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Ask HN: How to achieve limited scalability with less cash burnout?
I have been working on an algorithm around text processing. As a POC usecase, I am looking at using news articles as input text to the algo. However, the effectiveness will be seen only if I can have large number of them (say around a million).
I would like to know the best way to get access to free / cheap cloud infrastructure with less cash burnout (CPU, disk, RAM) as the App will be intensive on memory and CPU when it processes 1 million news articles. The initial need may be around 2 4 core nodes with 8GB RAM each.
Alternatively, would it be more cost effective if I buy a custom made server(s) and keep it at home to validate initially and once I cross the Beta, and see some traction (usage, funding) , I start using the cloud.
Note that I am self funded.
- stephenr 10y agoDo you need the resources constantly or in bursts? What are your storage requirements?
- thallukrish 10y agoI guess initially when I test it, I need it everyday for few hours at least when it will have bursts. Storage per se may be fine with 120 or 240 GB as I deal with text only and not videos/images in phase 1.
- ahoka 10y agoIn that case you could use AWS Spot Instances or Google Preemptible VMs, which are cheaper with the caveat of possibly shut down "randomly".
- chatmasta 10y agoHave you looked at dedicated server options? You could rent hardware with those specs for ~ $200/month.
- stephenr 10y agoFor the usage described, I think this is one of the few cases where the on-demand model of "cloud" operators actually makes sense.