HTTP 503 cloud resource_error ai_generated partial

Cloud Run: Request failed with 'memory limit exceeded' during cold start, even though memory usage is below limit

ID: cloud/gcp-cloud-run-cold-start-memory-threshold

Also available as: JSON · Markdown · 中文
78%Fix Rate
83%Confidence
1Evidence
2023-11-01First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
Cloud Run (fully managed) 2023-11 active — — —
gcloud CLI 460.0.0 active — — —

Root Cause

During cold start, Cloud Run allocates memory for the container and may temporarily exceed the configured memory limit due to initialization overhead (e.g., loading libraries, connecting to databases), leading to OOM kills.

generic

中文

在冷启动期间，Cloud Run 为容器分配内存，由于初始化开销（例如加载库、连接数据库）可能会暂时超过配置的内存限制，导致 OOM 杀死。

Official Documentation

https://cloud.google.com/run/docs/configuring/memory-limits

Workarounds

  1. 85% success Set a higher memory limit (e.g., 512 MiB) for the Cloud Run service, and use the --concurrency flag to limit concurrent requests during cold start. Example: gcloud run deploy myservice --memory=512Mi --concurrency=1 
    Set a higher memory limit (e.g., 512 MiB) for the Cloud Run service, and use the --concurrency flag to limit concurrent requests during cold start. Example: gcloud run deploy myservice --memory=512Mi --concurrency=1
  2. 75% success Optimize the application's startup code to defer heavy initialization (e.g., lazy-load libraries, use connection pooling) to reduce the memory spike. 
    Optimize the application's startup code to defer heavy initialization (e.g., lazy-load libraries, use connection pooling) to reduce the memory spike.
  3. 90% success Enable 'CPU always allocated' to keep the container warm and avoid cold starts entirely. 
    Enable 'CPU always allocated' to keep the container warm and avoid cold starts entirely.

中文步骤

  1. 为 Cloud Run 服务设置更高的内存限制（例如 512 MiB），并使用 --concurrency 标志在冷启动期间限制并发请求。示例：gcloud run deploy myservice --memory=512Mi --concurrency=1
  2. 优化应用程序的启动代码，延迟执行重型初始化（例如懒加载库、使用连接池），以减少内存峰值。
  3. 启用 'CPU always allocated' 以保持容器温暖，完全避免冷启动。

Dead Ends

Common approaches that don't work:

  1. 40% fail

    The issue is a transient spike; increasing limit helps but may not be cost-effective.

  2. 55% fail

    The spike is often due to runtime dependencies, not image size.