Update github links for Kafka Live Viewer Profiles tutorial (#1134)

Author: mscwilson

tutorials/kafka-live-viewer-profiles/deploy-aws-terraform.md

@@ -15,9 +15,9 @@ The following [Steps](#steps) will deploy the solution accelerator to AWS using
 
 1. Open a terminal.
 2. Install **Docker** and **Docker Compose**.
-3. [Clone the project](https://github.com/snowplow-incubator/live-viewer-profiles) and navigate to its directory.
+3. [Clone the project](https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles) and navigate to its directory.
 ```bash
-git clone https://github.com/snowplow-incubator/live-viewer-profiles.git
+git clone https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles.git
 ```
 4. Create a `.env` file based on `.env.example` and configure AWS variables.
 ```bash
@@ -58,7 +58,7 @@ $ ./up.sh    # <- start the Docker containers
 
 ### Step 4: Open Access to the Applications
 
-Review the [LocalStack guide](/tutorials/kafka-live-viewer-profiles/quickstart-localstack) for the default configuration for each component. Open public access to the two frontend applications and the Snowplow Collector using a HTTP load balancer so that anyone can watch the video, submit events to the pipeline, and see information on concurrent users. 
+Review the [LocalStack guide](/tutorials/kafka-live-viewer-profiles/quickstart-localstack) for the default configuration for each component. Open public access to the two frontend applications and the Snowplow Collector using a HTTP load balancer so that anyone can watch the video, submit events to the pipeline, and see information on concurrent users.
 
 The applications listen for HTTP traffic on the following ports
 - Web tracker front end - 3000
@@ -67,7 +67,7 @@ The applications listen for HTTP traffic on the following ports
 
 ## Next Steps
 - You can implement Snowplow media tracking on any [HTML5](/docs/sources/trackers/javascript-trackers/web-tracker/tracking-events/media/html5/) or [YouTube](/docs/sources/trackers/javascript-trackers/web-tracker/tracking-events/media/youtube/) media of your choice
-- Look into the output from Kafka and extend the Live Viewer to include information on the media being watched and the user. 
+- Look into the output from Kafka and extend the Live Viewer to include information on the media being watched and the user.
 - Replace Amazon DynamoDB with an alternative to be cloud agnostic, e.g. Google Bigtable or MongoDB.
 ---
 

tutorials/kafka-live-viewer-profiles/introduction.md

@@ -4,34 +4,34 @@ title: Introduction
 ---
 
 ## About This Accelerator
-Welcome to the **live viewer profiles** solution accelerator for video streaming! 
+Welcome to the **live viewer profiles** solution accelerator for video streaming!
 
-This accelerator demonstrates how to build a real-time use case leveraging **Snowplow event data** to create live viewer profiles for a video streaming site. By combining Snowplow's streaming pipeline with **Apache Kafka**, a **Java application** and **AWS DynamoDB**, the solution processes live streaming events to visualize user interactions with video content and advertisements. 
+This accelerator demonstrates how to build a real-time use case leveraging **Snowplow event data** to create live viewer profiles for a video streaming site. By combining Snowplow's streaming pipeline with **Apache Kafka**, a **Java application** and **AWS DynamoDB**, the solution processes live streaming events to visualize user interactions with video content and advertisements.
 
-On the left side of the image below we have someone watching a video. Their events are sent through a Snowplow pipeline to Kafka where they are consumed and processed by an application. The result of this processing is displayed in the right window. This shows the number of active users and their current state. 
+On the left side of the image below we have someone watching a video. Their events are sent through a Snowplow pipeline to Kafka where they are consumed and processed by an application. The result of this processing is displayed in the right window. This shows the number of active users and their current state.
 
 ![Application Output](images/one-viewer.png)
 
 Through this hands-on guide, you’ll learn how to build, deploy, and extend real-time, event-driven architectures using Snowplow and Kafka, enabling personalized recommendations, real-time insights, and dynamic analytics for streaming platforms. The framework is inspired by common challenges in video streaming, including tracking user behavior, ad engagement, and session activities, with the goal of maintaining up-to-date viewer profiles in DynamoDB.
 
 This accelerator is open source and can serve as the foundation to build practical applications like real-time viewer insights, engagement analytics, ad performance tracking, and personalized recommendations. Whether you're optimizing ad placements or enhancing viewer satisfaction, this guide equips you to unlock the full potential of Snowplow event data.
 
-Please start by reviewing how the application works in the next page on Localstack, even if you're planning to deploy with Terraform. 
+Please start by reviewing how the application works in the next page on Localstack, even if you're planning to deploy with Terraform.
 
 ---
 
 ## Solution Accelerator Code
-[**The code for this infrastructure is available on here on GitHub.**](https://github.com/snowplow-incubator/live-viewer-profiles)
+[**The code for this infrastructure is available on here on GitHub.**](https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles)
 
 ---
 
 ## Architecture
 
 The solution comprises several interconnected components:
 
-- **Web Tracking Application**: 
+- **Web Tracking Application**:
   - A React application with a video to watch. Snowplow's media tracking has been configured to send events (e.g., play, pause, ad skipped) to the [Snowplow Collector](/docs/fundamentals/architecture-overview).
-  - Code available in [tracker-frontend](https://github.com/snowplow-incubator/live-viewer-profiles/tree/main/tracker-frontend) folder in GitHub
+  - Code available in [tracker-frontend](https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles/tree/main/tracker-frontend) folder in GitHub
 
 - **Snowplow Collector**:
   - Collects and forwards events via [Stream Enrich](/docs/fundamentals/architecture-overview) and Kinesis to [Snowbridge](/docs/destinations/forwarding-events/snowbridge).
@@ -41,17 +41,17 @@ The solution comprises several interconnected components:
 
 - **Live Viewer Backend**:
   - A Java application which processes events from Kafka, stores the data in DynamoDB, and generates JSON state data for the Live Viewer Frontend
-  - Code available in [live-viewer-backend](https://github.com/snowplow-incubator/live-viewer-profiles/tree/main/live-viewer-backend) folder in GitHub
+  - Code available in [live-viewer-backend](https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles/tree/main/live-viewer-backend) folder in GitHub
 
 - **Live Viewer Frontend**:
   - A HTML website which displays the state of users currently watching the video.
-  - Code available in [live-viewer-frontend](https://github.com/snowplow-incubator/live-viewer-profiles/tree/main/live-viewer-frontend) folder in GitHub
+  - Code available in [live-viewer-frontend](https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles/tree/main/live-viewer-frontend) folder in GitHub
 
-The following diagram maps out where each component sits in the end to end communication flow. 
+The following diagram maps out where each component sits in the end to end communication flow.
 ![Architecture Diagram](images/architecture.png)
 
 ### Components & Configuration
-The following files in the [GitHub repository](https://github.com/snowplow-incubator/live-viewer-profiles) can be used  to configure the project's components. 
+The following files in the [GitHub repository](https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles) can be used  to configure the project's components.
 - **Snowplow components**: `compose.snowplow.yaml`
 - **Kafka infrastructure**: `compose.kafka.yaml`
 - **Application components**: `compose.apps.yaml`

tutorials/kafka-live-viewer-profiles/quickstart-localstack.md

@@ -11,9 +11,9 @@ title: Quickstart with Localstack
 
 1. Open a terminal.
 2. Install **Docker** and **Docker Compose**.
-3. [Clone the project](https://github.com/snowplow-incubator/live-viewer-profiles) and navigate to its directory.
+3. [Clone the project](https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles) and navigate to its directory.
 ```bash
-git clone https://github.com/snowplow-incubator/live-viewer-profiles.git
+git clone https://github.com/snowplow-industry-solutions/kafka-live-viewer-profiles.git
 ```
 4. Create a `.env` file based on `.env.example`. You can leave the AWS variables as placeholders when using Localstack
 ```bash
@@ -39,11 +39,11 @@ Details on everything that is installed can be found in [architecture](/tutorial
 
