MONITOR CPU USAGE WITH R LANGUAGE

Monitor your CPU usage in your R application

When developing a R application, it is essential to address performance considerations, as they play a crucial role in shaping the user experience. Performance issues are a common concern and can significantly impact the application's effectiveness. One of the most prevalent performance challenges faced by R applications is the occurrence of CPU-bound workloads. This situation arises when the application spends a significant amount of time waiting for the CPU to complete tasks.

In such instances, it becomes imperative to monitor the CPU usage of your R application and establish a tracking system to detect when the usage surpasses predefined thresholds. This approach ensures continuous awareness of your application's performance. In cases of performance degradation, such as when CPU usage exceeds specified thresholds, immediate action can be taken to rectify the issue before it escalates.

Thankfully, Palzin Track offers an effective solution to address these concerns. Palzin Track is a potent real-time event tracking tool that seamlessly integrates with R. With Palzin Track, you have the flexibility to set up event tracking for various aspects of your R application, including real-time monitoring of CPU usage. Furthermore, you can configure alert rules to promptly notify you and your team when CPU usage crosses designated thresholds. This proactive monitoring approach ensures that you remain well-informed about your application's performance and enables you to take swift action as required.

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 snippet to track your CPU Usage with Palzin Track. Please don't forget to 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 CPU Usage",  


 "description": "CPI usage has been over 90% for the last 5 minutes",  


 "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 CPU Usage\",  


 \"description\": \"CPI usage has been over 90% for the last 5 minutes\",  


 \"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

We believe that event tracking should be 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.

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.

Palzin Track 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 Palzin Track

1. Monitor your CI/CD build status for your R application
2. Monitor when database goes down in your R application
3. Monitor high disk usage 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