🔧 Lab 0: Environment Setup

Duration: ~15 minutes

In this lab, you’ll set up your workshop environment using GitHub Codespaces and configure the necessary credentials.

📋 Prerequisites

Before starting, ensure you have:

  • ✅ A GitHub account
  • ✅ Dynatrace credentials (provided by your instructor)
  • ✅ Access to this workshop repository

🏷️ Set Your Attendee ID

Before proceeding, set your Attendee ID in the sidebar (on the left side of this page). This will automatically personalize all code examples and commands throughout the workshop labs.

  1. Look for the “Your Attendee ID” input field in the sidebar
  2. Enter your attendee ID (e.g., your name or initials like sudosmitty)
  3. Click Set or press Enter

💡 Tip: Your attendee ID is stored in your browser and will persist across all lab pages. You’ll see {YOUR_ATTENDEE_ID} placeholders replaced with your actual ID throughout the documentation.

Step 1: Launch GitHub Codespace

  1. If you haven’t already, click the button below to launch your personal workshop environment:

    Open in GitHub Codespaces

  2. Wait for the Codespace to build (this takes 2-3 minutes on first launch)

  3. Once ready, you’ll see VS Code in your browser with the workshop files

💡 Important: Each attendee gets their own isolated Codespace. All your code changes stay within your Codespace and won’t affect other workshop participants. No need to fork or create branches!

Step 2: Configure Workshop Credentials

After the Codespace starts, you’ll need to configure credentials.

2.1 Run the Setup Script

In the open VS Code terminal run:

bash .devcontainer/fetch-secrets.sh

2.2 Enter Your Credentials

You’ll be prompted for:

  1. Attendee ID - Enter your ATTENDEE_ID (e.g., {YOUR_ATTENDEE_ID})
  2. Workshop Token - Your instructor will provide this
🔐 Workshop Credentials Setup

Enter your attendee ID (e.g., your name or initials, no spaces) [press enter to generate]: {YOUR_ATTENDEE_ID}
✅ Attendee ID: {YOUR_ATTENDEE_ID}

Enter your workshop token: *INSTRUCTOR PROVIDED*
✅ Azure OpenAI credentials configured!

2.3 Load Your Credentials

You will need to load your credentials into the terminal session with the following command:

source ~/.bashrc

Then reload VS Code:

  1. Press Ctrl+Shift+P (or Cmd+Shift+P on Mac)
  2. Run: Developer: Reload Window

Step 3: Configure Dynatrace Credentials

Your Attendee ID and Azure OpenAI credentials are now configured as environment variables. You just need to add your Dynatrace credentials.

3.1 Open the Environment File

  1. In the VS Code Explorer, locate and open the .env file in the root directory

  2. You’ll see it only contains placeholders for Dynatrace credentials

3.2 Add Dynatrace Credentials

Your instructor will provide the following values. Enter them in your .env file:

# Dynatrace Configuration - Get these from your instructor
DT_ENDPOINT=https://YOUR_ENV.live.dynatrace.com/api/v2/otlp
DT_API_TOKEN=dt0c01.XXXXXXXXXX.YYYYYYYYYYYYYYYY

3.3 Verify Configuration

Your complete .env file should look like this:

# Dynatrace Configuration
DT_ENDPOINT=https://abc12345.live.dynatrace.com/api/v2/otlp
DT_API_TOKEN=dt0c01.EXAMPLE_TOKEN_HERE

ℹ️ Note: Azure OpenAI credentials and your Attendee ID are stored as environment variables (not in the .env file) for security.

To verify your environment variables are set, run in the terminal:

echo "Attendee: $ATTENDEE_ID"
echo "Azure OpenAI: ${AZURE_OPENAI_ENDPOINT:+configured}"

Step 3: Verify the Sample Application

Let’s make sure everything is working before we add instrumentation.

3.1 Start the Application

In your VS Code terminal, run:

python app/main.py

3.2 Expected Output

You should see output similar to:

╔══════════════════════════════════════════════════════════════════════╗
║         🚀 AI Chat Service Starting...                               ║
║                                                                      ║
║         Attendee ID: {YOUR_ATTENDEE_ID}                                          ║
║         Service: ai-chat-service-{YOUR_ATTENDEE_ID}                              ║
╚══════════════════════════════════════════════════════════════════════╝

✅ RAG initialized successfully for attendee: {YOUR_ATTENDEE_ID}
INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)

3.3 Test the Application

  1. When the application starts, VS Code will show a popup about port 8000. Click “Open in Browser”

  2. You should see the AI Chat Interface - a beautiful web UI for chatting with the AI assistant!

  3. Try sending a message like:

    “What is Dynatrace?”

  4. You should receive an AI-generated response in the chat!

💡 Tip: If you miss the popup, click the Ports tab in VS Code, find port 8000, and click the 🌐 globe icon.

3.4 Stop the Application

Press Ctrl+C in the terminal to stop the application.

✅ Checkpoint

Before proceeding to Lab 1, verify:

  • You’ve set your Attendee ID in the sidebar (code examples should show your ID, not {YOUR_ATTENDEE_ID})
  • Your Codespace is running
  • The .env file has the DT_ENDPOINT and DT_API_TOKEN from your instructor
  • The sample application starts without errors
  • You can access the application in your browser
  • The chat endpoint responds with AI-generated text

🆘 Troubleshooting

“Azure OpenAI credentials not found”

If you skipped entering the workshop token during Codespace creation:

  1. Get the workshop token from your instructor
  2. Run: bash .devcontainer/fetch-secrets.sh
  3. Enter the workshop token when prompted

“Invalid workshop token”

  1. Double-check you’ve entered the token correctly
  2. Make sure there are no extra spaces
  3. Ask your instructor to verify the token is correct

Missing or wrong ATTENDEE_ID

If you skipped the Attendee ID prompt or want to change it:

  1. Open the .env file
  2. Add an ATTENDEE_ID={YOUR_ATTENDEE_ID} line

“Connection refused” on port 8000

  1. Make sure the application is running
  2. Check that port 8000 is being forwarded (look in the Ports tab)

Application crashes on startup

  1. Check your .env file for typos
  2. Ensure all dependencies are installed: pip install -r app/requirements.txt

🎉 Great Job!

Your environment is ready! Let’s move on to adding AI observability instrumentation.

← Home Lab 1: Instrumentation →