Based on the provided Grafana dashboard image (utilizing the popular Node Exporter Full template), here is a breakdown of what is happening on this Linux server (cvm-srv51).

The Main Takeaway: CPU Bottleneck

Your server is currently under a heavy CPU bottleneck, while memory and disk resources are mostly relaxed. Around 12:43 to 12:45, there was a brief dip where the load dropped significantly, but it immediately spiked back up to its previous high levels.

Detailed Metric Breakdown

1. Quick CPU / Mem / Disk (Gauges)

• CPU Busy (95.2%): Your CPU is running almost at maximum capacity. The red ring indicates this is in a critical threshold.
• Sys Load (136.3%): This represents a system load average that exceeds the server’s capacity. Since the server has 4 CPU Cores (shown in the info box), a 100% load capacity would mean a load average of 4.0. Running at 136.3% means the CPU queue is constantly backed up, and processes are waiting for CPU time.
• RAM Used (17.2%) & SWAP Used (0.0%): Out of 23 GiB available, memory usage is very low and healthy. SWAP isn’t being touched, meaning this is strictly a compute problem, not a memory-starvation problem.
• Root FS Used (32.7%): Storage space is perfectly fine, with plenty of room left on the root filesystem.

2. Historical Graphs (Last 15 Minutes)

• CPU Basic: The large blue block dominating the graph represents Busy User space. This means the high CPU usage is being driven by user-level applications or services (e.g., a heavy application, database queries, a running script, or containerized apps), rather than kernel overhead (Busy System) or waiting for hardware (Busy Iowait).
• Memory Basic: A completely flat line showing steady, low memory utilization.
• Network Traffic Basic: There is a noticeable drop in network traffic that perfectly correlates with the dip in CPU usage around 12:44. When network traffic resumed, CPU usage shot back up. This suggests that incoming network requests or data transfers are likely triggering the high CPU workload.

Next Steps for Troubleshooting

Because the CPU is being hammered by user-space applications linked to network activity, you should log into the server (cvm-srv51) via SSH and investigate:

1. Run top or htop: Check which specific processes are consuming the most CPU.
2. Inspect Containers: Since the network graph lists several virtual interfaces (like docker0 and veth...), it’s highly likely this server is running Docker containers. Use docker stats to see which container is pulling all the compute.
3. Check Application Logs: Match the timeline (the dip at 12:44) against your application or web server logs to see what traffic paused or restarted at that moment.