MONITOR MEMORY USAGE WITH R LANGUAGE

Monitor memory usage in your R application

In the realm of R applications, a recurring challenge we encounter relates to memory leaks and overall memory utilization. This issue assumes particular significance when developing applications destined for deployment in the cloud, whether as serverless functions, containers, or virtual machines. In such scenarios, excessive memory consumption can disrupt application performance, potentially leading to crashes and increased operational costs.

To mitigate these concerns, it is imperative to monitor the memory usage of our R applications and implement a robust tracking system with predefined thresholds. This proactive approach ensures ongoing performance awareness. For instance, if memory usage exceeds a predetermined threshold, such as 80 percent, immediate corrective actions can be taken to preempt more significant issues.

To address this, we introduce Palzin Track, a potent event tracking tool seamlessly compatible with R. With Palzin Track, you gain the capability to monitor various application events in real-time, including real-time tracking of memory usage. Moreover, you can configure notification rules to promptly alert your team and yourself when memory usage surpasses specified thresholds via push notifications. This vigilance ensures that you maintain a constant pulse on your application's performance, facilitating swift responses 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

You can use the following code snippets to track memory usage in your R application. 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 Memory Usage",  


 "description": "Memory usage has exceeded the threshold.",  


 "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 Memory Usage\",  


 \"description\": \"Memory usage has exceeded the threshold.\",  


 \"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

Palzin Track is a powerful and flexible event tracking tool that works surprisingly well with R applications. It provides powerful features such as real-time event tracking, cross-platform push notifications, user and product journeys, charts and analytics, and more.

Connect Palzin Track to your R application in minutes and start tracking events in real-time. 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 your CPU usage in your R application
3. Monitor when database goes down in your R application
4. Monitor high disk usage in your R application
5. Monitor when a user changes their email address in your R application
6. Monitor failed logins in your R application
7. Monitor failed payments for 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