Built with JetBrains AI? Deploy it to Heroku.
Step-by-step deployment help for JetBrains AI-built apps on Heroku. We fix deployment issues, configure Heroku correctly, and get your app live in production. From $19.
JetBrains AI issues we fix before deploying
Problems specific to JetBrains AI's code generation that affect Heroku deployments.
Over-engineered enterprise patterns generated for simple startup use cases
JetBrains AI is trained on enterprise Java and Kotlin patterns, so it tends to generate verbose factory patterns, abstract base classes, and interface hierarchies for problems that could be solved with a simple function in a startup context.
Generated Spring Boot code includes unnecessary security exposure in default configurations
Spring Boot applications generated by JetBrains AI may include actuator endpoints, management ports, or H2 console access enabled in configurations that should be disabled or secured before production deployment.
Verbose boilerplate code increases bundle size and maintenance overhead
Java code generation in particular produces verbose getter/setter patterns, checked exception hierarchies, and XML configuration that modern Kotlin or Lombok-based approaches would handle with a fraction of the code.
Generated unit tests use JUnit 4 patterns in projects that have moved to JUnit 5
JetBrains AI sometimes generates JUnit 4 annotations (@Test from org.junit, @Before, @After) in projects configured for JUnit 5, causing compilation errors and requiring annotation migration.
Heroku deployment issues we check for
Common Heroku problems that break AI-generated apps in production.
Free dyno sleeping causes cold starts
Eco and Basic dynos sleep after 30 minutes of inactivity. AI-generated apps with webhook receivers or background jobs break when the dyno is asleep.
Ephemeral filesystem loses uploaded files
AI tools save user uploads and generated files to the local filesystem, but Heroku's ephemeral FS wipes all changes on every dyno restart or deploy.
Database connection pool exhaustion
Heroku Postgres plans have strict connection limits (20 on Hobby). AI-generated apps open a new connection per request, exhausting the pool under moderate traffic.
Procfile missing or incorrect
AI-generated projects lack a Procfile, causing Heroku to guess the start command. For non-standard setups, this guess is often wrong.
Start with a self-serve audit
Get a professional review of your JetBrains AI project before deploying to Heroku.
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 deploy a JetBrains AI-built app to Heroku?
Yes. We regularly deploy JetBrains AI-generated projects to Heroku. We handle the platform-specific configuration, fix deployment errors, and ensure your app runs reliably in production on Heroku.
What Heroku issues do JetBrains AI projects typically have?
JetBrains AI projects commonly have over-engineered enterprise patterns generated for simple startup use cases and generated spring boot code includes unnecessary security exposure in default configurations. When deploying to Heroku, these combine with platform-specific issues like free dyno sleeping causes cold starts and ephemeral filesystem loses uploaded files.
How do I get my JetBrains AI project live on Heroku?
Start with our code audit ($19) to get a prioritized list of deployment blockers. For JetBrains AI-built projects targeting Heroku, the typical path is: fix JetBrains AI-specific code issues, configure Heroku settings correctly, then deploy. We provide a fixed quote after the audit.
Can you handle the full deployment of my JetBrains AI app to Heroku?
Yes. We handle end-to-end deployment: auditing your JetBrains AI codebase, fixing deployment blockers, configuring Heroku correctly, setting up environment variables, and getting your app live in production. Start with our code audit ($19).
Related resources
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Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.