Server Metrics Explained: How to Monitor Server Performance in CloudRaptor (CPU & RAM Guide)

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Want to understand how your server is performing in real time? In this tutorial, we break down server monitoring inside CloudRaptor so you can easily track CPU and RAM usage.

The Monitoring tab in CloudRaptor gives you live performance insights, helping you detect issues early and make better scaling decisions.

In this step-by-step guide, you’ll learn how to access server metrics, understand CPU usage across cores, and monitor memory usage effectively.

We also explain what normal vs high usage looks like—and when it’s time to upgrade your server.

📊 What You’ll Learn
How to access the Monitoring tab
Understanding CPU usage (multi-core explained)
Reading CPU percentage and spikes
Monitoring RAM usage and limits
Identifying performance bottlenecks
When to scale your server

⚙️ Key Concepts Explained
CPU Usage
Learn how percentage works across multiple cores (e.g., 400% on a 4-core server)
RAM Usage
Track memory consumption and avoid performance slowdowns
Real-Time Graphs
View server activity over time for better analysis
Monitoring Source
Metrics collected via CloudRaptor Agent or SSH

⚡ Best Practices
Short CPU spikes = normal
Constant high CPU = consider scaling
RAM above 90% = potential performance issue
Use the CloudRaptor Agent for real-time monitoring

⚠️ Requirements
Server must be active
Docker should be running
CloudRaptor Agent must be connected

🎯 Key Takeaway

With CloudRaptor monitoring, you can track performance in real time, prevent issues before they happen, and scale your infrastructure intelligently.

📩 Need help? Contact support at support@cloudraptor.io

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