LEDA with proper C9 template

content/design-patterns/ex1capacity/Step2.en.md

@@ -7,7 +7,7 @@ weight = 3
 
 Now that you have created the table, you can load some sample data into the table by running the following Python script.
 ```bash
-cd /home/ec2-user/workshop
+cd /home/ubuntu/workshop
 python load_logfile.py logfile ./data/logfile_small1.csv
 ```
 The parameters in the preceding command: 1) Table name = `logfile` 2) File name = `logfile_small1.csv`

content/design-patterns/setup/Step1.en.md

@@ -9,28 +9,28 @@ weight = 10
 1. In the services search bar, search for **Systems Manager** and click on it to open the AWS Systems Manager section of the AWS Management Console.
 1. In the AWS Systems Manager console, locate the menu in the left, identify the section **Node Management** and select **Session Manager** from the list.
 1. Choose **Start session** to launch a shell session.
-1. Click the radio button to select the EC2 instance for the lab. If you see no instance, wait a few minutes and then click refresh. Wait until an ec2 instance with name of `mod-XXXXXXXXXXXXXXXX` OR `ddb` is available before continuing. You will see only one of the two names.
-1. Click in the **Start Session** button (This action will open a new tab in your browser with a new black shell).
-1. In the new black shell, switch to the ec2-user account by running `sudo su - ec2-user`
+1. Click the radio button to select the EC2 instance for the lab. If you see no instance, wait a few minutes and then click refresh. Wait until an ec2 instance with name of `DynamoDBC9` is available before continuing. Select the instance.
+1. Click the **Start Session** button (This action will open a new tab in your browser with a new black shell).
+1. In the new black shell, switch to the ubuntu account by running `sudo su - ubuntu`
    ```bash
-   sudo su - ec2-user
+   sudo su - ubuntu
    ```
-1. run `shopt login_shell` and be sure it says `login_shell on`. Then, change into the workshop directory to begin: `cd ~/workshop`
-
+1. run `shopt login_shell` and be sure it says `login_shell on` and then change into the workshop directory. 
    ```bash
    #Verify login_shell is 'on'
    shopt login_shell
    #Change into the workshop directory
-   cd ~/workshop
+   cd ~/workshop/
    ```
 
-   The output of your commands in the Session Manager session should look like the following:
 
+The output of your commands in the Session Manager session should look like the following:
    ```bash
-   sh-4.2$ sudo su - ec2-user
-   [ec2-user@ip-172-31-24-0 ~]$ #Verify login_shell is 'on'
-   [ec2-user@ip-172-31-24-0 ~]$ shopt login_shell
+   $ sudo su - ubuntu
+   :~ $ #Verify login_shell is 'on'
+   shopt login_shell
+   #Change into the workshop directory
+   cd ~/workshop/
    login_shell     on
-   [ec2-user@ip-172-31-24-0 ~]$ #Change into the workshop directory
-   [ec2-user@ip-172-31-24-0 ~]$ cd ~/workshop
+   :~/workshop $
    ```

content/design-patterns/setup/Step2.en.md

@@ -14,8 +14,9 @@ python --version
 Output:
 
 ```plain
-Python 3.6.12
+Python 3.10.12
 ```
+**Note: The major and minor version of Python may vary from what you see above**
 
 Run the following command to check the AWS CLI on your EC2 instance:
 
@@ -28,9 +29,9 @@ Sample output:
 
 ```bash
 #Note that your linux kernel version may differ from the example.
-aws-cli/1.18.139 Python/3.6.12 Linux/4.14.193-113.317.amzn1.x86_64 botocore/1.17.62
+aws-cli/2.13.26 Python/3.11.6 Linux/6.2.0-1013-aws exe/x86_64.ubuntu.22 prompt/off
 ```
 
 {{% notice note %}}
-_Make sure you have AWS CLI version 1.18.139 and python 3.6.12 before proceeding. If you do not have these versions, review [Step 1]({{< ref "design-patterns/setup/Step1" >}}) to ensure you have completed each command correctly._
+_Make sure you have AWS CLI version 2.x or higher and python 3.10 or higher before proceeding. If you do not have these versions, you may have difficultly successfully completing the lab._
 {{% /notice %}}

content/design-patterns/setup/Step3.en.md

@@ -1,5 +1,5 @@
 +++
-title = "Step 3 - Check boto3 installation"
+title = "Step 3 - Boto3 installation"
 date = 2019-12-02T10:07:52-08:00
 weight = 30
 +++

content/design-patterns/setup/Step4.en.md

@@ -7,7 +7,7 @@ weight = 40
 On the EC2 instance, go to the workshop folder and run the ls command:
 
 ```bash
-cd /home/ec2-user/workshop
+cd /home/ubuntu/workshop
 ls -l .
 ```