MONITOR DISK USAGE WITH R LANGUAGE

Monitor high disk usage in your R application

When it comes to developing applications in the realm of R, managing persistent data is a recurring necessity. This can take various forms, such as handling JSON, CSV, or text files on local disks, uploading files to cloud storage solutions like S3 or Google Cloud Storage, or storing data in databases like MongoDB or MySQL. Irrespective of the method chosen, the utilization of disk storage is a pivotal factor for R applications and has a substantial impact on the user experience.

Hence, it's imperative to implement robust disk usage monitoring for R applications, whether they are operating in a local environment or residing in the cloud. The significance of this lies in the fact that exceeding a certain disk usage threshold can lead to application crashes and unavailability, resulting in substantial revenue loss and a compromised user experience.

Enter Palzin Track, a potent event tracking tool seamlessly integrated with R. Palzin Track simplifies the process of tracking crucial events in R applications in real time. An exemplary use case for Palzin Track involves real-time tracking of disk usage, coupled with the ability to establish alert rules that promptly notify your team when disk usage surpasses predefined thresholds. This proactive approach ensures continuous performance awareness, enabling immediate corrective action when necessary.

Connect Palzin Track to R

Setting up Palzin Track

1. Sign up for a free Palzin Track 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 Palzin Track 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.

Using R with httr

library(httr)  


headers = c(  


 'Content-Type' = 'application/json',  


 'Authorization' = 'Bearer YOUR_API_TOKEN'  


)  


body = '{  


 "project": "my-project",  


 "channel": "status",  


 "event": "High Disk Usage",  


 "description": "The disk usage is high.",  


 "icon": "💾",  


 "notify": true  


}';  


res VERB("POST", url = "https://api.palzin.live/v1/log", body = body, add_headers(headers))  


cat(content(res, 'text'))

Using R with RCurl

library(RCurl)  


headers = c(  


 "Content-Type" = "application/json",  


 "Authorization" = "Bearer YOUR_API_TOKEN"  


)  


params = "{  


 \"project\": \"my-project\",  


 \"channel\": \"status\",  


 \"event\": \"High Disk Usage\",  


 \"description\": \"The disk usage is high.\",  


 \"icon\": \"💾\",  


 \"notify\": true  


}"  


res postForm("https://api.palzin.live/v1/log", .opts=list(postfields = params, httpheader = headers, followlocation = TRUE), style = "httppost")  


cat(res)

R integration details

In addition to real-time event tracking, Palzin Track provides powerful features such as cross-platform push notifications, event filtering, user and product journeys, charts, insights, and more. Via Palzin Track, 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, Palzin Track is flexible and easy to use, making it a great companion for your R applications.

Other use-cases for Palzin Track

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. Monitor user signup events via R
24. Track waitlist signup events via R