Skip to content

Guides > DevOps & infrastructure

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.

Open in ChatGPT ↗
Ask ChatGPT about this page
Open in Claude ↗
Ask Claude about this page
Copied!

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

  1. Open Warp and enable voice input (optional) for 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.
  2. 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.
  3. 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.

  4. 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.