 ### Step 2: Open the Web Tracking Frontend
 
-Visit [http://localhost:3000](http://localhost:3000) to configure the Stream Collector endpoint and start tracking events. Enter the Collector URL: `localhost:9090` and click `Create tracker`. 
+Visit [http://localhost:3000](http://localhost:3000) to configure the Stream Collector endpoint and start tracking events. Enter the Collector URL: `localhost:9090` and click `Create tracker`.
 
 ![First page of tracking website](images/tracker-demo.png)
 
-On the next screen, click `Custom media tracking demo`. This will bring up a video and a screen that displays information on what events are sent from the browser to the pipeline. If you want to simulate multiple users watching the video at the same time, you can open this in separate browsers. 
+On the next screen, click `Custom media tracking demo`. This will bring up a video and a screen that displays information on what events are sent from the browser to the pipeline. If you want to simulate multiple users watching the video at the same time, you can open this in separate browsers.
 
 ![Welcome page on tracking website](images/welcome-page.png)
 
@@ -61,7 +61,7 @@ Congratulations! You have successfully run the accelerator to stream web behavio
 
 ## Next Steps
 - You can implement Snowplow media tracking on any [HTML5](/docs/sources/trackers/javascript-trackers/web-tracker/tracking-events/media/html5/) or [YouTube](/docs/sources/trackers/javascript-trackers/web-tracker/tracking-events/media/youtube/) media of your choice
-- Look into the output from Kafka and extend the Live Viewer to include information on the media being watched and the user. 
+- Look into the output from Kafka and extend the Live Viewer to include information on the media being watched and the user.
 - Use our supplied Terraform in the next section to run this on AWS and make it publicly available.
 
 ## Other Things You Can Do
@@ -80,7 +80,7 @@ sudo ./lazydocker.sh
 
 ### Inspect Infrastructure with LocalStack UI
 
-Visit the [LocalStack UI](https://app.localstack.cloud/) to inspect infrastructure components such as Kinesis and DynamoDB. Please note that a LocalStack account is required to view this. 
+Visit the [LocalStack UI](https://app.localstack.cloud/) to inspect infrastructure components such as Kinesis and DynamoDB. Please note that a LocalStack account is required to view this.
 
 ## Cleaning Up