My Experience: VS Code extensions for Azure developers

Context

Developers often waste time on repetitive Azure tasks that could be automated.

The Journey

Why I Started

I was facing this challenge while working on a project for a client. The existing solution was:

• Slow (took 5 minutes to complete)


• Expensive (costing $500/month)


• Difficult to maintain (required constant manual intervention)

I knew there had to be a better way using Azure services.

What I Tried First

Approach 1: Azure Functions

[FunctionName("MyFunction")]

public static async Task<IActionResult> Run(

    [HttpTrigger(AuthorizationLevel.Function, "post")] HttpRequest req,

    ILogger log)

{

    // Implementation

    return new OkObjectResult("Success");

}

Result: Partial success, but cold starts were an issue.

What Worked

After experimenting, I found the winning combination:

1. 
   Azure Service A: For handling X


2. 
   Azure Service B: For processing Y


3. 
   Azure Service C: For storage

Here's the final architecture:

# Deploy infrastructure

az deployment group create \

  --resource-group myRG \

  --template-file main.bicep

Key Metrics

Challenges Faced

Challenge 1: Authentication Issues

Problem: Managed identities weren't working as expected.

Solution: Added explicit role assignments:

az role assignment create \

  --assignee $PRINCIPAL_ID \

  --role "Contributor" \

  --scope $RESOURCE_ID

Challenge 2: Cost Overruns

Problem: Costs were higher than expected in the first month.

Solution: Implemented auto-scaling rules and budget alerts:

az monitor autoscale create \

  --resource $RESOURCE_ID \

  --min-count 1 \

  --max-count 3 \

  --count 1

Lessons Learned

1. 
   Start small: Don't over-engineer the first version


2. 
   Monitor early: Set up monitoring from day 1


3. 
   Cost matters: Always estimate costs before deploying


4. 
   Test thoroughly: Use Azure DevTest Labs


5. 
   Document everything: Future you will thank you

What I'd Do Differently

1. Use Bicep instead of ARM templates from the start


2. Implement CI/CD pipeline earlier


3. Spend more time on cost estimation upfront


4. Use Azure Advisor recommendations sooner

Recommendation

Use this approach when:

• ✅ You need high availability


• ✅ Cost optimization is important


• ✅ You have variable workloads

Avoid this approach when:

• ❌ Workload is constant and predictable


• ❌ You need sub-millisecond latency


• ❌ Budget is extremely tight

Resources

• My GitHub Repo


• Azure Documentation


• Related Post

Have you faced similar challenges? I'd love to hear about your experience in the comments! 💭

This post is part of my Azure learning journey. Follow for more real-world experiences!