Monitor memory usage in your Python application

LogSnag is a monitoring service that alerts you when your application is experiencing high memory usage.

A common problem that we often face with Python applications is memory leaks and the overall memory usage of our application. This is a significant problem when building applications that we end up deploying to the cloud either as a serverless function, container, or virtual machine. In such cases, memory usage can become a significant problem by slowing down our application, causing it to crash entirely, or increasing costs.

Therefore, monitoring our Python application's memory 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. In cases of a performance issue, for example, when the memory usage goes above a certain threshold, say 80 percent, we can take immediate action and fix the problem before it becomes a significant issue.

To do so, we have created LogSnag, a powerful event tracking tool that works seamlessly with Python and allows us to track any event in our application in real-time. For example, with LogSnag, we can track our memory usage in real-time and set up a rule to notify our team and us when the memory usage goes above a certain threshold via push notifications. This way, we will always be aware of the performance of our application, and we 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

You can use the following code snippets to track memory usage in your Python application. Please don't forget to 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 Memory Usage",
  "description": "Memory usage has exceeded the threshold.",
  "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 Memory Usage",
  "description": "Memory usage has exceeded the threshold.",
  "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

LogSnag is a powerful and flexible event tracking tool that works surprisingly well with Python applications. It provides powerful features such as real-time event tracking, cross-platform push notifications, user and product journeys, charts and analytics, and more.

Connect LogSnag to your Python application in minutes and start tracking events in real-time. 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. 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 high disk 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