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Hey, I am developing an internal app using Python (that's what I am okish at). This is an backend app which pulls the hourly metrics for different VM and pods from Datadog. Metrics like (load average,
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Hey, I am developing an internal app using Python (that's what I am okish at). This is an backend app which pulls the hourly metrics for different VM and pods from Datadog. Metrics like (load average, cpu usage , memory usage, etc). This would then be shared with App Owners using Backstage (Self-Service Interface). Infra Size - We have 2k+ machines Current Arch - The backend app is still not production and we are still developing it. So here is the current flow : 1. Read the CSV file using pandas (we currently get the list of VMs and Pods as a CSV File) 2. Generate batch id 3. Query the Datadog API for the VM metrics 4. Store it in DB 5. Update the control table with Success. It's an usual arch using control table. similar to what described here : <a href="https://datawarehouseandautomation.wordpress.com/wp-content/uploads/2014/08/processcontrol-7aug.jpg;
![<a href="https://datawarehouseandautomation.wordpress.com/wp-content/uploads/2014/08/processcontrol-7aug.jpg](https://datawarehouseandautomation.wordpress.com/wp-content/uploads/2014/08/processcontrol-7aug.jpg" target="_blank" rel="noopener" class="text-emerald-400 hover:text-emerald-300 underline">https://datawarehouseandautomation.wordpress.com/wp-content/uploads/2014/08/processcontrol-7aug.jpg](https://datawarehouseandautomation.wordpress.com/wp-content/uploads/2014/08/processcontrol-7aug.jpg</a>) Problems : In this setup, it takes huge amount of time to query datadog and then it fails sometimes because DD limit to API call. Restarting it again with smaller set of VMs and Pods works fine. So what happens is with 1k+ VMs, if the app has done the query for 900 VMs and it fails for 901st, then the whole operation fails. So I am thinking of having an arrangement where I can temporarily store the datadog api results in an temporary storage and only query again for the failed one. I am thinking of introducing Kafka in my setup. Is there any other better solution ? PS : I am not an seasoned software engineer, so please feel free to be as detailed as possible. Ȁ){kind=link}
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This is a candidate experience report from a datadog interview for a data eng role reported in 2024.
It covers the following topics: Sql .
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