find-and-replace for attributes (#53)

Author: aimurphy

antora.yml

@@ -8,7 +8,13 @@ nav:
 
 asciidoc:
   attributes:
-    product_name: 'Astra Streaming'
-    pulsar_version: '2.10' #DO NOT INCLUDE PATCH VERSION <MAJOR>.<MINOR>.<PATCH>
-    debezium_version: '1.7'
-    request_feature_access_email: '[email protected]'
+    product: 'Astra Streaming'
+    pulsar: 'Apache Pulsar'
+    pulsar-short: 'Pulsar'
+    pulsar-reg: 'Apache Pulsar(TM)'
+    pulsar-version: '2.10' #DO NOT INCLUDE PATCH VERSION <MAJOR>.<MINOR>.<PATCH>
+    debezium-version: '1.7'
+    astra-streaming-examples-repo: 'https://raw.githubusercontent.com/datastax/astra-streaming-examples/master'
+    cass: Apache Cassandra
+    cass-short: Cassandra
+    cass-reg: Apache Cassandra(R)

example-guide.adoc

@@ -9,8 +9,8 @@
 A guide is a document offering step by step instruction to reach some goal. Guides are technical in nature and tend to make assumptions about the consumer's environment. To help create guides that will work in most environments, please follow these ideas.
 
 * *Keep links to a minimum* - when someone is learning a new concept for the first time and xref:README.adoc[every] other xref:README.adoc[word] is linked it xref:README.adoc[makes] things xref:README.adoc[confusing] and hard to get a good flow going. Instead, annotate a word or phrase and provide a "Resources" area at the bottom of the guide.
-* *Separate products and runtimes in tabs* - it is common to reach the same result through multiple ways. An example is creating a tenant/namespace/topic in Astra Streaming and Luna Streaming. Both have the same result but get there in very different ways. Offer each as a tab and let the consumer choose their path. The step after the tabbed step can assume the consumer has complete the previious step and is in a known state. Runtimes follow the same pattern. Weather one is using Java or C#, they are still creating a Pulsar client to interact with the cluster. Create a single step in the guide with multiple tabs for each runtime.
-* *Be thoughtful about the names you use* - if you are leaning a new concept or feature with no background on the product, words matter. Labeling a tab as "Luna Helm" and then referring to it as "Pulsar Helm Chart" are two distinct things to that reader. The author of the document has such deep understanding that they consider those things the same - and technically they are at DataStax. But the read isn't from DataStax, so be mindful of their context.
+* *Separate products and runtimes in tabs* - it is common to reach the same result through multiple ways. An example is creating a tenant/namespace/topic in {product} and Luna Streaming. Both have the same result but get there in very different ways. Offer each as a tab and let the consumer choose their path. The step after the tabbed step can assume the consumer has complete the previious step and is in a known state. Runtimes follow the same pattern. Weather one is using Java or C#, they are still creating a {pulsar-short} client to interact with the cluster. Create a single step in the guide with multiple tabs for each runtime.
+* *Be thoughtful about the names you use* - if you are leaning a new concept or feature with no background on the product, words matter. Labeling a tab as "Luna Helm" and then referring to it as "{pulsar-short} Helm Chart" are two distinct things to that reader. The author of the document has such deep understanding that they consider those things the same - and technically they are at {company}. But the read isn't from {company}, so be mindful of their context.
 * *Talk in first person* - humans create the guides and humans consume the guides. Write as if you are paired with your consumer in doing what ever the guide does. Use "we", "us", "you".
 ====
 
@@ -21,7 +21,7 @@ Have you ever wanted to use this new feature? Well look no further than this gui
 You will need the following things in place to complete this guide:
 
 * about 5 minutes
-* a working Pulsar topic (xref:README.adoc[get started here] if you don't have one)
+* a working {pulsar-short} topic (xref:README.adoc[get started here] if you don't have one)
 
 == First group of tasks
 

modules/ROOT/nav.adoc

@@ -11,13 +11,13 @@
 ** xref:use-cases-architectures:real-time-data-pipeline/03-put-it-all-together.adoc[]
 ** xref:use-cases-architectures:real-time-data-pipeline/04-debugging-and-clean-up.adoc[]
 
-.Migrating to Apache Pulsar
+.Migrating to {pulsar}
 * xref:use-cases-architectures:starlight/index.adoc[]
 * xref:use-cases-architectures:starlight/kafka/index.adoc[]
 * xref:use-cases-architectures:starlight/rabbitmq/index.adoc[]
 * xref:use-cases-architectures:starlight/jms/index.adoc[]
 
-.APIs & References
+.APIs and References
 * Connectors
 ** xref:pulsar-io:connectors/index.adoc[]
 ** Sources

modules/ROOT/pages/index.adoc

@@ -1,6 +1,6 @@
-= DataStax Streaming Learning
+= {company} Streaming Learning
 
-The learning site is a collection of guides and articles about DataStax streaming products. Each product has its own area dedicated to providing specifics to get started, its features, and other details. The learning site helps you get the most out of each product and get to production using best practices.
+The learning site is a collection of guides and articles about {company} streaming products. Each product has its own area dedicated to providing specifics to get started, its features, and other details. The learning site helps you get the most out of each product and get to production using best practices.
 
