data-prepper/peer-forwarder.md
+++ b/_data-prepper/managing-data-prepper/peer-forwarder.md
@@ -2,12 +2,12 @@
 layout: default
 title: Peer forwarder
 nav_order: 12
-parent: Managing Data Prepper
+parent: Managing OpenSearch Data Prepper
 ---
 
 # Peer forwarder
 
-Peer forwarder is an HTTP service that performs peer forwarding of an `event` between Data Prepper nodes for aggregation. This HTTP service uses a hash-ring approach to aggregate events and determine which Data Prepper node it should handle on a given trace before rerouting it to that node. Currently, peer forwarder is supported by the `aggregate`, `service_map_stateful`, and `otel_traces_raw` [processors]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/processors/).
+Peer forwarder is an HTTP service that performs peer forwarding of an `event` between OpenSearch Data Prepper nodes for aggregation. This HTTP service uses a hash-ring approach to aggregate events and determine which Data Prepper node it should handle on a given trace before rerouting it to that node. Currently, peer forwarder is supported by the `aggregate`, `service_map_stateful`, and `otel_traces_raw` [processors]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/processors/).
 
 Peer Forwarder groups events based on the identification keys provided by the supported processors. For `service_map_stateful` and `otel_traces_raw`, the identification key is `traceId` by default and cannot be configured. The `aggregate` processor is configured using the `identification_keys` configuration option. From here, you can specify which keys to use for Peer Forwarder. See [Aggregate Processor page](https://github.com/opensearch-project/data-prepper/tree/main/data-prepper-plugins/aggregate-processor#identification_keys) for more information about identification keys.
 
diff --git a/_data-prepper/managing-data-prepper/source-coordination.md b/_data-prepper/managing-data-prepper/source-coordination.md
index 3c60b45280..5dc85e50a7 100644
--- a/_data-prepper/managing-data-prepper/source-coordination.md
+++ b/_data-prepper/managing-data-prepper/source-coordination.md
@@ -2,12 +2,12 @@
 layout: default
 title: Source coordination
 nav_order: 35
-parent: Managing Data Prepper
+parent: Managing OpenSearch Data Prepper
 ---
 
 # Source coordination
 
-_Source coordination_ is the concept of coordinating and distributing work between Data Prepper data sources in a multi-node environment. Some data sources, such as Amazon Kinesis or Amazon Simple Queue Service (Amazon SQS), handle coordination natively. Other data sources, such as OpenSearch, Amazon Simple Storage Service (Amazon S3), Amazon DynamoDB, and JDBC/ODBC, do not support source coordination.
+_Source coordination_ is the concept of coordinating and distributing work between OpenSearch Data Prepper data sources in a multi-node environment. Some data sources, such as Amazon Kinesis or Amazon Simple Queue Service (Amazon SQS), handle coordination natively. Other data sources, such as OpenSearch, Amazon Simple Storage Service (Amazon S3), Amazon DynamoDB, and JDBC/ODBC, do not support source coordination.
 
 Data Prepper source coordination decides which partition of work is performed by each node in the Data Prepper cluster and prevents duplicate partitions of work.
 
diff --git a/_data-prepper/migrate-open-distro.md b/_data-prepper/migrate-open-distro.md
index 8b3e7a7198..31a47c5682 100644
--- a/_data-prepper/migrate-open-distro.md
+++ b/_data-prepper/migrate-open-distro.md
@@ -23,4 +23,4 @@ In your Data Prepper Docker configuration, adjust `amazon/opendistro-for-elastic
 
 ## Next steps
 
-For more information about Data Prepper configurations, see [Getting Started with Data Prepper]({{site.url}}{{site.baseurl}}/clients/data-prepper/get-started/).
+For more information about Data Prepper configurations, see [Getting Started with OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/clients/data-prepper/get-started/).
diff --git a/_data-prepper/migrating-from-logstash-data-prepper.md b/_data-prepper/migrating-from-logstash-data-prepper.md
index 3d87f29517..13548092dc 100644
--- a/_data-prepper/migrating-from-logstash-data-prepper.md
+++ b/_data-prepper/migrating-from-logstash-data-prepper.md
@@ -9,9 +9,9 @@ redirect_from:
 
 # Migrating from Logstash
 
-You can run Data Prepper with a Logstash configuration.
+You can run OpenSearch Data Prepper with a Logstash configuration.
 
-As mentioned in [Getting started with Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/), you'll need to configure Data Prepper with a pipeline using a `pipelines.yaml` file.
+As mentioned in [Getting started with OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/), you'll need to configure Data Prepper with a pipeline using a `pipelines.yaml` file.
 
 Alternatively, if you have a Logstash configuration `logstash.conf` to configure Data Prepper instead of `pipelines.yaml`.
 
@@ -29,7 +29,7 @@ As of the Data Prepper 1.2 release, the following plugins from the Logstash conf
 
 ## Running Data Prepper with a Logstash configuration
 
-1. To install Data Prepper's Docker image, see Installing Data Prepper in [Getting Started with Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started#1-installing-data-prepper).
+1. To install Data Prepper's Docker image, see Installing Data Prepper in [Getting Started with OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started#1-installing-data-prepper).
 
 2. Run the Docker image installed in Step 1 by supplying your `logstash.conf` configuration.
 
diff --git a/_data-prepper/pipelines/configuration/buffers/buffers.md b/_data-prepper/pipelines/configuration/buffers/buffers.md
index 287825b549..0965b0acd0 100644
--- a/_data-prepper/pipelines/configuration/buffers/buffers.md
+++ b/_data-prepper/pipelines/configuration/buffers/buffers.md
@@ -8,7 +8,7 @@ nav_order: 30
 
 # Buffers
 
-The `buffer` component acts as an intermediary layer between the `source` and `sink` components in a Data Prepper pipeline. It serves as temporary storage for events, decoupling the `source` from the downstream processors and sinks. Buffers can be either in-memory or disk based. 
+The `buffer` component acts as an intermediary layer between the `source` and `sink` components in an OpenSearch Data Prepper pipeline. It serves as temporary storage for events, decoupling the `source` from the downstream processors and sinks. Buffers can be either in-memory or disk based. 
 
