# How to: 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.

![YouTube video](https://i.ytimg.com/vi/GJ0NepZmmv8/sddefault.jpg)

1.  #### Setting the Context
    
    Open Warp and enable **voice input** (optional) for hands-free prompting.
    
    Note
    
    Voice input is optional — only enable it if you prefer hands-free prompting.
    
    **Prompt**
    
    ```
    Use the warp-server-staging gcloud project and pull logsfor 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.  #### 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.
3.  #### 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 total980 info11 warning9 errors
    ```
    
    You can view or fast-forward execution, or stop the process at any point.
    
4.  #### 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.