Built with Zed AI? Deploy it to Google Cloud Platform.
Step-by-step deployment help for Zed AI-built apps on Google Cloud Platform. We fix deployment issues, configure Google Cloud Platform correctly, and get your app live in production. From $19.
Zed AI issues we fix before deploying
Problems specific to Zed AI's code generation that affect Google Cloud Platform deployments.
Inline edits applied directly to files without a diff review step
Zed AI applies inline edits immediately to open files, which makes changes fast but difficult to review as a unit before they are applied. Mistakes in multi-line edits can be harder to undo cleanly compared to tools that show a diff preview.
Fewer security guardrails than more established AI coding assistants
As a newer tool in a smaller ecosystem, Zed AI has less institutional knowledge built into its guardrails — it is less likely to flag insecure patterns in generated code like missing authentication or unsafe deserialization.
Limited codebase context compared to dedicated AI coding assistants
Zed AI operates primarily on open files and the immediate context rather than indexing the full codebase, so suggestions may not account for existing utilities, established patterns, or dependencies defined elsewhere in the project.
Rust-specific suggestions may not account for lifetime and ownership rules
Generated Rust code from Zed AI sometimes produces code that compiles but has ownership patterns that are overly restrictive or introduce unnecessary clones, requiring a Rust-savvy developer to optimize.
Google Cloud Platform deployment issues we check for
Common Google Cloud Platform problems that break AI-generated apps in production.
Cloud Run container port misconfigured
Cloud Run injects the PORT environment variable, but AI-generated Dockerfiles hardcode port 3000 or 8080, causing the container to fail health checks and never become healthy.
Service account with Owner role
AI-generated deployment scripts use the default compute service account with overly broad Owner permissions instead of custom roles scoped to required APIs.
Cloud Run concurrency set to 1
Default concurrency of 1 request per container instance causes excessive scaling and costs. AI tools don't optimize concurrency settings for the application's actual threading model.
VPC connector not attached for private resources
Cloud Run services can't reach Cloud SQL or Memorystore instances in a VPC because AI-generated configs omit the Serverless VPC Access connector.
Start with a self-serve audit
Get a professional review of your Zed AI project before deploying to Google Cloud Platform.
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 Zed AI-built app to Google Cloud Platform?
Yes. We regularly deploy Zed AI-generated projects to Google Cloud Platform. We handle the platform-specific configuration, fix deployment errors, and ensure your app runs reliably in production on Google Cloud Platform.
What Google Cloud Platform issues do Zed AI projects typically have?
Zed AI projects commonly have inline edits applied directly to files without a diff review step and fewer security guardrails than more established ai coding assistants. When deploying to Google Cloud Platform, these combine with platform-specific issues like cloud run container port misconfigured and service account with owner role.
How do I get my Zed AI project live on Google Cloud Platform?
Start with our code audit ($19) to get a prioritized list of deployment blockers. For Zed AI-built projects targeting Google Cloud Platform, the typical path is: fix Zed AI-specific code issues, configure Google Cloud Platform settings correctly, then deploy. We provide a fixed quote after the audit.
Can you handle the full deployment of my Zed AI app to Google Cloud Platform?
Yes. We handle end-to-end deployment: auditing your Zed AI codebase, fixing deployment blockers, configuring Google Cloud Platform correctly, setting up environment variables, and getting your app live in production. Start with our code audit ($19).
Related resources
Deploy Zed AI Apps
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Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.