 If not explicitly specified in the pipeline configuration, Data Prepper uses the default `bounded_blocking` buffer, which is an in-memory queue bounded by the number of events it can store. The `bounded_blocking` buffer is a convenient option when the event volume and processing rates are manageable within the available memory constraints. 
 
diff --git a/_data-prepper/pipelines/configuration/buffers/kafka.md b/_data-prepper/pipelines/configuration/buffers/kafka.md
index 87600601b4..0152d967d7 100644
--- a/_data-prepper/pipelines/configuration/buffers/kafka.md
+++ b/_data-prepper/pipelines/configuration/buffers/kafka.md
@@ -59,7 +59,7 @@ Option | Required | Type | Description
 `name` | Yes | String | The name of the Kafka topic.
 `group_id` | Yes | String | Sets Kafka's `group.id` option.
 `workers` | No | Integer | The number of multithreaded consumers associated with each topic. Default is `2`. The maximum value is `200`.
-`encryption_key` | No | String | An Advanced Encryption Standard (AES) encryption key used to encrypt and decrypt data within Data Prepper before sending it to Kafka. This value must be plain text or encrypted using AWS Key Management Service (AWS KMS).
+`encryption_key` | No | String | An Advanced Encryption Standard (AES) encryption key used to encrypt and decrypt data within OpenSearch Data Prepper before sending it to Kafka. This value must be plain text or encrypted using AWS Key Management Service (AWS KMS).
 `kms` | No | AWS KMS key | When configured, uses an AWS KMS key to encrypt data. See [`kms`](#kms) for more information.
 `auto_commit` | No | Boolean | When `false`, the consumer offset will not be periodically committed to Kafka in the background. Default is `false`.
 `commit_interval` | No | Integer | When `auto_commit` is set to `true`, sets how often, in seconds, the consumer offsets are auto-committed to Kafka through Kafka's `auto.commit.interval.ms` option. Default is `5s`.
diff --git a/_data-prepper/pipelines/configuration/processors/aggregate.md b/_data-prepper/pipelines/configuration/processors/aggregate.md
index 38b138a996..1d0052ada6 100644
--- a/_data-prepper/pipelines/configuration/processors/aggregate.md
+++ b/_data-prepper/pipelines/configuration/processors/aggregate.md
@@ -20,7 +20,7 @@ Option | Required | Type | Description
 identification_keys | Yes | List | An unordered list by which to group events. Events with the same values as these keys are put into the same group. If an event does not contain one of the `identification_keys`, then the value of that key is considered to be equal to `null`. At least one identification_key is required (for example, `["sourceIp", "destinationIp", "port"]`).
 action | Yes | AggregateAction | The action to be performed on each group. One of the [available aggregate actions](#available-aggregate-actions) must be provided, or you can create custom aggregate actions. `remove_duplicates` and `put_all` are the available actions. For more information, see [Creating New Aggregate Actions](https://github.com/opensearch-project/data-prepper/tree/main/data-prepper-plugins/aggregate-processor#creating-new-aggregate-actions).
 group_duration | No | String | The amount of time that a group should exist before it is concluded automatically. Supports ISO_8601 notation strings ("PT20.345S", "PT15M", etc.) as well as simple notation for seconds (`"60s"`) and milliseconds (`"1500ms"`). Default value is `180s`.
-local_mode | No | Boolean | When `local_mode` is set to `true`, the aggregation is performed locally on each Data Prepper node instead of forwarding events to a specific node based on the `identification_keys` using a hash function. Default is `false`.
+local_mode | No | Boolean | When `local_mode` is set to `true`, the aggregation is performed locally on each OpenSearch Data Prepper node instead of forwarding events to a specific node based on the `identification_keys` using a hash function. Default is `false`.
 
 ## Available aggregate actions
 
@@ -31,7 +31,7 @@ Use the following aggregate actions to determine how the `aggregate` processor p
 The `remove_duplicates` action processes the first event for a group immediately and drops any events that duplicate the first event from the source. For example, when using `identification_keys: ["sourceIp", "destination_ip"]`:
 
 1. The `remove_duplicates` action processes `{ "sourceIp": "127.0.0.1", "destinationIp": "192.168.0.1", "status": 200 }`, the first event in the source.
-2. Data Prepper drops the `{ "sourceIp": "127.0.0.1", "destinationIp": "192.168.0.1", "bytes": 1000 }` event because the `sourceIp` and `destinationIp` match the first event in the source.
+2. OpenSearch Data Prepper drops the `{ "sourceIp": "127.0.0.1", "destinationIp": "192.168.0.1", "bytes": 1000 }` event because the `sourceIp` and `destinationIp` match the first event in the source.
 3. The `remove_duplicates` action processes the next event, `{ "sourceIp": "127.0.0.2", "destinationIp": "192.168.0.1", "bytes": 1000 }`. Because the `sourceIp` is different from the first event of the group, Data Prepper creates a new group based on the event.
 
 ### put_all
diff --git a/_data-prepper/pipelines/configuration/processors/anomaly-detector.md b/_data-prepper/pipelines/configuration/processors/anomaly-detector.md
index ba574bdf7d..3fae80cb3f 100644
--- a/_data-prepper/pipelines/configuration/processors/anomaly-detector.md
+++ b/_data-prepper/pipelines/configuration/processors/anomaly-detector.md
@@ -35,7 +35,7 @@ The random cut forest (RCF) ML algorithm is an unsupervised algorithm for detect
 | :--- | :--- |
 | `random_cut_forest` | Processes events using the RCF ML algorithm to detect anomalies. | 
 
-RCF is an unsupervised ML algorithm for detecting anomalous data points within a dataset. Data Prepper uses RCF to detect anomalies in data by passing the values of the configured key to RCF. For example, when an event with a latency value of 11.5 is sent, the following anomaly event is generated:
+RCF is an unsupervised ML algorithm for detecting anomalous data points within a dataset. OpenSearch Data Prepper uses RCF to detect anomalies in data by passing the values of the configured key to RCF. For example, when an event with a latency value of 11.5 is sent, the following anomaly event is generated:
 
 
  ```json
diff --git a/_data-prepper/pipelines/configuration/processors/aws-lambda.md b/_data-prepper/pipelines/configuration/processors/aws-lambda.md
index bd167996a1..0ef9dfd7d7 100644
--- a/_data-prepper/pipelines/configuration/processors/aws-lambda.md
+++ b/_data-prepper/pipelines/configuration/processors/aws-lambda.md
@@ -6,9 +6,9 @@ grand_parent: Pipelines
 nav_order: 10
 ---
 
-# aws_lambda integration for Data Prepper
+# aws_lambda integration for OpenSearch Data Prepper
 
-The [AWS Lambda](https://aws.amazon.com/lambda/) integration allows developers to use serverless computing capabilities within their Data Prepper pipelines for flexible event processing and data routing.
+The [AWS Lambda](https://aws.amazon.com/lambda/) integration allows developers to use serverless computing capabilities within their OpenSearch Data Prepper pipelines for flexible event processing and data routing.
 
 ## AWS Lambda processor configuration
 
diff --git a/_data-prepper/pipelines/configuration/processors/convert-entry-type.md b/_data-prepper/pipelines/configuration/processors/convert-entry-type.md
index c2c46260ed..cc707832ad 100644
--- a/_data-prepper/pipelines/configuration/processors/convert-entry-type.md
+++ b/_data-prepper/pipelines/configuration/processors/convert-entry-type.md
@@ -47,7 +47,7 @@ type-conv-pipeline:
 ```
 {% include copy.html %}
 
-Next, create a log file named `logs_json.log` and replace the `path` in the file source of your `pipeline.yaml` file with that filepath. For more information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
+Next, create a log file named `logs_json.log` and replace the `path` in the file source of your `pipeline.yaml` file with that filepath. For more information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
 
 For example, before you run the `convert_entry_type` processor, if the `logs_json.log` file contains the following event record:
 
diff --git a/_data-prepper/pipelines/configuration/processors/csv.md b/_data-prepper/pipelines/configuration/processors/csv.md
index e386db4bf4..d640b19eb3 100644
--- a/_data-prepper/pipelines/configuration/processors/csv.md
+++ b/_data-prepper/pipelines/configuration/processors/csv.md
@@ -113,4 +113,4 @@ The `csv` processor includes the following custom metrics.
 
