Monitor high disk usage in your R application

When building R 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 R application and can significantly affect the user experience.

Therefore, monitoring our R 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 R and makes it trivial to track any important event in our R 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.

R code snippets

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

library(httr)

headers = c(
  'Content-Type' = 'application/json',
  'Authorization' = 'Bearer YOUR_API_TOKEN'
)

body = '{
  "project": "my-saas",
  "channel": "status",
  "event": "High Disk Usage",
  "description": "The disk usage is high.",
  "icon": "💾",
  "notify": true
}';

res <- VERB("POST", url = "https://api.logsnag.com/v1/log", body = body, add_headers(headers))

cat(content(res, 'text'))

library(RCurl)
headers = c(
  "Content-Type" = "application/json",
  "Authorization" = "Bearer YOUR_API_TOKEN"
)
params = "{
  \"project\": \"my-saas\",
  \"channel\": \"status\",
  \"event\": \"High Disk Usage\",
  \"description\": \"The disk usage is high.\",
  \"icon\": \"💾\",
  \"notify\": true
}"
res <- postForm("https://api.logsnag.com/v1/log", .opts=list(postfields = params, httpheader = headers, followlocation = TRUE), style = "httppost")
cat(res)

R 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 R 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 R applications.

Other use-cases for LogSnag

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