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cloudrun-development

Develop CloudBase Run backends in function or container mode.

Updated Dec 8, 2025
Search Tags:#ai-agent#backend-development#cloudrun#cloudbase-run#function-mode#container-mode
One-click install
npx skills add https://github.com/sycsky/Soncho --skill cloudrun-development-sycsky
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cloudrun-development
Source: https://github.com/sycsky/Soncho/tree/main/.codebuddy/rules/tcb/rules/cloudrun-development-skill
Command: npx skills add https://github.com/sycsky/Soncho --skill cloudrun-development-sycsky

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

CloudBase Run backend development requires architecting services that can handle long-lived connections, multi-language stacks, and flexible runtime environments. This skill provides a structured, mode-aware approach to building, testing, and deploying such backends using Function mode or Container mode.

Core Features & Use Cases

  • Mode selection between Function mode for fast-start, low-latency workloads and Container mode for arbitrary runtimes with Docker support.
  • End-to-end lifecycle: initialize a local project, download existing code, run locally (Function mode), deploy to CloudRun, and manage AI agents.
  • Security and scalability guidelines: enforce PORT binding, statelessness, minimal dependencies, resource constraints, and private/public access controls.

Quick Start

Choose the appropriate mode (Function for fast start or Container for custom runtimes), then initialize and deploy a CloudBase Run project.

Frequently Asked Questions about cloudrun-development

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy a backend to CloudBase Run?▼

To deploy a backend to CloudBase Run, initialize a local project, select Function or Container mode, and execute the deploy workflow. This enforces port binding and stateless design for successful cloud deployment.

What is the difference between Function mode and Container mode for CloudBase Run?▼

Function mode supports fast-start, low-latency workloads, whereas Container mode enables arbitrary runtimes with Docker support. Choosing the right mode ensures optimal performance for your specific backend architecture.

Can I use CloudBase Run for AI agent workloads with long-lived connections?▼

Yes, CloudBase Run supports AI agent workloads and long-lived connections. You can use the createAgent workflow to build and deploy intelligent agents while maintaining stateless design and controlled network access.

How do I structure a stateless backend for CloudBase Run?▼

Structure a stateless backend by enforcing PORT binding, minimizing dependencies, and adhering to resource constraints. This design ensures your service scales properly within the CloudBase Run environment.

Does CloudBase Run support custom runtimes and multi-language stacks?▼

Yes, CloudBase Run supports custom runtimes and multi-language stacks through Container mode. You can deploy services using Docker images to accommodate your specific language and runtime requirements.

What are the limitations when developing backends with CloudBase Run?▼

Limitations include mandatory statelessness, strict PORT binding, resource constraints, and controlled private or public network access. These boundaries ensure scalable but restricted execution environments for your workloads.

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