 The `csv` processor includes the following counter metrics:
 
-* `csvInvalidEvents`: The number of invalid events, usually caused by an unclosed quotation mark in the event itself. Data Prepper throws an exception when an invalid event is parsed. 
+* `csvInvalidEvents`: The number of invalid events, usually caused by an unclosed quotation mark in the event itself. OpenSearch Data Prepper throws an exception when an invalid event is parsed. 
diff --git a/_data-prepper/pipelines/configuration/processors/delete-entries.md b/_data-prepper/pipelines/configuration/processors/delete-entries.md
index e7c022c6a7..f30bccae23 100644
--- a/_data-prepper/pipelines/configuration/processors/delete-entries.md
+++ b/_data-prepper/pipelines/configuration/processors/delete-entries.md
@@ -41,7 +41,7 @@ pipeline:
 ```
 {% include copy.html %}
 
-Next, create a log file named `logs_json.log` and replace the `path` in the file source of your `pipeline.yaml` file with that filepath. For more information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper).
+Next, create a log file named `logs_json.log` and replace the `path` in the file source of your `pipeline.yaml` file with that filepath. For more information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper).
 
 For example, before you run the `delete_entries` processor, if the `logs_json.log` file contains the following event record:
 
diff --git a/_data-prepper/pipelines/configuration/processors/drop-events.md b/_data-prepper/pipelines/configuration/processors/drop-events.md
index 1f601c9743..eba3d0a8fb 100644
--- a/_data-prepper/pipelines/configuration/processors/drop-events.md
+++ b/_data-prepper/pipelines/configuration/processors/drop-events.md
@@ -13,7 +13,7 @@ The `drop_events` processor drops all the events that are passed into it. The fo
 
 Option | Required | Type | Description
 :--- | :--- | :--- | :---
-drop_when | Yes | String | Accepts a Data Prepper expression string following the [Data Prepper Expression Syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). Configuring `drop_events` with `drop_when: true` drops all the events received.
+drop_when | Yes | String | Accepts an OpenSearch Data Prepper expression string following the [expression syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). Configuring `drop_events` with `drop_when: true` drops all the events received.
 handle_failed_events | No | Enum | Specifies how exceptions are handled when an exception occurs while evaluating an event. Default value is `drop`, which drops the event so that it is not sent to OpenSearch. Available options are `drop`, `drop_silently`, `skip`, and `skip_silently`. For more information, see [handle_failed_events](https://github.com/opensearch-project/data-prepper/tree/main/data-prepper-plugins/drop-events-processor#handle_failed_events).
 
 <!---## Configuration
diff --git a/_data-prepper/pipelines/configuration/processors/flatten.md b/_data-prepper/pipelines/configuration/processors/flatten.md
index 43793c2b83..0a64995286 100644
--- a/_data-prepper/pipelines/configuration/processors/flatten.md
+++ b/_data-prepper/pipelines/configuration/processors/flatten.md
@@ -26,7 +26,7 @@ Option | Required | Type | Description
 
 ## Usage
 
-The following examples show how the `flatten` processor can be used in Data Prepper pipelines.
+The following examples show how the `flatten` processor can be used in OpenSearch Data Prepper pipelines.
 
 ### Minimum configuration
 
diff --git a/_data-prepper/pipelines/configuration/processors/geoip.md b/_data-prepper/pipelines/configuration/processors/geoip.md
index d0b6bd1cbb..eaedd06269 100644
--- a/_data-prepper/pipelines/configuration/processors/geoip.md
+++ b/_data-prepper/pipelines/configuration/processors/geoip.md
@@ -9,7 +9,7 @@ nav_order: 49
 # geoip
 
 The `geoip` processor enriches events with geographic information extracted from IP addresses contained in the events.
-By default, Data Prepper uses the [MaxMind GeoLite2](https://dev.maxmind.com/geoip/geolite2-free-geolocation-data) geolocation database.
+By default, OpenSearch Data Prepper uses the [MaxMind GeoLite2](https://dev.maxmind.com/geoip/geolite2-free-geolocation-data) geolocation database.
 Data Prepper administrators can configure the databases using the [`geoip_service`]({{site.url}}{{site.baseurl}}/data-prepper/managing-data-prepper/extensions/geoip-service/) extension configuration.
 
 ## Usage
diff --git a/_data-prepper/pipelines/configuration/processors/mutate-event.md b/_data-prepper/pipelines/configuration/processors/mutate-event.md
index ff2da6b527..139ea95ac8 100644
--- a/_data-prepper/pipelines/configuration/processors/mutate-event.md
+++ b/_data-prepper/pipelines/configuration/processors/mutate-event.md
@@ -8,7 +8,7 @@ nav_order: 65
 
 # Mutate event processors
 
-Mutate event processors allow you to modify events in Data Prepper. The following processors are available:
+Mutate event processors allow you to modify events in OpenSearch Data Prepper. The following processors are available:
 
 * [add_entries]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/add-entries/) allows you to add entries to an event.
 * [convert_entry_type]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/processors/convert-entry-type/) allows you to convert value types in an event.
diff --git a/_data-prepper/pipelines/configuration/processors/mutate-string.md b/_data-prepper/pipelines/configuration/processors/mutate-string.md
index 48f6423676..b84e63ea61 100644
--- a/_data-prepper/pipelines/configuration/processors/mutate-string.md
+++ b/_data-prepper/pipelines/configuration/processors/mutate-string.md
@@ -53,9 +53,9 @@ pipeline:
 ```
 {% include copy.html %}
 
-Next, create a log file named `logs_json.log`. After that, replace the `path` of the file source in your `pipeline.yaml` file with your file path. For more detailed information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
+Next, create a log file named `logs_json.log`. After that, replace the `path` of the file source in your `pipeline.yaml` file with your file path. For more detailed information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
 
-Before you run Data Prepper, the source appears in the following format:
+Before you run OpenSearch Data Prepper, the source appears in the following format:
 
 ```json
 {"message": "ab:cd:ab:cd"}
@@ -105,7 +105,7 @@ pipeline:
 ```
 {% include copy.html %}
 
-Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with your file path. For more detailed information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
+Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with your file path. For more detailed information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
 
