Monitor your Postgres downtime in your Python application

Postgres is a robust, relational database commonly used in Python applications to persist and query data. It is a great tool with many features, making it an excellent choice for small and large applications.

However, just like any other database, Postgres is susceptible to downtime caused by various reasons. For example, your database instance might go down due to hardware failure, network issues, misconfiguration, or several other reasons. When this happens, chances are that your application will not be able to continue working as expected, causing significant issues such as failing requests and slow performance. In severe cases, it can cause data loss.

Therefore, it is crucial to monitor the status of your database and take immediate action when something is not functioning as expected. Fortunately, LogSnag makes it trivial to track such events as database downtimes and failures. LogSnag is a simple and powerful event tracking tool that allows us to log whenever we encounter an unexpected behavior in our applications.

For example, in the case of Postgres, we usually set up periodic checks to ensure that our database is up and running and monitor its performance, disk, and memory usage. If we encounter any issues, such as increased disk usage, slow performance, or downtime, we log the event using LogSnag. It then notifies our team immediately and allows us to take immediate action.

In addition, LogSnag provides a powerful insights dashboard that allows us to monitor the status of our database, its performance, uptime, memory usage, and any other metric that we want to track, making it easy to monitor the health of our database.

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 Postgres downtime, 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": "Postgres is down",
  "description": "Postgres has been down 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": "Postgres is down",
  "description": "Postgres has been down 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

In addition, LogSnag provides several powerful features, such as real-time event tracking, push notifications, charts, funnels, and user journey tracking. Furthermore, it works seamlessly with Python and is an excellent tool for monitoring each application part.

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 your CPU usage in your Python application
3. Monitor when database goes down in your Python application
4. Monitor high disk usage in your Python application
5. Monitor when a user changes their email address in your Python application
6. Monitor failed logins in your Python application
7. Monitor failed payments for your Python application
8. Monitor memory usage in your Python application
9. Monitor MySQL downtime in your Python application
10. Monitor when a new feature is used 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