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I think you vastly underestimate Snapchat's scale and vastly overestimate AWS out-of-the-box scaleability. Someone like Snapchat periodically surprises GCP wit

by vgt 10y ago

I think you vastly underestimate Snapchat's scale and vastly overestimate AWS out-of-the-box scaleability. Someone like Snapchat periodically surprises GCP with millions of QPS, something AWS would deem akin to DDOS. With AWS, you'd need to carefully setup infrastructure that statically accepts such scale. You need to plan, test, deploy resources, measure, etc etc. Snapchat has to do absolutely 0 of that - they deploy code. This is a major difference between Google and AWS - with one you can setup scale, but you pay for it, and with the other you get scale as part of your service, out of the box.

gjolund 10y ago
Great response. Out of the box I agree with you, GCE is much more capable than AWS. However in my experience AWS is just as capable and much more flexible once it has been setup. Also AWS Lambda functions give you the ability to "deploy code" and has proved to be massively scalable. I feel that "carefully setup infrastructure that statically accepts such scale" is not an accurate way to describe top tier deployments on the AWS platform.
- vgt 10y ago
  Minor correction: Snapchat runs on GAE, not GCE. PaaS, not IaaS, so nearly EVERYTHING is taken care of. Something like this is impossible on AWS without pre-warming, pre-setup, or maybe even calling someone - https://www.youtube.com/watch?v=xT6tQAIywFQ&feature=youtu.be https://www.youtube.com/watch?v=xT6tQAIywFQ&feature=youtu.be Here's another example: EMR versus Dataproc. Dataproc has per minute billing + very fast startup times (sub 90s for decent-sized clusters). So with Dataproc, you can rethink how you run Hadoop. Rather than starting with a cluster, which you fill up with jobs, you can have "cluster setup" as part of the job path. This is possible because you don't pay a large penalty in startup, nor do you pay a large penalty in per-hour billing granularity. Oh and Google is much more inexpensive (http://fortune.com/2016/01/08/google-amazon-cloud-price-war/ http://fortune.com/2016/01/08/google-amazon-cloud-price-war/).

by vgt 10y ago

gjolund 10y ago

Great response. Out of the box I agree with you, GCE is much more capable than AWS. However in my experience AWS is just as capable and much more flexible once it has been setup. Also AWS Lambda functions give you the ability to "deploy code" and has proved to be massively scalable. I feel that "carefully setup infrastructure that statically accepts such scale" is not an accurate way to describe top tier deployments on the AWS platform.

vgt 10y ago
Minor correction: Snapchat runs on GAE, not GCE. PaaS, not IaaS, so nearly EVERYTHING is taken care of. Something like this is impossible on AWS without pre-warming, pre-setup, or maybe even calling someone - https://www.youtube.com/watch?v=xT6tQAIywFQ&feature=youtu.be https://www.youtube.com/watch?v=xT6tQAIywFQ&feature=youtu.be Here's another example: EMR versus Dataproc. Dataproc has per minute billing + very fast startup times (sub 90s for decent-sized clusters). So with Dataproc, you can rethink how you run Hadoop. Rather than starting with a cluster, which you fill up with jobs, you can have "cluster setup" as part of the job path. This is possible because you don't pay a large penalty in startup, nor do you pay a large penalty in per-hour billing granularity. Oh and Google is much more inexpensive (http://fortune.com/2016/01/08/google-amazon-cloud-price-war/ http://fortune.com/2016/01/08/google-amazon-cloud-price-war/).