 Before you run Data Prepper, the source appears in the following format:
 
@@ -150,7 +150,7 @@ pipeline:
 ```
 {% include copy.html %}
 
-Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with the correct file path. For more detailed information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
+Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with the correct file path. For more detailed information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
 
 Before you run Data Prepper, the source appears in the following format:
 
@@ -195,7 +195,7 @@ pipeline:
 ```
 {% include copy.html %}
 
-Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with the correct file path. For more detailed information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
+Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with the correct file path. For more detailed information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
 
 Before you run Data Prepper, the source appears in the following format:
 
@@ -241,7 +241,7 @@ pipeline:
 ```
 {% include copy.html %}
 
-Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with the correct file path. For more detailed information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
+Next, create a log file named `logs_json.log`. After that, replace the `path` in the file source of your `pipeline.yaml` file with the correct file path. For more detailed information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper). 
 
 Before you run Data Prepper, the source appears in the following format:
 
diff --git a/_data-prepper/pipelines/configuration/processors/otel-metrics.md b/_data-prepper/pipelines/configuration/processors/otel-metrics.md
index 6fc82f5deb..38c3a825c6 100644
--- a/_data-prepper/pipelines/configuration/processors/otel-metrics.md
+++ b/_data-prepper/pipelines/configuration/processors/otel-metrics.md
@@ -141,7 +141,7 @@ The following `JSON` file is a more detailed form of OpenTelemetry representatio
 
 The `exponential_histogram_max_allowed_scale` parameter defines the maximum allowed scale for an exponential histogram. If you increase this parameter, you will increase potential memory consumption. See the [OpenTelemetry specifications](https://github.com/open-telemetry/opentelemetry-proto/blob/main/opentelemetry/proto/metrics/v1/metrics.proto) for more information on exponential histograms and their computational complexity.
 
-All exponential histograms that have a scale that is above the configured parameter (by default, a value of `10`) are discarded and logged with an error level. You can check the log that Data Prepper creates to see the `ERROR` log message.
+All exponential histograms that have a scale that is above the configured parameter (by default, a value of `10`) are discarded and logged with an error level. You can check the log that OpenSearch Data Prepper creates to see the `ERROR` log message.
 
 The absolute scale value is used for comparison, so a scale of `-11` that is treated equally to `11` exceeds the configured value of `10` and can be discarded.
 {: .note}
diff --git a/_data-prepper/pipelines/configuration/processors/otel-traces.md b/_data-prepper/pipelines/configuration/processors/otel-traces.md
index 6d26a5aca8..4d8d6cc5a1 100644
--- a/_data-prepper/pipelines/configuration/processors/otel-traces.md
+++ b/_data-prepper/pipelines/configuration/processors/otel-traces.md
@@ -8,7 +8,7 @@ nav_order: 75
 
 # otel_trace
 
-The `otel_trace` processor completes trace-group-related fields in all incoming Data Prepper span records by state caching the root span information for each `traceId`. 
+The `otel_trace` processor completes trace-group-related fields in all incoming OpenSearch Data Prepper span records by state caching the root span information for each `traceId`. 
 
 ## Parameters
 
diff --git a/_data-prepper/pipelines/configuration/processors/parse-ion.md b/_data-prepper/pipelines/configuration/processors/parse-ion.md
index 8360eaa296..38de7a86eb 100644
--- a/_data-prepper/pipelines/configuration/processors/parse-ion.md
+++ b/_data-prepper/pipelines/configuration/processors/parse-ion.md
@@ -26,7 +26,7 @@ This table is autogenerated. Do not edit it.
 | `source` | No | String | The field in the `event` that is parsed. Default value is `message`. |
 | `destination` | No | String | The destination field of the parsed JSON. Defaults to the root of the `event`. Cannot be `""`, `/`, or any white-space-only `string` because these are not valid `event` fields. |
 | `pointer` | No | String | A JSON pointer to the field to be parsed. There is no `pointer` by default, meaning that the entire `source` is parsed. The `pointer` can access JSON array indexes as well. If the JSON pointer is invalid, then the entire `source` data is parsed into the outgoing `event`. If the key that is pointed to already exists in the `event` and the `destination` is the root, then the pointer uses the entire path of the key. |
-| `parse_when` | No | String | Specifies under which conditions the processor should perform parsing. Default is no condition. Accepts a Data Prepper expression string following the [Expression syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). |
+| `parse_when` | No | String | Specifies under which conditions the processor should perform parsing. Default is no condition. Accepts an OpenSearch Data Prepper expression string following the [expression syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). |
 | `overwrite_if_destination_exists` | No | Boolean | Overwrites the destination if set to `true`. Set to `false` to prevent changing a destination value that exists. Defaults is `true`. |
 | `delete_source` | No | Boolean | If set to `true`, then the source field is deleted. Defaults is `false`. |
 | `tags_on_failure` | No | String | A list of strings specifying the tags to be set in the event that the processor fails or an unknown exception occurs during parsing.
diff --git a/_data-prepper/pipelines/configuration/processors/parse-json.md b/_data-prepper/pipelines/configuration/processors/parse-json.md
index 894d5dba42..2b654451f2 100644
--- a/_data-prepper/pipelines/configuration/processors/parse-json.md
+++ b/_data-prepper/pipelines/configuration/processors/parse-json.md
@@ -27,7 +27,7 @@ This table is autogenerated. Do not edit it.
 | `source` | No | String | The field in the `event` that will be parsed. Default value is `message`. |
 | `destination` | No | String | The destination field of the parsed JSON. Defaults to the root of the `event`. Cannot be `""`, `/`, or any white-space-only `string` because these are not valid `event` fields. |
 | `pointer` | No | String | A JSON pointer to the field to be parsed. There is no `pointer` by default, meaning the entire `source` is parsed. The `pointer` can access JSON array indexes as well. If the JSON pointer is invalid then the entire `source` data is parsed into the outgoing `event`. If the key that is pointed to already exists in the `event` and the `destination` is the root, then the pointer uses the entire path of the key. |
-| `parse_when` | No | String | Specifies under which conditions the processor should perform parsing. Default is no condition. Accepts a Data Prepper expression string following the [Expression syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). |
+| `parse_when` | No | String | Specifies under which conditions the processor should perform parsing. Default is no condition. Accepts an OpenSearch Data Prepper expression string following the [expression syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). |
 | `overwrite_if_destination_exists` | No | Boolean | Overwrites the destination if set to `true`. Set to `false` to prevent changing a destination value that exists. Defaults to `true`. |
 | `delete_source` | No | Boolean | If set to `true` then this will delete the source field. Defaults to `false`. |
 | `tags_on_failure` | No | String | A list of strings specifying the tags to be set in the event that the processor fails or an unknown exception occurs during parsing.
diff --git a/_data-prepper/pipelines/configuration/processors/parse-xml.md b/_data-prepper/pipelines/configuration/processors/parse-xml.md
index c8c9f3eebf..6908877074 100644
--- a/_data-prepper/pipelines/configuration/processors/parse-xml.md
+++ b/_data-prepper/pipelines/configuration/processors/parse-xml.md
