Monitor your CPU usage in your Python application

When building a Python application, we often have to think and deal with performance issues. Performance is a critical aspect of any application and can significantly affect the user experience. One of the most common performance issues for Python applications is when the workload is CPU bound. This means that the application spends most of its time waiting for the CPU to complete a task.

In such cases, monitoring our Python application's CPU usage and setting up a system to track when use goes above a certain threshold is essential. This way, we can always be aware of the performance of our application. Furthermore, in cases of a performance issue, for example, when the CPU usage goes above a certain threshold, we can take immediate action and fix the problem before it becomes a significant issue.

Fortunately, here at LogSnag, we have created a powerful solution for this problem. LogSnag is a powerful, real-time event tracking tool that works seamlessly with Python. With LogSnag, you can set up event tracking for anything you want and monitor things like your CPU usage in real-time. In addition, you can set up a rule to notify you and your team when the CPU usage goes above a certain threshold. This way, you will always be aware of the performance of your application, and you can take immediate action if needed.

Setting up LogSnag

1. Sign up for a free LogSnag account.
2. Create your first project from the dashboard.
3. Head to settings and copy your API token.

Python code snippets

To track your CPU usage, you can use the following code snippet Please don't forget to replace the YOUR_API_TOKEN with your API token and update the project and channel names.

import http.client
import json

conn = http.client.HTTPSConnection("api.logsnag.com")
payload = json.dumps({
  "project": "my-saas",
  "channel": "status",
  "event": "High CPU Usage",
  "description": "CPI usage has been over 90% for the last 5 minutes",
  "icon": "🚨",
  "notify": True
})
headers = {
  'Content-Type': 'application/json',
  'Authorization': 'Bearer YOUR_API_TOKEN'
}
conn.request("POST", "/v1/log", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))

import requests
import json

url = "https://api.logsnag.com/v1/log"

payload = json.dumps({
  "project": "my-saas",
  "channel": "status",
  "event": "High CPU Usage",
  "description": "CPI usage has been over 90% for the last 5 minutes",
  "icon": "🚨",
  "notify": True
})
headers = {
  'Content-Type': 'application/json',
  'Authorization': 'Bearer YOUR_API_TOKEN'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

Python integration details

We believe that event tracking should be simple and accessible to every developer and team. Therefore, we have worked hard to create the next generation of event tracking tools. As a result, LogSnag is flexible and easy to use, making it a great companion for your Python applications.

In addition to real-time event tracking, LogSnag provides powerful features such as cross-platform push notifications, event filtering, user and product journeys, charts, insights, and more.

LogSnag provides a generous free plan to get you started with event tracking. You can also check out our pricing page to see our paid plans. So please give us a try and let us know what you think!

Other use-cases for LogSnag

1. Monitor your CI/CD build status for your Python application
2. Monitor when database goes down in your Python application
3. Monitor high disk usage in your Python application
4. Monitor when a user changes their email address in your Python application
5. Monitor failed logins in your Python application
6. Monitor failed payments for your Python application
7. Monitor memory usage in your Python application
8. Monitor MySQL downtime in your Python application
9. Monitor when a new feature is used in your Python application
10. Monitor your Postgres downtime in your Python application
11. Monitor Redis downtime in your Python application
12. Monitor suspicious activity in your Python application
13. Monitor when a user exceeds the usage limit for your Python service
14. Monitor when a user is being rate limited in your Python application
15. Get a notification when your Python code is done executing
16. Send push notifications to your phone or desktop using Python
17. Track canceled subscriptions in your Python application
18. Track your Python cron jobs
19. Track when a file is uploaded to your Python application
20. Track when a form is submitted to your Python application
21. Track payment events via Python
22. Track user sign in events in Python
23. Track user signup events via Python
24. Track waitlist signup events via Python