Hi everyone, I’m managing a restaurant-related website (mainly focused on Texas Roadhouse menu insights and kitchen operations), and I recently tried to integrate some IoT-based performance tracking data from Siemens devices into it. The idea was to display live temperature and energy efficiency data from kitchen sensors that run on Siemens controllers. However, ever since I connected my site to the Siemens API, I’ve been facing serious technical issues — both with data refresh and overall website performance.
The first problem is with the data synchronization. I set up a small backend script that fetches sensor readings from the Siemens cloud platform every 10 minutes using the provided REST API. It works fine for a while, but after a few cycles, the data stops updating and the connection throws 504 Gateway Timeout or Connection reset errors. Restarting the script temporarily restores the link, but it fails again within hours. I’m not sure if this is an authentication issue or something related to request rate limits.
Another issue is that the website’s load time has increased dramatically since adding the IoT integration. The pages that display live data now take 5–7 seconds to load, compared to under two seconds before. I suspect that the synchronous API calls might be blocking page rendering, but I’m not entirely sure how to optimize this with Siemens’ data endpoints. Would switching to an MQTT-based approach improve real-time performance compared to repeated REST polling?
I’ve also been getting inconsistent readings from the Siemens devices themselves. Sometimes the data returned from the API shows blank or null values for parameters like “temperature” or “status.” I verified that the sensors are online through the Siemens management console, so it’s not a hardware failure. Could this be a delay in the cloud data replication or an issue with the API token’s permission scope? The documentation wasn’t completely clear about how long cached sensor values are stored before being refreshed.
Another strange behavior is that the website’s server (hosted on a VPS) occasionally crashes due to excessive CPU usage when multiple users access the live dashboard simultaneously. I checked the logs and noticed several threads hanging in the data fetch routine. It seems like my async queue is not handling concurrent requests efficiently. Has anyone else tried integrating Siemens IoT APIs into a public-facing web dashboard and run into similar scaling issues?
At this point, I’m considering whether I should offload the Siemens data processing to a separate microservice or caching layer instead of directly fetching it on-page load. If anyone here has experience working with Siemens MindSphere or other Siemens cloud APIs in a web application context, I’d really appreciate your advice. My goal is to keep the real-time restaurant data visible to users without overloading the site or breaking the API connection every few hours. Sorry for the long post.
Thanks Joe for the question. Can you provide more information on exactly which API you are using and what Siemens devices you are talking about? I couldn’t find the relevant information on the example page you shared.