@@ -26,7 +26,7 @@ This table is autogenerated. Do not edit it.
 | `source` | No | String | Specifies which `event` field to parse. |
 | `destination` | No | String | The destination field of the parsed XML. Defaults to the root of the `event`. Cannot be `""`, `/`, or any white-space-only string because these are not valid `event` fields. |
 | `pointer` | No | String | A JSON pointer to the field to be parsed. The value is null by default, meaning that the entire `source` is parsed. The `pointer` can access JSON array indexes as well. If the JSON pointer is invalid, then the entire `source` data is parsed into the outgoing `event` object. If the key that is pointed to already exists in the `event` object and the `destination` is the root, then the pointer uses the entire path of the key. |
-| `parse_when` | No | String | Specifies under what conditions the processor should perform parsing. Default is no condition. Accepts a Data Prepper expression string following the [Data Prepper Expression Syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). |
+| `parse_when` | No | String | Specifies under what conditions the processor should perform parsing. Default is no condition. Accepts an OpenSearch Data Prepper expression string following the [expression syntax]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/expression-syntax/). |
 | `overwrite_if_destination_exists` | No | Boolean | Overwrites the destination if set to `true`. Set to `false` to prevent changing a destination value that exists. Defaults to `true`. |
 | `delete_source` | No | Boolean | If set to `true` then this will delete the source field. Defaults to `false`. |
 | `tags_on_failure` | No | String | A list of strings specifying the tags to be set in the event that the processor fails or an unknown exception occurs during parsing.
diff --git a/_data-prepper/pipelines/configuration/processors/processors.md b/_data-prepper/pipelines/configuration/processors/processors.md
index 1fa7120551..a5d9e315f1 100644
--- a/_data-prepper/pipelines/configuration/processors/processors.md
+++ b/_data-prepper/pipelines/configuration/processors/processors.md
@@ -8,7 +8,7 @@ nav_order: 35
 
 # Processors
 
-Processors are components within a Data Prepper pipeline that enable you to filter, transform, and enrich events using your desired format before publishing records to the `sink` component. If no `processor` is defined in the pipeline configuration, then the events are published in the format specified by the `source` component. You can incorporate multiple processors within a single pipeline, and they are executed sequentially as defined in the pipeline.
+Processors are components within an OpenSearch Data Prepper pipeline that enable you to filter, transform, and enrich events using your desired format before publishing records to the `sink` component. If no `processor` is defined in the pipeline configuration, then the events are published in the format specified by the `source` component. You can incorporate multiple processors within a single pipeline, and they are executed sequentially as defined in the pipeline.
 
 Prior to Data Prepper 1.3, these components were named *preppers*. In Data Prepper 1.3, the term *prepper* was deprecated in favor of *processor*. In Data Prepper 2.0, the term *prepper* was removed.
 {: .note }
diff --git a/_data-prepper/pipelines/configuration/processors/rename-keys.md b/_data-prepper/pipelines/configuration/processors/rename-keys.md
index f57b4e509f..a2f1711ebf 100644
--- a/_data-prepper/pipelines/configuration/processors/rename-keys.md
+++ b/_data-prepper/pipelines/configuration/processors/rename-keys.md
@@ -44,7 +44,7 @@ pipeline:
 {% include copy.html %}
 
 
-Next, create a log file named `logs_json.log` and replace the `path` in the file source of your `pipeline.yaml` file with that filepath. For more information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper).
+Next, create a log file named `logs_json.log` and replace the `path` in the file source of your `pipeline.yaml` file with that filepath. For more information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper).
 
 For example, before you run the `rename_keys` processor, if the `logs_json.log` file contains the following event record:
 
diff --git a/_data-prepper/pipelines/configuration/processors/routes.md b/_data-prepper/pipelines/configuration/processors/routes.md
index eb45153756..89399f3f1a 100644
--- a/_data-prepper/pipelines/configuration/processors/routes.md
+++ b/_data-prepper/pipelines/configuration/processors/routes.md
@@ -8,7 +8,7 @@ nav_order: 90
 
 # Routes
 
-Routes define conditions that can be used in sinks for conditional routing. Routes are specified at the same level as processors and sinks under the name `route` and consist of a list of key-value pairs, where the key is the name of a route and the value is a Data Prepper expression representing the routing condition.
+Routes define conditions that can be used in sinks for conditional routing. Routes are specified at the same level as processors and sinks under the name `route` and consist of a list of key-value pairs, where the key is the name of a route and the value is an OpenSearch Data Prepper expression representing the routing condition.
 
 <!---## Configuration
 
diff --git a/_data-prepper/pipelines/configuration/processors/select-entries.md b/_data-prepper/pipelines/configuration/processors/select-entries.md
index 49fac39f4b..7566b2cb4c 100644
--- a/_data-prepper/pipelines/configuration/processors/select-entries.md
+++ b/_data-prepper/pipelines/configuration/processors/select-entries.md
@@ -8,7 +8,7 @@ nav_order: 59
 
 # select_entries
 
-The `select_entries` processor selects entries from a Data Prepper event.
+The `select_entries` processor selects entries from an OpenSearch Data Prepper event.
 Only the selected entries remain in the processed event and while all other entries are removed. However, the processor does not remove any events from the Data Prepper pipeline.
 
 ## Configuration
diff --git a/_data-prepper/pipelines/configuration/processors/trace-peer-forwarder.md b/_data-prepper/pipelines/configuration/processors/trace-peer-forwarder.md
index a73295b8c8..2665b985f7 100644
--- a/_data-prepper/pipelines/configuration/processors/trace-peer-forwarder.md
+++ b/_data-prepper/pipelines/configuration/processors/trace-peer-forwarder.md
@@ -14,7 +14,7 @@ You should use `trace_peer_forwarder` for Trace Analytics pipelines when you hav
 
 ## Usage
 
-To get started with `trace_peer_forwarder`, first configure [peer forwarder]({{site.url}}{{site.baseurl}}/data-prepper/managing-data-prepper/peer-forwarder/). Then create a `pipeline.yaml` file and specify `trace peer forwarder` as the processor. You can configure `peer forwarder` in your `data-prepper-config.yaml` file. For more detailed information, see [Configuring Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper).
+To get started with `trace_peer_forwarder`, first configure [peer forwarder]({{site.url}}{{site.baseurl}}/data-prepper/managing-data-prepper/peer-forwarder/). Then create a `pipeline.yaml` file and specify `trace peer forwarder` as the processor. You can configure `peer forwarder` in your `data-prepper-config.yaml` file. For more detailed information, see [Configuring OpenSearch Data Prepper]({{site.url}}{{site.baseurl}}/data-prepper/getting-started/#2-configuring-data-prepper).
 
 See the following example `pipeline.yaml` file: 
 
diff --git a/_data-prepper/pipelines/configuration/processors/translate.md b/_data-prepper/pipelines/configuration/processors/translate.md
index d29aa5894c..2da970d843 100644
--- a/_data-prepper/pipelines/configuration/processors/translate.md
+++ b/_data-prepper/pipelines/configuration/processors/translate.md
@@ -42,7 +42,7 @@ Then create the following file named `logs_json.log` and replace the `path` in t
 The `translate` processor configuration in `pipeline.yaml` retrieves the `source` value from the event data and compares it against the keys specified under the `targets`. 
 When a match is found, the processor places the corresponding mapped value into the `target` key provided in the configuration.
 
-When you run Data Prepper with the previous `pipeline.yaml` file, you should receive the following output:
+When you run OpenSearch Data Prepper with the previous `pipeline.yaml` file, you should receive the following output:
 
