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.

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.