updates

Author: codingbandit

01_Overview_Cosmos_DB/README.md

@@ -1,4 +1,4 @@
-# Overview of Azure Cosmos DB (high-level with links to docs for more information)
+# Overview of Azure Cosmos DB
 
 [Azure Cosmos DB](https://learn.microsoft.com/en-us/azure/cosmos-db/introduction) is a globally distributed, multi-model database service that enables you to query and store data using NoSQL models using one of five APIs: SQL (document database), Cassandra (column-family), MongoDB (document database), Azure Table, and Gremlin (graph database). It provides turnkey global distribution, elastic scaling of throughput and storage worldwide, single-digit millisecond latencies at the 99th percentile, and guaranteed high availability with multi-homing capabilities. Azure Cosmos DB provides comprehensive service level agreements (SLAs) for throughput, latency, availability, and consistency guarantees, something not found in any other database service.
 
@@ -12,7 +12,7 @@ The [RU architecture](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/
 
 Azure Cosmos DB for MongoDB [vCore architecture](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/vcore/introduction) integrates AI-based applications with your data, with text indexing for easy querying. Simplify your development process with high-capacity vertical scaling and free 35-day backups with a point-in-time restore (PITR).
 
-The [choice between vCore and Request Units (RU)](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/choose-model) in Azure Cosmos DB for MongoDB API depends on the workload.
+The [choice between vCore and Request Units (RU)](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/choose-model) in Azure Cosmos DB for MongoDB API depends on the workload. A list of [compatibility and feature support between RU and vCore](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/vcore/compatibility) is available.
 
 vCore provides predictable performance and cost and is ideal for running high-performance, mission-critical workloads with low latency and high throughput. With vCore, the number of vCPUs and the memory the database needs is configurable and can be scaled up or down as needed.
 

06_Create_First_Cosmos_DB_Project/README.md

@@ -12,7 +12,7 @@ For Windows machines, the emulator can be installed via an installer. There is a
 
 Learn more about the pre-requisites and installation of the emulator [here](https://learn.microsoft.com/en-us/azure/cosmos-db/how-to-develop-emulator?tabs=windows%2Cpython&pivots=api-mongodb).
 
->**NOTE**: When using the Azure CosmosDB emulator using the API for MongoDB it must be started with the [MongoDB endpoint options enabled](https://learn.microsoft.com/en-us/azure/cosmos-db/how-to-develop-emulator?tabs=windows%2Cpython&pivots=api-mongodb#start-the-emulator) on the command-line.
+>**NOTE**: When using the Azure CosmosDB emulator using the API for MongoDB it must be started with the [MongoDB endpoint options enabled](https://learn.microsoft.com/en-us/azure/cosmos-db/how-to-develop-emulator?tabs=windows%2Cpython&pivots=api-mongodb#start-the-emulator) at the command-line.
 
 **The Azure Cosmos DB emulator does not support vector search. To complete the vector search and AI-related labs, you must use an Azure Cosmos DB API for the MongoDB vCore account in Azure.**
 
@@ -28,27 +28,10 @@ The splash screen or **Quickstart** section of the Cosmos DB Emulator will displ
 
 ### Retrieving the connection string from the Azure portal
 
-Retrieve the connection string from the Azure portal by navigating to your Azure Cosmos DB account and selecting the **Connection String** menu item on the left-hand side of the screen. The connection string contains tokens for the username and password that must be replaced with the username and password used when provisioning the Azure Cosmos DB API for MongoDB service. Users can be added at any time using the [Azure CLI](https://learn.microsoft.com/en-us/cli/azure/cosmosdb/mongodb/user?view=azure-cli-latest).
+Retrieve the connection string from the Azure portal by navigating to your Azure Cosmos DB account and selecting the **Connection String** menu item on the left-hand side of the screen. The connection string contains tokens for the username and password that must be replaced with the username and password used when provisioning the Azure Cosmos DB API for MongoDB service.
 
 ![The Azure CosmosDb API for MongoDB Connection strings screen displays with the copy button next to the connection string highlighted.](media/azure_connection_string.png)
 
-## Authorization
-
-Azure Cosmos DB API for MongoDB supports fine-grained role-based access control (RBAC) for authorization. There are several built-in roles available. The built-in roles are:
-    1. read
-    2. readWrite
-    3. dbAdmin
-    4. dbOwner
-
-The ability to create custom roles is also available. Custom roles can be created using the [Azure CLI](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/how-to-setup-rbac). Customized roles can include granular permissions for specific databases, collections, and operational actions. Learn more about the [Azure CLI RBAC commands to define custom roles](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/how-to-setup-rbac#azure-cli-rbac-commands).
-
-## Helpful tools
-
-Visualization and querying tools:
-    1. Studio 3T
-    2. MongoDB Compass
-    3. MongoDB Shell
-
 ## Lab 1 - Create your first Cosmos DB for the MongoDB application
 
 Using a notebook, we'll create a Cosmos DB for the MongoDB application in this lab. You can use the Azure Cosmos DB Emulator or an Azure Cosmos DB account in Azure. The following concepts will be covered in this lab:

07_Load_Data/README.md

@@ -12,8 +12,8 @@ When loading data, bulk operations are preferred over adding each document indiv
 
 4. Simplified code logic: By using bulk operations, the lab can simplify its code logic and reduce the number of database queries. This results in cleaner, more manageable code and reduces the likelihood of errors or inconsistencies.
 
-## Lab 3 - Load data into Azure Cosmos DB API for MongoDB collections
+## Lab 2 - Load data into Azure Cosmos DB API for MongoDB collections
 
 This lab will load the Cosmic Works Customer, Product, and Sales data into Azure Cosmos DB API for MongoDB collections using bulk operations.
 
-Please complete Lab 3 in the lab repository.
+Please complete Lab 2 in the lab repository.