Document changes for nginx architecture

Author: rohitkatakol

metro-ai-suite/image-based-video-search/README.md

@@ -1,4 +1,4 @@
-# Image-Based Video Search Sample Application
+# Image-Based Video Search (IBVS) Sample Application
 <!--REQUIRED: Add a short description without including the name of the RI/Application/microservice in the description. Ensure it's at least 50 characters (excluding spaces) and doesn't exceed 150 characters (excluding spaces). This will enable the content to be properly displayed in the catalog's card layout.-->
 Performs near real-time analysis and image-based search to detect and retrieve objects of interest in large video datasets.
 
@@ -12,7 +12,7 @@ You can use this foundation to build solutions for diverse use cases, including
 ## How it Works
 The application workflow has three stages: inputs, processing, and outputs.
 
-![Diagram illustrating the components and interactions within the Image-Based Video Search system, including inputs, processing, and outputs.](docs/user-guide/_images/architecture_simplified.png)
+![Diagram illustrating the components and interactions within the Image-Based Video Search system, including inputs, processing, and outputs.](docs/user-guide/_images/architecture.png)
 
 ### Inputs
 
@@ -23,6 +23,7 @@ The application includes a demonstration video for testing. The video loops cont
 
 ### Processing
 
+- **Nginx reverse proxy server**: All interactions with user happens via Nginx server. It protects IBVS app by handling SSL/TLS encryption, filtering and validating requests and making the app directly inaccessible from external access.
 - **Video analysis with Deep Learning Streamer Pipeline Server and MediaMTX**: Select **Analyze Stream** to start the DL Streamer Pipeline Server pipeline. The Pipeline Server processes video through **MediaMTX**, which simulates remote video cameras and publishes live streams. The Pipeline Server extracts frames and detects objects in each frame, publishing predictions through **MQTT**.
 - **Feature extraction with Feature Matching**: DL Streamer Pipeline Server sends metadata and images through MQTT to the Feature Matching microservice. Feature Matching generates feature vectors. If predictions exceed the threshold, the system stores vector embeddings in MilvusDB and saves frames in the Docker file system.
 - **Storage and retrieval in MilvusDB**: MilvusDB stores feature vectors. You can review them in MilvusUI.

metro-ai-suite/image-based-video-search/docs/user-guide/Overview.md

@@ -1,4 +1,4 @@
-# Image-Based Video Search Sample Application
+# Image-Based Video Search (IBVS) Sample Application
 
 <!--REQUIRED: Add a short description without including the name of the RI/Application/microservice in the description. Ensure it's at least 50 characters (excluding spaces) and doesn't exceed 150 characters (excluding spaces). This will enable the content to be properly displayed in the catalog's card layout.-->
 
@@ -23,7 +23,7 @@ quickly locate objects of interest across large video datasets.
 
 The application workflow has three stages: inputs, processing, and outputs.
 
-![Diagram illustrating the components and interactions within the Image-Based Video Search system, including inputs, processing, and outputs.](_images/architecture_simplified.png)
+![Diagram illustrating the components and interactions within the Image-Based Video Search system, including inputs, processing, and outputs.](_images/architecture.png)
 
 ### Inputs
 
@@ -35,6 +35,7 @@ continuously and appears in the UI as soon as the application starts.
 
 ### Processing
 
+- **Nginx reverse proxy server**: All interactions with user happens via Nginx server. It protects IBVS app by handling SSL/TLS encryption, filtering and validating requests and making the app directly inaccessible from external access.
 - **Video analysis with Deep Learning Streamer Pipeline Server and MediaMTX**:
   Select **Analyze Stream** to start the DL Streamer Pipeline Server pipeline.
   The Pipeline Server processes video through **MediaMTX**, which simulates

metro-ai-suite/image-based-video-search/docs/user-guide/_images/architecture.png

@@ -25,7 +25,7 @@ How it Works
 
 The application workflow has three stages: inputs, processing, and outputs.
 
-.. figure:: ./_images/architecture_simplified.png
+.. figure:: ./_images/architecture.png
    :alt: Diagram illustrating the components and interactions within the Image-Based Video Search system, including inputs, processing, and outputs.
 
    Figure 1: Diagram illustrating the components and interactions within the Image-Based Video Search system, including inputs, processing, and outputs.

metro-ai-suite/image-based-video-search/docs/user-guide/index.rst

@@ -53,6 +53,11 @@ Architecture of the Image-Based Video Search Application.*
 
 ## Key Components and Their Roles
 
+1. **Nginx reverse proxy server**
+   - **What it is**: An Nginx reverse proxy acts as an intermediary server that forwards client requests to backend servers, helping with load balancing, SSL termination, caching, and centralized access control.
+   - **How it’s used**: It acts as proxy server. All interactions to IBVS app happens via nginx server. It forwards all the requests from outside world to internal serices based on routing configuration.
+   - **Benefits**: It acts as protective gateway that receives external requests and securely forwards them to internal services, keeping those backend apps hidden and inaccessible from direct external access.
+
 1. **MediaMTX (Third-Party Microservice)**
 
    - **What it is**: A service that simulates remote video cameras.