How to: Analyze Cloud Run Logs (gcloud)

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.

   Note

   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.

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 total
   980 info
   11 warning
   9 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.