 ```json
 {
diff --git a/_data-prepper/pipelines/configuration/sinks/aws-lambda.md b/_data-prepper/pipelines/configuration/sinks/aws-lambda.md
index d8c00bdb16..5fc6e7a8bf 100644
--- a/_data-prepper/pipelines/configuration/sinks/aws-lambda.md
+++ b/_data-prepper/pipelines/configuration/sinks/aws-lambda.md
@@ -7,9 +7,9 @@ nav_order: 10
 ---
 
 ----------------------------------------------------------------------------------------
-# `aws_lambda` sink for Data Prepper
+# `aws_lambda` sink for OpenSearch Data Prepper
 
-This page explains how to configure and use [AWS Lambda](https://aws.amazon.com/lambda/) with Data Prepper, enabling Lambda functions to serve as both processors and sinks.
+This page explains how to configure and use [AWS Lambda](https://aws.amazon.com/lambda/) with OpenSearch Data Prepper, enabling Lambda functions to serve as both processors and sinks.
 
 ## `aws_lambda` sink
 
diff --git a/_data-prepper/pipelines/configuration/sinks/opensearch.md b/_data-prepper/pipelines/configuration/sinks/opensearch.md
index b1c32f0005..67209ea5b9 100644
--- a/_data-prepper/pipelines/configuration/sinks/opensearch.md
+++ b/_data-prepper/pipelines/configuration/sinks/opensearch.md
@@ -58,7 +58,7 @@ Option | Required | Type | Description
 `password` | No | String | The password for HTTP basic authentication.
 `aws` | No | AWS  | The [AWS](#aws) configuration. 
 [max_retries](#configure-max_retries) | No | Integer | The maximum number of times that the `opensearch` sink should try to push data to the OpenSearch server before considering it to be a failure. Defaults to `Integer.MAX_VALUE`. When not provided, the sink will try to push data to the OpenSearch server indefinitely and exponential backoff will increase the waiting time before a retry.
-`aws_sigv4` | No | Boolean | **Deprecated in Data Prepper 2.7.** Default is `false`. Whether to use AWS Identity and Access Management (IAM) signing to connect to an Amazon OpenSearch Service domain. For your access key, secret key, and optional session token, Data Prepper uses the default credential chain (environment variables, Java system properties, `~/.aws/credential`). 
+`aws_sigv4` | No | Boolean | **Deprecated in Data Prepper 2.7.** Default is `false`. Whether to use AWS Identity and Access Management (IAM) signing to connect to an Amazon OpenSearch Service domain. For your access key, secret key, and optional session token, OpenSearch Data Prepper uses the default credential chain (environment variables, Java system properties, `~/.aws/credential`). 
 `aws_region` | No | String | **Deprecated in Data Prepper 2.7.** The AWS Region (for example, `"us-east-1"`) for the domain when you are connecting to Amazon OpenSearch Service.
 `aws_sts_role_arn` | No | String | **Deprecated in Data Prepper 2.7.** The IAM role that the plugin uses to sign requests sent to Amazon OpenSearch Service. If this information is not provided, then the plugin uses the default credentials.
 `socket_timeout` | No | Integer | The timeout value, in milliseconds, when waiting for data to be returned (the maximum period of inactivity between two consecutive data packets). A timeout value of `0` is interpreted as an infinite timeout. If this timeout value is negative or not set, then the underlying Apache HttpClient will rely on operating system settings to manage socket timeouts.
diff --git a/_data-prepper/pipelines/configuration/sinks/s3.md b/_data-prepper/pipelines/configuration/sinks/s3.md
index 6bae749d38..43de4dc895 100644
--- a/_data-prepper/pipelines/configuration/sinks/s3.md
+++ b/_data-prepper/pipelines/configuration/sinks/s3.md
@@ -8,7 +8,7 @@ nav_order: 55
 
 # s3
 
-The `s3` sink saves and writes batches of Data Prepper events to Amazon Simple Storage Service (Amazon S3) objects. The configured `codec` determines how the `s3` sink serializes the data into Amazon S3.
+The `s3` sink saves and writes batches of OpenSearch Data Prepper events to Amazon Simple Storage Service (Amazon S3) objects. The configured `codec` determines how the `s3` sink serializes the data into Amazon S3.
 
 The `s3` sink uses the following format when batching events:
 
diff --git a/_data-prepper/pipelines/configuration/sinks/sinks.md b/_data-prepper/pipelines/configuration/sinks/sinks.md
index 51bf3b1c9c..cad70af9c7 100644
--- a/_data-prepper/pipelines/configuration/sinks/sinks.md
+++ b/_data-prepper/pipelines/configuration/sinks/sinks.md
@@ -8,7 +8,7 @@ nav_order: 25
 
 # Sinks
 
-A `sink` is an output component that specifies the destination(s) to which a Data Prepper pipeline publishes events. Sink destinations can be services like OpenSearch, Amazon Simple Storage Service (Amazon S3), or even another Data Prepper pipeline, enabling chaining of multiple pipelines. The sink component has the following configurable options that you can use to customize the destination type.
+A `sink` is an output component that specifies the destination(s) to which an OpenSearch Data Prepper pipeline publishes events. Sink destinations can be services like OpenSearch, Amazon Simple Storage Service (Amazon S3), or even another Data Prepper pipeline, enabling chaining of multiple pipelines. The sink component has the following configurable options that you can use to customize the destination type.
 
 ## Configuration options
 
diff --git a/_data-prepper/pipelines/configuration/sources/documentdb.md b/_data-prepper/pipelines/configuration/sources/documentdb.md
index d3dd31edcb..5eaebcfd5a 100644
--- a/_data-prepper/pipelines/configuration/sources/documentdb.md
+++ b/_data-prepper/pipelines/configuration/sources/documentdb.md
@@ -12,7 +12,7 @@ The `documentdb` source reads documents from [Amazon DocumentDB](https://aws.ama
 It can read historical data from an export and keep up to date on the data using Amazon DocumentDB [change streams](https://docs.aws.amazon.com/documentdb/latest/developerguide/change_streams.html).
 
