Analyzing Linux System Performance Data

vikash11

As a data analyst, I'm tasked with analyzing system performance data from a Linux server to identify potential issues and optimize system resources. I have collected data using tools like sar, vmstat, and iostat and stored it in CSV files.

Here's a simplified example of the data structure:

• timestamp (datetime): The timestamp of the data point.
• cpu_usage_percent (float): CPU usage percentage at that moment.
• memory_usage_percent (float): Memory usage percentage.
• disk_io_rate (float): Disk I/O rate in KB/s.

I want to perform the following analyses:

• CPU Usage Patterns: Identify patterns in CPU usage throughout the day and week. Are there specific times when CPU usage spikes or remains consistently high?

• Memory Trends: Analyze memory usage trends over time. Are there memory leaks or periods of excessive memory consumption?

• Disk I/O Optimization: Identify periods of high disk I/O activity and potential bottlenecks. Are there specific processes or directories contributing to heavy disk I/O?

• Performance Summary: Provide a summary report with key performance metrics and insights.

I'm searching for advice on how to effectively analyze this Linux system performance statistics using Python (or other tools). What specific tools or strategies can I use to visualize and understand this data? I looked online for a solution on several, but I was unable to locate anything; any code samples or suggested techniques would be highly appreciated. I appreciate your knowledge in analyzing Linux system performance.