# Technical Data Extraction: Cluster Performance and Network Traffic Analysis
## 1. Document Overview
This image is a multi-paneled time-series line chart used for root cause analysis in a computing cluster environment. It correlates a high-level alarm (Cluster CPU Usage) with the network traffic of four specific Virtual Machines (VM1 through VM4) over a 15-hour period.
## 2. Component Isolation
### A. Header/Y-Axis Labels (Left Side)
The chart is divided into five vertically stacked sub-plots, each with a specific label:
1. **Cluster CPU Usage (Alarm KPI)**: The primary metric being monitored.
2. **Network Traffic of VM1 (Root Cause)**: Identified as the source of the anomaly.
3. **Network Traffic of VM2**: Comparative metric.
4. **Network Traffic of VM3**: Comparative metric.
5. **Network Traffic of VM4**: Comparative metric.
### B. X-Axis (Footer)
The horizontal axis represents time on the date **08-26**. The markers are:
* `08-26 07:00`
* `08-26 10:00`
* `08-26 13:00`
* `08-26 16:00`
* `08-26 19:00`
* `08-26 22:00`
## 3. Data Series Analysis and Trend Verification
### Series 1: Cluster CPU Usage (Alarm KPI)
* **Color**: Dark Red / Maroon.
* **Visual Trend**: Highly erratic with frequent, sharp vertical spikes reaching a consistent maximum ceiling. There are approximately 7-8 major "burst" periods of high activity.
* **Correlation**: The spikes in this series align precisely with the activity peaks in the VM1 series.
### Series 2: Network Traffic of VM1 (Root Cause)
* **Color**: Pink / Magenta.
* **Visual Trend**: Characterized by distinct "plateau" blocks of high traffic.
* **Key Data Points**:
* First peak: Just before 07:00.
* Second peak: Between 07:00 and 10:00.
* Major sustained peak: Around 10:30.
* Major sustained peak: Around 13:30.
* Smaller peaks: Between 16:00 and 19:00.
* Final peak: Just before 22:00.
* **Observation**: This series is the only one that mirrors the timing of the "Cluster CPU Usage" spikes perfectly, justifying the "(Root Cause)" label.
### Series 3: Network Traffic of VM2
* **Color**: Blue.
* **Visual Trend**: Flat/low activity for the first half of the day, followed by high-frequency oscillations starting around 16:00, ending with a high-level sustained plateau after 21:00.
* **Observation**: Does not correlate with the initial CPU spikes seen in the first panel.
### Series 4: Network Traffic of VM3
* **Color**: Blue.
* **Visual Trend**: Binary/Step function behavior. The traffic is either at a baseline or at a fixed high plateau with perfectly vertical transitions.
* **Key Data Points**: High traffic blocks occur at ~08:30, ~12:00, ~14:30, ~18:30, and a final sustained jump at ~21:30.
* **Observation**: These regular intervals suggest a scheduled task or batch process, but they do not align with the erratic CPU spikes.
### Series 5: Network Traffic of VM4
* **Color**: Blue.
* **Visual Trend**: High initial activity before 07:00, followed by low activity with minor bumps until 19:00. After 19:00, it shows intense, high-amplitude noise/volatility.
* **Observation**: The late-day volatility does not match the specific timing of the CPU alarm peaks.
## 4. Summary of Findings
The visualization demonstrates a direct temporal correlation between **Cluster CPU Usage** and **Network Traffic of VM1**. Whenever VM1 experiences a surge in network traffic (Pink line), the Cluster CPU Usage (Red line) hits its peak alarm threshold. The traffic patterns of VM2, VM3, and VM4 show significant activity at different times, but their patterns do not synchronize with the Cluster CPU Alarm KPI, effectively ruling them out as the primary root cause during the observed spikes.
