使用方法
- 复制安装命令，在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物，并对照来源检查输出。
npx skills add https://github.com/sickn33/agentic-awesome-skills --skill gcp-cloud-run开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。
按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。
GCP Cloud Run
Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub.
Detailed Guide
Read the detailed guide before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.
Calculate memory including /tmp usage
# cloudbuild.yaml
steps:
- name: 'gcr.io/cloud-builders/gcloud'
args:
- 'run'
- 'deploy'
- 'my-service'
- '--memory=1Gi' # Include /tmp overhead
- '--image=gcr.io/$PROJECT_ID/my-service'Monitor memory usage
import psutil
import logging
def log_memory():
memory = psutil.virtual_memory()
logging.info(f"Memory: {memory.percent}% used, "
f"{memory.available / 1024 / 1024:.0f}MB available")Concurrency=1 Causes Scaling Bottlenecks
Severity: HIGH
Situation: Setting concurrency to 1 for request isolation
Symptoms: Auto-scaling creates many container instances. High latency during traffic spikes. Increased cold starts. Higher costs from more instances.
Why this breaks: Setting concurrency to 1 means each container handles only one request at a time. During traffic spikes:
- 100 concurrent requests = 100 container instances
- Each instance has cold start overhead
- More instances = higher costs
- Scaling takes time, requests queue up
This should only be used when:
- Processing is truly single-threaded
- Memory-heavy per-request processing
- Using thread-unsafe libraries
Recommended fix:
When to Use
Use this skill when the request clearly matches the capabilities and patterns described above.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
