Monitor when database goes down in your Python application

LogSnag makes it easy to track your Python application and monitor when your database goes down.

Almost every Python application requires some data persistence. In a good number of cases, we can go by using a simple JSON, CSV, or even a text file to store our data. However, in most cases, we need a more robust solution that can handle a large amount of data and many requests and allow us to perform complex queries.

This is where databases come in. Databases are a great way to store and retrieve data in a structured form. They are also a great way to perform complex queries and scale our application. However, databases can be a complex topic and can be challenging to set up and maintain.

One of the most common problems with databases is that they can go down and become unavailable for various reasons. As a consequence, our Python application will fail to work correctly and will not be able to retrieve or store data.

In such cases, it's essential to monitor your database activity and notify you and your team when something is wrong. This way, you can take immediate action and fix the problem before it becomes a significant issue.

Fortunately, LogSnag is an excellent tool for this problem as it trivializes tracking events in your Python application and monitoring database outages. With LogSnag, you can easily track your database outages in real-time and notify you and your entire team when something goes wrong.


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 snippet to track your database outages with LogSnag. 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": "Database is Down",
  "description": "PostgresSQL is down in Oregon",
  "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": "Database is Down",
  "description": "PostgresSQL is down in Oregon",
  "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 real-time event tracking tool that works seamlessly with Python applications. It provides a number of features such as real-time event tracking, cross-platform push notifications, event filtering, user and product journeys, charts and analytics, and much more.

By being a use-case agnostic event tracking tool, LogSnag allows you to track any event in your Python applications in any way you want. You can track your database outages, system status, and even user activity in real-time.

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 your CPU usage in your Python application

  12. Monitor memory 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

    View all common use-cases with Python