Built a internal tool with Amazon Q Developer?
We'll make it production-ready.
Internal tools don't face the public internet, but they often have access to sensitive business data — customer records, financial data, operational metrics. AI tools build internal dashboards quickly, but the security bar is still high because a compromised internal tool can expose your entire business.
Internal Tool challenges in Amazon Q Developer apps
Building a internal tool with Amazon Q Developer is a great start — but these challenges need attention before launch.
Access control
Who can see what? Internal tools need role-based access — finance sees revenue data, support sees customer data, engineering sees system metrics. AI tools build the dashboard but rarely implement granular permissions.
Data sensitivity
Internal tools often connect directly to production databases. A bug that deletes records or a missing auth check that exposes customer PII can have serious legal and business consequences.
Network security
Internal tools should be behind a VPN or protected network, not on the public internet. AI tools deploy to public URLs by default. Proper network configuration prevents external access.
Audit logging
When someone modifies data through an internal tool, you need to know who did what and when. This is essential for debugging, compliance, and accountability.
Data mutations
Internal tools often write to production databases — updating orders, modifying user accounts, issuing refunds. These operations need confirmation dialogs, validation, and audit trails to prevent costly mistakes.
What we check in your Amazon Q Developer internal tool
Common Amazon Q Developer issues we fix
Beyond internal tool-specific issues, these are Amazon Q Developer patterns we commonly fix.
Overly permissive IAM policies generated with wildcard actions and resources
Amazon Q often generates IAM policies with `*` wildcards for actions or resources as a starting point, which violates the principle of least privilege. These policies should be scoped to specific actions and resource ARNs before being applied in production.
Lambda cold start latency not addressed in generated function configurations
Generated Lambda functions use default memory and timeout settings without considering cold start impact. Functions with heavy initialization code (loading models, establishing DB connections) need provisioned concurrency or memory tuning, which Amazon Q does not configure.
Generated CDK code creates AWS resources without cost estimation or tagging
Amazon Q CDK suggestions deploy resources without cost-tracking tags or budget guardrails, making it easy to inadvertently provision expensive resources (NAT gateways, multi-AZ RDS instances) without visibility into the cost impact.
DynamoDB access patterns generated without consideration for partition key hot spots
Generated DynamoDB table designs and query patterns sometimes use partition keys that distribute poorly under load — such as a status field with few values — creating hot partitions that throttle at scale.
Start with a self-serve audit
Get a professional review of your Amazon Q Developer internal tool at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
Frequently asked questions
Can I build a internal tool with Amazon Q Developer?
Amazon Q Developer is a great starting point for a internal tool. It handles the initial scaffolding well, but internal tools have specific requirements — access control and data sensitivity — that need professional attention before launch.
What issues does Amazon Q Developer leave in internal tools?
Common issues include: overly permissive iam policies generated with wildcard actions and resources, lambda cold start latency not addressed in generated function configurations, generated cdk code creates aws resources without cost estimation or tagging. For a internal tool specifically, these issues are compounded by the need for access control.
How do I make my Amazon Q Developer internal tool production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most Amazon Q Developer-built internal tools, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.
How much does it cost to fix a Amazon Q Developer-built internal tool?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger internal tool projects, we provide a custom fixed quote after the audit — no hourly billing.
Get your Amazon Q Developer internal tool production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.