 == Processing Data
 
@@ -28,7 +28,7 @@ A real-time data pipeline is a series of steps that takes data from its original
 </div>
 ++++
 
-== Migrating to Apache Pulsar
+== Migrating to {pulsar-reg}
 
 ++++
 <div class="landing-row">
@@ -48,7 +48,7 @@ xref:streaming-learning:use-cases-architectures:starlight/jms/index.adoc[Get sta
 .xref:streaming-learning:use-cases-architectures:starlight/kafka/index.adoc[Starlight for Kafka]
 ****
 --
-Starlight for Kafka brings native Apache Kafka(R) protocol support to Apache Pulsar by introducing a Kafka protocol handler on Pulsar brokers.
+Starlight for Kafka brings native {pulsar} protocol support by introducing a Kafka protocol handler on {pulsar-short} brokers.
 
 xref:streaming-learning:use-cases-architectures:starlight/kafka/index.adoc[Get started now] | xref:starlight-for-kafka:ROOT:index.adoc[Configuring] | https://github.com/datastax/starlight-for-kafka[Source Code]
 --
@@ -58,7 +58,7 @@ xref:streaming-learning:use-cases-architectures:starlight/kafka/index.adoc[Get s
 .xref:streaming-learning:use-cases-architectures:starlight/rabbitmq/index.adoc[Starlight for RabbitMQ]
 ****
 --
-Starlight for RabbitMQ combines the AMQP 0.9.1 API with Pulsar, providing a powerful way to modernize your RabbitMQ infrastructure, improve performance, and reduce costs.
+Starlight for RabbitMQ combines the AMQP 0.9.1 API with {pulsar-short}, providing a powerful way to modernize your RabbitMQ infrastructure, improve performance, and reduce costs.
 
 xref:streaming-learning:use-cases-architectures:starlight/rabbitmq/index.adoc[Get started now] | xref:starlight-for-rabbitmq:ROOT:index.adoc[Configuring] | https://github.com/datastax/starlight-for-rabbitmq[Source Code]
 --
@@ -72,20 +72,20 @@ xref:streaming-learning:use-cases-architectures:starlight/rabbitmq/index.adoc[Ge
 
 === Connectors
 
-A connector is a function that moves data between Apache Pulsar and external systems. Source are used to push data to Pulsar from external systems such as databases, message queues, and storage systems. Sinks are used to pull data from a Pulsar topic to an external system like a database, data warehouse, or storage system. +
+A connector is a function that moves data between {pulsar} and external systems. Source are used to push data to {pulsar-short} from external systems such as databases, message queues, and storage systems. Sinks are used to pull data from a {pulsar-short} topic to an external system like a database, data warehouse, or storage system. +
 xref:streaming-learning:pulsar-io:connectors/index.adoc#_source_connectors[Sources] | xref:streaming-learning:pulsar-io:connectors/index.adoc#_sink_connectors[Sinks] | xref:streaming-learning:pulsar-io:connectors/index.adoc#_experimental_connectors[Experimental]
 
-=== Pulsar Functions
+=== {pulsar-short} Functions
 
 Functions are lightweight compute processes that enable you to process each message received on a topic. You can apply custom logic to that message, transforming or enriching it, and then output it to a different topic. +
 xref:streaming-learning:functions:astream-functions.adoc[Learn more]
 
 === Transformation Functions
 
-Transform functions are a low-code implementation of common Pulsar functions. They are used to transform messages from one format to another. Use them to transform a message, enrich messages with additional data, or filter messages based on their content. +
+Transform functions are a low-code implementation of common {pulsar-short} functions. They are used to transform messages from one format to another. Use them to transform a message, enrich messages with additional data, or filter messages based on their content. +
 xref:streaming-learning:functions:cast.adoc[Cast] | xref:streaming-learning:functions:compute.adoc[Compute] | xref:streaming-learning:functions:drop.adoc[Drop] | xref:streaming-learning:functions:flatten.adoc[Flatten] | xref:streaming-learning:functions:merge-key-value.adoc[Merge] | xref:streaming-learning:functions:unwrap-key-value.adoc[Unwrap]
 
 === Topic Subscriptions
 
-Subscriptions in Pulsar describe which consumers are consuming data from a topic and how they want to consume that data. +
+Subscriptions in {pulsar-short} describe which consumers are consuming data from a topic and how they want to consume that data. +
 xref:streaming-learning:subscriptions:astream-subscriptions-exclusive.adoc[Exclusive] | xref:streaming-learning:subscriptions:astream-subscriptions-shared.adoc[Shared] | xref:streaming-learning:subscriptions:astream-subscriptions-failover.adoc[Failover] | xref:streaming-learning:subscriptions:astream-subscriptions-keyshared.adoc[Key Shared]