Building a dashboard with FastAPI? Let us review it.
Expert code review for dashboards built with FastAPI. We fix FastAPI-specific security gaps, optimize performance, and handle deployment. From $19.
Common FastAPI issues we find
Real problems from FastAPI codebases we've reviewed.
Blocking calls inside async endpoints
Synchronous database calls, file operations, or HTTP requests inside async def endpoints block the entire event loop, making your API unresponsive under load.
Missing authentication on endpoints
API routes that handle sensitive data or actions without any auth middleware — Depends() for authentication is simply not included in the route definition.
No CORS configuration
CORSMiddleware either missing (blocking all cross-origin requests) or set to allow_origins=['*'] (allowing any website to call your API).
Pydantic models without validation constraints
Request models that accept any string length, any number range, and any format. No Field() constraints, so invalid data flows through your system.
Dashboard challenges to solve
Key dashboard concerns that AI-generated code often misses.
Query performance at scale
AI-generated dashboards run raw database queries on every page load. With thousands of rows, these queries take seconds or minutes instead of milliseconds. You need materialized views, pre-aggregated data, proper indexing, and caching to keep dashboards responsive.
Data accuracy
A dashboard that shows wrong numbers is worse than no dashboard at all. AI tools generate SQL aggregations that look correct but miss edge cases — timezone handling, duplicate records, null values, and off-by-one errors in date ranges produce silently incorrect metrics.
Access control and data exposure
Dashboards display sensitive business data. AI tools often skip role-based access, meaning anyone with the URL can see revenue figures, customer data, or operational metrics. Different team members need different data visibility levels.
Real-time vs. cached data
Some metrics need to be live (active users, system status), while others can be cached (monthly revenue, historical trends). AI tools either make everything real-time (slow, expensive) or everything static (stale). You need a thoughtful caching strategy.
What we check
Key areas we review for FastAPI dashboard projects.
Query performance — response times under 500ms for all dashboard views
Data accuracy — aggregation logic, timezone handling, null values
Access control — role-based permissions enforced on API and database level
Caching strategy — appropriate refresh intervals for each metric type
Not sure if your app passes? Our code audit ($19) checks all of these and more.
Start with a self-serve audit
Get a professional review of your FastAPI dashboard project 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.
How it works
Tell us about your app
Share your project details and what you need help with.
Expert + AI audit
A human expert assisted by AI reviews your code within 24 hours.
Launch with confidence
We fix what needs fixing and stick around to help.
Frequently asked questions
Can you review a dashboard built with FastAPI?
Yes. We regularly audit FastAPI dashboard projects and understand the specific patterns and pitfalls of this combination. Our review covers security, performance, and deployment readiness.
What issues do you find in FastAPI dashboards?
Common issues include blocking calls inside async endpoints and missing authentication on endpoints on the FastAPI side, combined with dashboard-specific concerns like query performance at scale and data accuracy. We check for all of these and more.
How do I make my FastAPI dashboard production-ready?
Start with our code audit ($19) to get a prioritized list of issues. For FastAPI dashboard projects, the typical path is: fix security gaps, address dashboard-specific requirements, optimize FastAPI performance, then configure deployment. We provide a fixed quote after the audit.
How long does it take to audit a FastAPI dashboard?
Our code audit delivers a full report within 24 hours. For FastAPI dashboard projects, we check security, architecture, performance, and deployment readiness across all FastAPI-specific patterns. Fixes are scoped separately with a fixed quote.
Related resources
FastAPI by Use Case
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