Using AWS or High end PC is better for Kite ?

ANL edited September 11 in Python client
I just want to know if using AWS (Mumbai) or a high-end computing PC is better for execution, bulk data, or OHLC processing.
I see that AWS is more expensive than PCs, and AWS does not provide a high-end AMD processor or RAM. Is that correct?
When commuting, I see that using AWS is more practical than PC.

Please comment
  • ANL
    @sujith Please comment
  • sujith
    Kite Connect is just a REST like APIs. From API's perspective computation power is not much, but everything depends on what you are doing before making an API call and how you can do it. A basic PC will do the job.
    If you are located in a good place where the availability and speed of internet is good and reliable then local PC would do. After your setup is complete, you can run on aws and check if it gives you a significant advantage.
    If your ISP is not good then it is better to start on aws itself.
    PS: Please keep in mind that Kite Connect is not suitable for HFT or latency based trading.
  • MAG
    @ANL Just came across this

    AWS is anyday better. When you run on your local system the main issue is the broadband internet connection. There will always be network disruptions on home broadband connections. AWS runs in the best of class datacenters with multiple redundancies and hence you will not get any network issues.

    Also there is a whole lot of difference between server grade hardware and desktop grade hardware.
    I have seen that when I am processing ticks, my AWS server runs significantly faster than my local machine though the local machine has a higher clock speed.

    Also AWS does provide AMD servers. The following is the output of cpuinfo on my aws server

    Yes AWS is expensive so you need to run live production code on AWS and then backup and download the data to local machine for any backtest/dev/staging etc. Storage costs on AWS can quickly add up to multiples of your compute costs if one is not careful.
  • ANL
    ANL edited 4:27AM
    Thank you @MAG Can you please suggest an efficient AWS configuration if compared with the AMD 7950X-64GB combo?
  • MAG
    Depends on how many instruments you want to subscribe to and what you want to do exactly. I track and process all ticks for nifty and banknifty. Thats about 300-350 instruments and I run it on a m6a.2xlarge (8 cpu, 32gb, 200gb SSD) with considerable headroom.

    You cant compare apples to oranges (AMD 7950X-64GB to AWS ) as your AMD 7950X-64GB desktop might be sitting idle 90% of the time and it doesn't really hurt you because you are not paying for it monthly. But on AWS you need to be careful of sizing your instance carefully. If you get a equivalent 32 core machine with 64 gb ram and its cpu and RAM utilisation is less than 10% you will be throwing away money because you are being billed monthly. And on AWS everything adds up -storage, network data transferred etc. Calculating AWS instance sizing and costs is a different ballgame altogether.
  • ANL
    @MAG Except for the efficient virtual machine advantage when commuting and the lower latency, I believe AWS is not ideal for me. I checked the pricing of the instance; it is actually head-over for me to keep the subscription. I am still using the desktop. it will not be idle 90% of the time, as I presently have 12 projects running on the desktop. and attempting to grow on numerous initiatives. Thank you for your help with AWS.
Sign In or Register to comment.