Introducing AI Playground on Azure App Service for Linux

If you’re running a Small Language Model (SLM) as a sidecar with your web app, there’s now a faster way to try prompts, measure latency, and copy working code into your app—all without leaving your site. AI Playground is a lightweight, built-in experience available from the Kudu endpoint for every Linux App Service. 

What is AI Playground? 

AI Playground is a simple UI that talks to the SLM you’ve attached to your App Service app (for example, Phi or BitNet via the Sidecar extension). It lets you: 

• Send system and user prompts and view responses in-line
• See performance metrics like Time to First Token (TTFT), total time, and tokens/sec
• Grab ready-to-use code snippets for popular languages from the right sidebar (when you’re ready to integrate) 
• Confirm whether a sidecar SLM is configured—and get clear guidance if it isn’t 

Sidecar SLMs were introduced earlier this year; they let you run models like Phi and BitNet alongside your app. Learn more: https://learn.microsoft.com/en-us/azure/app-service/tutorial-ai-slm-dotnet 

 Where to find it the AI Playground 

1. In the Azure portal, go to your App Service (Linux). 
2. Open Advanced Tools (Kudu) → Go. 
3. In the Kudu left navigation, select AI Playground. 

Note: A pre-requisite for the playground is already having an SLM sidecar setup with your application. Here is a tutorial to set it up https://learn.microsoft.com/en-us/azure/app-service/tutorial-ai-slm-dotnet

A quick tour 

Prompts panel 

• Set a System Prompt (e.g., “You speak like a pirate.”) to steer behavior. 
• Enter a User Prompt, then click Send to SLM. 

Performance metrics displayed 

• TTFT: how quickly the first token arrives—great for responsiveness checks. 
• Total: overall response time. 
• Tokens/sec: sustained throughput for the generation. 

Code integration examples 

• On the right, you’ll find minimal snippets for C#, Python, and Node.js you can paste into your app later (no need to leave Kudu). 

Tip: Keep prompts compact for SLMs. If output slows, shorten the prompt or reduce requested length. 

Don’t have a sidecar yet? 

If AI Playground can’t find an SLM, you’ll see an inline notice with setup steps. 

Full tutorial: https://learn.microsoft.com/en-us/azure/app-service/tutorial-ai-slm-dotnet

Troubleshooting  

No responses / timeouts 

• Confirm the sidecar is Running in Deployment Center → Containers. 
• Check the sidecar’s port and endpoint 

Slow TTFT or Tokens/sec 

• Warm up with a couple of short prompts. 
• Consider scaling up to a Premium plan. 
• Keep prompts and requested outputs short. 

Roadmap 

This is v1. We’re already working on: 

• Bring-your-own LLMs (play with different models beyond SLMs) 
• Richer evaluation (prompt presets, saved sessions, exportable traces) 
• Better observability (per-call logs, quick links to Log Stream) 

Conclusion 

AI Playground makes building AI features on App Service feel immediate - type, run, measure, and ship. We’ll keep smoothing the experience and unlocking more model choices so you can go from idea to integrated AI faster than ever.