 The `documentdb` source reads data from Amazon DocumentDB and puts that data into an [Amazon Simple Storage Service (Amazon S3)](https://aws.amazon.com/s3/) bucket.
-Then, other Data Prepper workers read from the S3 bucket to process data.
+Then, other OpenSearch Data Prepper workers read from the S3 bucket to process data.
 
 ## Usage
 The following example pipeline uses the `documentdb` source:
diff --git a/_data-prepper/pipelines/configuration/sources/http.md b/_data-prepper/pipelines/configuration/sources/http.md
index 574f49e289..452398603d 100644
--- a/_data-prepper/pipelines/configuration/sources/http.md
+++ b/_data-prepper/pipelines/configuration/sources/http.md
@@ -16,7 +16,7 @@ Option | Required | Type | Description
 :--- | :--- | :--- | :---
 port | No | Integer | The port that the source is running on. Default value is `2021`. Valid options are between `0` and `65535`.
 health_check_service | No | Boolean | Enables the health check service on the `/health` endpoint on the defined port. Default value is `false`.
-unauthenticated_health_check | No | Boolean | Determines whether or not authentication is required on the health check endpoint. Data Prepper ignores this option if no authentication is defined. Default value is `false`.
+unauthenticated_health_check | No | Boolean | Determines whether or not authentication is required on the health check endpoint. OpenSearch Data Prepper ignores this option if no authentication is defined. Default value is `false`.
 request_timeout | No | Integer | The request timeout, in milliseconds. Default value is `10000`.
 thread_count | No | Integer | The number of threads to keep in the ScheduledThreadPool. Default value is `200`.
 max_connection_count | No | Integer | The maximum allowed number of open connections. Default value is `500`.
diff --git a/_data-prepper/pipelines/configuration/sources/kafka.md b/_data-prepper/pipelines/configuration/sources/kafka.md
index ecd7c7eaa0..7bdb548cb4 100644
--- a/_data-prepper/pipelines/configuration/sources/kafka.md
+++ b/_data-prepper/pipelines/configuration/sources/kafka.md
@@ -8,7 +8,7 @@ nav_order: 40
 
 # kafka
 
-You can use the Apache Kafka source (`kafka`) in Data Prepper to read records from one or more Kafka [topics](https://kafka.apache.org/intro#intro_concepts_and_terms). These records hold events that your Data Prepper pipeline can ingest. The `kafka` source uses Kafka's [Consumer API](https://kafka.apache.org/documentation/#consumerapi) to consume messages from the Kafka broker, which then creates Data Prepper events for further processing by the Data Prepper pipeline.
+You can use the Apache Kafka source (`kafka`) in OpenSearch Data Prepper to read records from one or more Kafka [topics](https://kafka.apache.org/intro#intro_concepts_and_terms). These records hold events that your Data Prepper pipeline can ingest. The `kafka` source uses Kafka's [Consumer API](https://kafka.apache.org/documentation/#consumerapi) to consume messages from the Kafka broker, which then creates Data Prepper events for further processing by the Data Prepper pipeline.
 
 ## Usage
 
diff --git a/_data-prepper/pipelines/configuration/sources/kinesis.md b/_data-prepper/pipelines/configuration/sources/kinesis.md
index 659ed2afe1..48f7baad4f 100644
--- a/_data-prepper/pipelines/configuration/sources/kinesis.md
+++ b/_data-prepper/pipelines/configuration/sources/kinesis.md
@@ -8,7 +8,7 @@ nav_order: 45
 
 # kinesis
 
-You can use the Data Prepper `kinesis` source to ingest records from one or more [Amazon Kinesis Data Streams](https://aws.amazon.com/kinesis/data-streams/).
+You can use the OpenSearch Data Prepper `kinesis` source to ingest records from one or more [Amazon Kinesis Data Streams](https://aws.amazon.com/kinesis/data-streams/).
 
 ## Usage
 
diff --git a/_data-prepper/pipelines/configuration/sources/opensearch.md b/_data-prepper/pipelines/configuration/sources/opensearch.md
index 1ee2237575..248e6251d0 100644
--- a/_data-prepper/pipelines/configuration/sources/opensearch.md
+++ b/_data-prepper/pipelines/configuration/sources/opensearch.md
@@ -84,7 +84,7 @@ The `opensearch` source can be configured with Amazon OpenSearch Serverless by s
 
 ## Using metadata
 
-When the `opensource` source constructs Data Prepper events from documents in the cluster, the document index is stored in the EventMetadata with an `opensearch-index` key, and the document_id is stored in the `EventMetadata` with the `opensearch-document_id` as the key. This allows for conditional routing based on the index or `document_id`. The following example pipeline configuration sends events to an `opensearch` sink and uses the same index and `document_id` from the source cluster as in the destination cluster:
+When the `opensource` source constructs OpenSearch Data Prepper events from documents in the cluster, the document index is stored in the EventMetadata with an `opensearch-index` key, and the document_id is stored in the `EventMetadata` with the `opensearch-document_id` as the key. This allows for conditional routing based on the index or `document_id`. The following example pipeline configuration sends events to an `opensearch` sink and uses the same index and `document_id` from the source cluster as in the destination cluster:
 
