Monitor high disk usage in your Python application

LogSnag makes it easy to track your Python application and monitor when it is experiencing high disk usage.

When building Python applications, we often end up dealing with persistent data in one way or another. This can be a simple JSON, CSV, or text file on disk, uploading files to cloud storage such as S3 or Google Cloud Storage, or even storing data in a database such as MongoDB or MySQL. In all of these cases, disk usage is a critical aspect of our Python application and can significantly affect the user experience.

Therefore, monitoring our Python application's disk usage is essential, whether in the local environment or somewhere in the cloud. This is critical as going over a certain threshold can cause our application to crash or become unavailable, resulting in a significant loss of revenue and user experience.

LogSnag is a powerful event tracking tool that works seamlessly with Python and makes it trivial to track any important event in our Python application in real time. For example, one common use case for LogSnag is tracking disk usage in real-time and setting up rules to notify our team and us when our disk usage has exceeded a certain threshold. This way, we can always be aware of the performance of our application and 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

Use the following code to connect LogSnag to your Python application and track disk usage: Please replace the YOUR_API_TOKEN with your API token and update the project and channel names.

Using Python with http.client
import http.client
import json

conn = http.client.HTTPSConnection("api.logsnag.com")
payload = json.dumps({
  "project": "my-saas",
  "channel": "status",
  "event": "High Disk Usage",
  "description": "The disk usage is high.",
  "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"))
Using Python with Requests
import requests
import json

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

payload = json.dumps({
  "project": "my-saas",
  "channel": "status",
  "event": "High Disk Usage",
  "description": "The disk usage is high.",
  "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

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. Via LogSnag, you can get better insight into your Python application and track anything important all in one place and in real time.

We strive to make event tracking 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.

Other use-cases for LogSnag

  1. Track payment events via Python

  2. Track user signup events via Python

  3. Track your Python cron jobs

  4. Track waitlist signup events via Python

  5. Track user sign in events in Python

  6. Get a notification when your Python code is done executing

  7. Monitor when a user exceeds the usage limit for your Python service

  8. Monitor when a new feature is used in your Python application

  9. Monitor suspicious activity in your Python application

  10. Monitor when a user is being rate limited in your Python application

  11. Monitor when database goes down in your Python application

  12. Monitor your CPU usage in your Python application

  13. Monitor memory usage in your Python application

  14. Track when a file is uploaded to your Python application

  15. Track when a form is submitted to your Python application

  16. Track canceled subscriptions in your Python application

  17. Monitor failed payments for your Python application

  18. Monitor your CI/CD build status for your Python application

  19. Monitor when a user changes their email address in your Python application

  20. Monitor Redis downtime in your Python application

    View all common use-cases with Python