# Source: https://docs.warp.dev/university/developer-workflows/devops/how-to-analyze-cloud-run-logs-gcloud.md

# 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.

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**Setting the Context**

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

{% hint style="info" %}
Voice input is optional — only enable it if you prefer hands-free prompting.
{% endhint %}

**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.
```

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**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.
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**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.
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**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.
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