 
 ```yaml
diff --git a/_data-prepper/pipelines/configuration/sources/otel-trace-source.md b/_data-prepper/pipelines/configuration/sources/otel-trace-source.md
index de45a5de63..c4266d5153 100644
--- a/_data-prepper/pipelines/configuration/sources/otel-trace-source.md
+++ b/_data-prepper/pipelines/configuration/sources/otel-trace-source.md
@@ -19,7 +19,7 @@ Option | Required | Type | Description
 port | No | Integer | The port that the `otel_trace_source` source runs on. Default value is `21890`.
 request_timeout | No | Integer | The request timeout, in milliseconds. Default value is `10000`.
 health_check_service | No | Boolean | Enables a gRPC health check service under `grpc.health.v1/Health/Check`. Default value is `false`.
-unauthenticated_health_check | No | Boolean | Determines whether or not authentication is required on the health check endpoint. Data Prepper ignores this option if no authentication is defined. Default value is `false`.
+unauthenticated_health_check | No | Boolean | Determines whether or not authentication is required on the health check endpoint. OpenSearch Data Prepper ignores this option if no authentication is defined. Default value is `false`.
 proto_reflection_service | No | Boolean | Enables a reflection service for Protobuf services (see [gRPC reflection](https://github.com/grpc/grpc/blob/master/doc/server-reflection.md) and [gRPC Server Reflection Tutorial](https://github.com/grpc/grpc-java/blob/master/documentation/server-reflection-tutorial.md) docs). Default value is `false`.
 unframed_requests | No | Boolean | Enable requests not framed using the gRPC wire protocol.
 thread_count | No | Integer | The number of threads to keep in the ScheduledThreadPool. Default value is `200`.
diff --git a/_data-prepper/pipelines/configuration/sources/s3.md b/_data-prepper/pipelines/configuration/sources/s3.md
index 7ca27ee500..ce3a284286 100644
--- a/_data-prepper/pipelines/configuration/sources/s3.md
+++ b/_data-prepper/pipelines/configuration/sources/s3.md
@@ -11,7 +11,7 @@ nav_order: 100
 `s3` is a source plugin that reads events from [Amazon Simple Storage Service (Amazon S3)](https://aws.amazon.com/s3/) objects. You can configure the source to either use an [Amazon Simple Queue Service (Amazon SQS)](https://aws.amazon.com/sqs/) queue or scan an S3 bucket:
 
 - To use Amazon SQS notifications, configure S3 event notifications on your S3 bucket. After Amazon SQS is configured, the `s3` source receives messages from Amazon SQS. When the SQS message indicates that an S3 object has been created, the `s3` source loads the S3 objects and then parses them using the configured [codec](#codec).
-- To use an S3 bucket, configure the `s3` source to use Amazon S3 Select instead of Data Prepper to parse S3 objects.
+- To use an S3 bucket, configure the `s3` source to use Amazon S3 Select instead of OpenSearch Data Prepper to parse S3 objects.
 
 ## IAM permissions
 
diff --git a/_data-prepper/pipelines/configuration/sources/sources.md b/_data-prepper/pipelines/configuration/sources/sources.md
index 682f215517..9da88a080e 100644
--- a/_data-prepper/pipelines/configuration/sources/sources.md
+++ b/_data-prepper/pipelines/configuration/sources/sources.md
@@ -8,6 +8,6 @@ nav_order: 110
 
 # Sources
 
-A `source` is an input component that specifies how a Data Prepper pipeline ingests events. Each pipeline has a single source that either receives events over HTTP(S) or reads from external endpoints, such as OpenTelemetry Collector or Amazon Simple Storage Service (Amazon S3). Sources have configurable options based on the event format (string, JSON, Amazon CloudWatch logs, OpenTelemtry traces). The source consumes events and passes them to the [`buffer`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/buffers/buffers/) component.
+A `source` is an input component that specifies how an OpenSearch Data Prepper pipeline ingests events. Each pipeline has a single source that either receives events over HTTP(S) or reads from external endpoints, such as OpenTelemetry Collector or Amazon Simple Storage Service (Amazon S3). Sources have configurable options based on the event format (string, JSON, Amazon CloudWatch logs, OpenTelemtry traces). The source consumes events and passes them to the [`buffer`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/configuration/buffers/buffers/) component.
 
 
diff --git a/_data-prepper/pipelines/dlq.md b/_data-prepper/pipelines/dlq.md
index ac1d868ea4..fc18e6f1e9 100644
--- a/_data-prepper/pipelines/dlq.md
+++ b/_data-prepper/pipelines/dlq.md
@@ -7,7 +7,7 @@ nav_order: 15
 
 # Dead-letter queues
 
-Data Prepper pipelines support dead-letter queues (DLQs) for offloading failed events and making them accessible for analysis.
+OpenSearch Data Prepper pipelines support dead-letter queues (DLQs) for offloading failed events and making them accessible for analysis.
 
 As of Data Prepper 2.3, only the `s3` source supports DLQs.
 
diff --git a/_data-prepper/pipelines/expression-syntax.md b/_data-prepper/pipelines/expression-syntax.md
index 07f68ee58e..a8fc968112 100644
--- a/_data-prepper/pipelines/expression-syntax.md
+++ b/_data-prepper/pipelines/expression-syntax.md
@@ -7,7 +7,7 @@ nav_order: 5
 
 # Expression syntax  
 
-Expressions provide flexibility in manipulating, filtering, and routing data. The following sections provide information about expression syntax in Data Prepper.
+Expressions provide flexibility in manipulating, filtering, and routing data. The following sections provide information about expression syntax in OpenSearch Data Prepper.
 
 ## Key terms
 
diff --git a/_data-prepper/pipelines/functions.md b/_data-prepper/pipelines/functions.md
index f0661faba4..caed78ac55 100644
--- a/_data-prepper/pipelines/functions.md
+++ b/_data-prepper/pipelines/functions.md
@@ -8,7 +8,7 @@ has_children: true
 
 # Functions
 
-Data Prepper offers a range of built-in functions that can be used within expressions to perform common data preprocessing tasks, such as calculating lengths, checking for tags, retrieving metadata, searching for substrings, checking IP address ranges, and joining list elements. These functions include the following:
+OpenSearch Data Prepper offers a range of built-in functions that can be used within expressions to perform common data preprocessing tasks, such as calculating lengths, checking for tags, retrieving metadata, searching for substrings, checking IP address ranges, and joining list elements. These functions include the following:
 
 - [`cidrContains()`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/cidrcontains/)
 - [`contains()`]({{site.url}}{{site.baseurl}}/data-prepper/pipelines/contains/)
diff --git a/_data-prepper/pipelines/has-tags.md b/_data-prepper/pipelines/has-tags.md
index d6cb498b11..8505842993 100644
--- a/_data-prepper/pipelines/has-tags.md
+++ b/_data-prepper/pipelines/has-tags.md
@@ -10,7 +10,7 @@ nav_order: 20
 
 The `hasTags()` function takes one or more string type arguments and returns `true` if all of the arguments passed are present in an event's tags. If an argument does not exist in the event's tags, then the function returns `false`. 
 
-For example, if you use the expression `hasTags("tag1")` and the event contains `tag1`, then Data Prepper returns `true`. If you use the expression `hasTags("tag2")` but the event only contains `tag1`, then Data Prepper returns `false`.
+For example, if you use the expression `hasTags("tag1")` and the event contains `tag1`, then OpenSearch Data Prepper returns `true`. If you use the expression `hasTags("tag2")` but the event only contains `tag1`, then Data Prepper returns `false`.
 
 #### Example
 
diff --git a/_data-prepper/pipelines/pipelines.md b/_data-prepper/pipelines/pipelines.md
index d519f0da80..db4b648d1f 100644
--- a/_data-prepper/pipelines/pipelines.md
+++ b/_data-prepper/pipelines/pipelines.md
@@ -10,7 +10,7 @@ redirect_from:
 
 # Pipelines
 
-Pipelines are critical components that streamline the process of acquiring, transforming, and loading data from various sources into a centralized data repository or processing system. The following diagram illustrates how Data Prepper ingests data into OpenSearch.
+Pipelines are critical components that streamline the process of acquiring, transforming, and loading data from various sources into a centralized data repository or processing system. The following diagram illustrates how OpenSearch Data Prepper ingests data into OpenSearch.
 
 <img src="{{site.url}}{{site.baseurl}}/images/data-prepper-pipeline.png" alt="Data Prepper pipeline">{: .img-fluid}