AWS EC2实例使用监控咨询：跨Windows/Linux的进程追踪工具选型

Hey there! Let's break down the tools and approaches you can use to track what's running on your AWS EC2 instances—both Windows and Linux—plus how to set up agents for ongoing process listing, especially since you're managing students with elevated permissions. We'll also cover specific checks for things like Python usage or Ethereum mining.

Built-in Tools (No Extra Installs Needed) #

• Tasklist Command Line: Run tasklist /v /fo csv > process_report.csv to export a detailed CSV of all processes, including usernames, window titles, and memory usage. The /v flag adds verbose details that help spot suspicious activity (like unknown processes running as admin).
• PowerShell's Get-Process: For more flexibility, use Get-Process | Select-Object Name, Id, Path, CPU, StartTime | Export-Csv -Path "process_report.csv". This lets you filter and export specific fields—critical for verifying if Python is running, or if a process has a legitimate install path (mining tools often live in temp folders).

Third-Party Tools (Deeper Insights) #

• Process Explorer (Sysinternals): A more powerful alternative to Task Manager. It shows parent-child process relationships, loaded DLLs, and network connections—perfect for digging into whether an "unknown.exe" is actually a mining tool.
• Windows Sysmon: A system monitoring service that logs process creation, network activity, and file changes. Configure it with rules to flag suspicious behavior (like processes spawning mining tools) and send logs to AWS CloudWatch or S3 for long-term analysis.

Built-in Tools (No Extra Installs Needed) #

• ps Command: Run ps aux to list all processes with full command-line arguments—great for spotting Python scripts or mining commands. Use pgrep python or pgrep ethminer to quickly check if specific processes are running.
• top/htop: Real-time resource monitors. Mining processes will almost always max out CPU/GPU resources, so keep an eye on sustained high usage. htop is a more user-friendly, color-coded version of top.
• lsof: Use lsof -i to check which processes are making network connections—mining tools often connect to known mining pool addresses (you can cross-reference with public lists of mining pool endpoints).

Third-Party Tools (Scalable Monitoring) #

• Node Exporter + Prometheus + Grafana: Node Exporter collects system metrics (including process lists) from Linux instances, Prometheus stores the data, and Grafana builds interactive dashboards. This setup lets you visualize process activity across all your instances in one place.
• iftop: A network traffic monitor that shows real-time bandwidth usage per process. Mining tools will have consistent outbound traffic to mining pool servers, making this a quick way to spot anomalies.

If you need to regularly collect process lists across multiple instances (without manually logging into each one), these approaches work for both Windows and Linux:

AWS Systems Manager (SSM) #

Most AWS EC2 instances come pre-installed with the SSM Agent. You can use SSM Run Command to execute scripts across all instances in a fleet:

• For Windows: Run a PowerShell script that collects processes and uploads the report to S3:

  Get-Process | Select-Object Name, Id, Path, CPU | Export-Csv -Path "$env:TEMP\process_report.csv"
  aws s3 cp "$env:TEMP\process_report.csv" s3://your-report-bucket/$(hostname)-processes.csv
  

• For Linux: Run a bash script to do the same:

  ps aux > /tmp/process_report.txt
  aws s3 cp /tmp/process_report.txt s3://your-report-bucket/$(hostname)-processes.txt
  

This avoids exposing instance credentials directly to students, since SSM uses IAM roles for authentication.

CloudWatch Agent #

Install the CloudWatch Agent on each instance to collect custom metrics and logs, including process activity. You can configure it to send process lists to CloudWatch Logs, then use CloudWatch Insights to query and generate reports (e.g., "show all instances running Python" or "flag instances with processes named 'ethminer'").

Custom Python Agent #

If you need full control over what's collected, build a simple Python script using the psutil library (cross-platform):

import psutil
import boto3

def collect_processes():
    processes = []
    for proc in psutil.process_iter(['name', 'exe', 'cpu_percent']):
        try:
            proc_info = proc.info
            # Check for Python or mining-related processes
            if 'python' in proc_info['name'].lower() or 'miner' in proc_info['name'].lower():
                processes.append(proc_info)
        except (psutil.NoSuchProcess, psutil.AccessDenied):
            continue
    return processes

# Upload results to S3
s3 = boto3.client('s3')
process_data = str(collect_processes())
s3.put_object(Bucket='your-report-bucket', Key=f"{psutil.hostname()}_processes.txt", Body=process_data)

Schedule this script to run periodically with Task Scheduler (Windows) or cron (Linux).

• Resource Usage: Mining tools will consistently use 90%+ of CPU/GPU resources.
• Process Names: Look for names like ethminer, claymore, xmrig, or generic names like miner.exe.
• Network Connections: Mining processes connect to known mining pool domains/IPs—use lsof (Linux) or Process Explorer (Windows) to check outbound connections.
• File Paths: Mining tools often run from temporary directories (like /tmp on Linux or %TEMP% on Windows) instead of legitimate program folders.

内容的提问来源于stack exchange，提问作者eze1981