跳到正文
FunCoding

搜索

搜索文档、文章、Skill 和 MCP

Analyze Cloud Run logs (gcloud)

Use Warp to pull, organize, and analyze Cloud Run production logs by severity with natural language prompts and automated Python scripts.

Learn how to use Warp to retrieve, organize, and analyze production logs from your cloud servers — all with natural language prompts.

  1. Setting the context

    Open Warp and enable voice input (optional) for hands-free prompting.

Voice input is optional — only enable it if you prefer hands-free prompting.

Prompt

Use the warp-server-staging gcloud project and pull logs
for the last 10 minutes from the warp-server Cloud Run instance.
Organize them by info, warning, and error levels.
Create a histogram across message types,
and highlight the most concerning errors to investigate.
  1. Warp’s agent in action

    After you hit Enter:

    • Warp detects the command as an Agent Mode request.
    • It gathers project context (warp-server-staging).
    • Executes the necessary gcloud logging queries automatically.
    • Writes retrieved data to a temporary file for processing.
  2. Automated analysis

    Warp’s agent generates a Python script on the fly to:

    • Parse logs
    • Count messages by severity
    • Output summary metrics

    Example output:

    1,000 log entries total
    980 info
    11 warning
    9 errors

    You can view or fast-forward execution, or stop the process at any point.

  3. Reviewing results

    Warp outputs a readable histogram and highlights anomalies.
    For example:

    “Gemini AI error messages detected — worth reviewing.”

    You can expand each log group interactively or inspect the temporary Python code for debugging.