Amazon Q Developer in Action: How I Used AI to Accelerate Infrastructure Reviews and Code Quality in My AWS Projects

Prabhu Jayaseelan · June 2026 · 10 min read

Introduction

I have been writing infrastructure code for many years. Terraform, CloudFormation, CDK, Kubernetes manifests, Python Lambda functions — thousands of lines of code across dozens of AWS projects. And I still make mistakes. Everyone does.

Misconfigured IAM policies. Security groups that are too permissive. Missing error handling. Hardcoded values that should be parameters. These are the kinds of issues that slip through code review and cause incidents at 2 AM.

Amazon Q Developer changed how I approach this problem. It is AWS’s AI-powered developer tool that reviews your code, suggests improvements, identifies security vulnerabilities, generates IaC, and explains AWS services — all in real time inside your IDE or directly in the AWS console.

Amazon Q — A generative-AI powered assistant from AWS. Five products available: Amazon Q Developer, Q Business, Q in QuickSight, Q in Connect, and Q in AWS Supply Chain.

What is Amazon Q Developer?

Amazon Q Developer is an AI coding assistant purpose-built for AWS. Unlike general-purpose AI tools, it has deep AWS knowledge built in — it knows IAM, it knows EKS, it knows CloudFormation.

Use Case 1: Security Review of IAM Policies

I asked Amazon Q to review an IAM policy I had written for the ADOT collector in my observability setup:

My original policy:

{
  "Effect": "Allow",
  "Action": "aps:*",
  "Resource": "*"
}

Amazon Q’s response:

⚠️ Security Issue Found — Overly Permissive IAM Policy

Your policy grants aps:* (all APS actions) on * (all resources).
This violates the principle of least privilege.

Recommended fix:
{
  "Effect": "Allow",
  "Action": [
    "aps:RemoteWrite",
    "aps:QueryMetrics",
    "aps:GetLabels",
    "aps:GetSeries",
    "aps:GetMetricMetadata"
  ],
  "Resource": "arn:aws:aps:ap-south-1:041124937068:workspace/ws-f531d5d1-ba3c-4c3d-9dc9-5b3fe24db32c"
}

This is exactly the policy I ended up using in my observability setup. Amazon Q caught the issue in seconds that would have been a security finding in a production audit.

Use Case 2: Generating Kubernetes YAML

I asked Amazon Q: “Generate a Kubernetes DaemonSet for ADOT collector with resource limits and health checks.”

It generated the complete YAML — with liveness probes, resource requests, security context, and service account reference — in under 10 seconds. The same YAML I would have spent 20 minutes writing and looking up documentation for. The generated YAML matched almost exactly what I ended up deploying for this blog series.

Use Case 3: Explaining AWS Services

When setting up Amazon Managed Grafana, I asked: “What is the difference between Amazon Managed Grafana and self-hosted Grafana on EC2?”

Amazon Q gave me a comparison table covering cost model, authentication options, plugin availability, upgrade management, and HA configuration. The kind of answer that would take 30 minutes of documentation reading — delivered in 10 seconds. It even noted that Managed Grafana is not available in ap-south-1 (Mumbai) and suggested ap-southeast-1 (Singapore) — exactly the situation I encountered.

Use Case 4: CLI Command Suggestions

In AWS CloudShell, Amazon Q suggests commands as you type. When setting up the EKS cluster for this blog series, it suggested the exact aws eks update-kubeconfig command with the cluster name inferred from context. Every day this saves minutes of looking up exact parameter names and formats.

Use Case 5: Code Security Scanning

Amazon Q Developer scans your entire codebase for security vulnerabilities — not just the file you are editing. In one project it found:

Critical: Hardcoded AWS credentials in config.py (line 47)
High:     SQL injection vulnerability in user_query.py (line 123)
Medium:   Insecure random number generation in token_service.py (line 89)

Each finding included the exact code change needed to fix it — not just the problem, but the solution.

Amazon Q Developer Pricing

For individual AWS practitioners, the Free tier is a great starting point. For production teams doing security scanning, Pro pays for itself with the first security issue it catches.

My Honest Assessment After 6 Months

What Amazon Q Developer is great at:

• IAM policy review and least-privilege suggestions
• Generating boilerplate IaC (CloudFormation, CDK, Terraform)
• Explaining unfamiliar AWS services and APIs
• Catching obvious security issues before they reach production
• AWS CLI command suggestions in terminal

Where it needs improvement:

• Complex multi-service architecture suggestions
• Understanding very large codebases due to context window limits
• Custom organizational conventions and internal tooling

Net verdict: It has genuinely made me faster. Not by replacing my thinking — by handling the lookup and boilerplate work so I can focus on architecture decisions.

Conclusion

Amazon Q Developer is the AI pair programmer purpose-built for AWS. It knows IAM, it knows EKS, it knows CloudFormation. For AWS Ambassadors, SREs, and platform engineers working with AWS daily, it is one of the highest-leverage tools available today.

Try it in your next AWS project. Ask it to review your IAM policies first — I guarantee it will find something.

Prabhu Jayaseelan | AWS Ambassador | 14x AWS Certified Golden JacketHolder | Public Speaker

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