Built a real-time app with GitHub Copilot?
We'll make it production-ready.
Real-time apps — chat, live collaboration, multiplayer features, live dashboards — have fundamentally different technical requirements than standard request-response web apps. Users expect sub-second updates, offline handling, and reliable message delivery. AI tools can set up a basic WebSocket connection, but production real-time features need connection management, message ordering, conflict resolution, and infrastructure that scales with concurrent users.
Real-time App challenges in GitHub Copilot apps
Building a real-time app with GitHub Copilot is a great start — but these challenges need attention before launch.
Connection management and reconnection
WebSocket connections drop constantly — network switches, phone sleep, server deploys. AI tools open a connection but don't handle disconnection, reconnection, or missed messages during downtime. Users see stale data or lose messages without knowing it.
Message ordering and delivery guarantees
Messages must arrive in order and must not be lost. Network issues can deliver messages out of sequence or duplicate them. AI-generated real-time code has no message ordering, no deduplication, and no delivery confirmation — which means lost messages and confused users.
Conflict resolution in collaborative editing
When two users edit the same content simultaneously, whose changes win? AI tools implement 'last write wins,' which silently discards one user's work. Production collaboration needs operational transforms or CRDTs to merge concurrent edits correctly.
Scaling concurrent connections
Each WebSocket connection holds server resources. A single server can handle hundreds of connections, but thousands require load balancing with sticky sessions, a pub/sub layer (like Redis), and horizontal scaling. AI tools don't implement any of this.
Presence and typing indicators
Showing who's online, who's typing, and who's viewing a document requires frequent presence updates that can overwhelm your server. These updates need throttling, batching, and efficient broadcast — details AI tools skip entirely.
Message persistence and history
Real-time messages need to be stored for later retrieval — chat history, edit history, activity logs. AI tools send messages through WebSockets but don't persist them, so refreshing the page loses the entire conversation.
Security in real-time channels
Every WebSocket message needs authentication and authorization. Who can send messages to this channel? Who can read them? AI tools often create open WebSocket endpoints where anyone can listen to or inject messages into any conversation.
What we check in your GitHub Copilot real-time app
Common GitHub Copilot issues we fix
Beyond real-time app-specific issues, these are GitHub Copilot patterns we commonly fix.
Insecure code patterns from training data
Copilot sometimes suggests patterns from its training data that are known to be insecure — like using eval(), innerHTML, or outdated crypto functions.
Hardcoded secrets in suggestions
Copilot occasionally suggests placeholder API keys or credentials that look real and get committed to version control.
Inconsistent code style across files
Different completions use different patterns — sometimes callbacks, sometimes async/await, sometimes .then(). The codebase becomes inconsistent over time.
Subtly incorrect logic
Copilot completions often look correct but contain off-by-one errors, wrong comparison operators, or missed edge cases that cause intermittent bugs.
Start with a self-serve audit
Get a professional review of your GitHub Copilot real-time app 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 real-time app with GitHub Copilot?
GitHub Copilot is a great starting point for a real-time app. It handles the initial scaffolding well, but real-time apps have specific requirements — connection management and reconnection and message ordering and delivery guarantees — that need professional attention before launch.
What issues does GitHub Copilot leave in real-time apps?
Common issues include: insecure code patterns from training data, hardcoded secrets in suggestions, inconsistent code style across files. For a real-time app specifically, these issues are compounded by the need for connection management and reconnection.
How do I make my GitHub Copilot real-time app production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most GitHub Copilot-built real-time apps, 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 GitHub Copilot-built real-time app?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger real-time app projects, we provide a custom fixed quote after the audit — no hourly billing.
Get your GitHub Copilot real-time app production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.