When you look at an application running on cloud resources, you need to look at all of the costs…

Great response, and I’m glad you brought this up.

The argument in my blog is confined to specific scope — how and why Google’s Compute is more flexible than Amazon’s, especially when it comes to RIs. I am certainly not intending for that argument to be taken as a superset of all arguments around cloud.

Your response does expand the scope of this conversation, and into a topic that Google shines in (and far from accidentally)- powerful higher level services, so I’d love to hear your thoughts on just some of these points:

  • Unique to Google — Google has Multi-region Object Storage, in case of those pesky regional storage outages.
  • Unique to Google — Bigtable, a high-level serverless NoSQL database, demonstrated to serve 53 million qps by Sungard FIS last year.
  • Unique to Google — BigQuery provides the highest level of manageability for an analytics database yet, at Petabyte-scale. Last week Yahoo and NYT detailed their migrations from, well, a different cloud vendor :)
  • Unique to Google — Spanner is the only serverless Petabyte-scale strongly consistent regionally replicated horizontal, and highly available RDBMS.
  • Unique to Google — Cloud Dataflow is serverless batch and stream processing engine.
  • Unique to Google — Dataproc is job-scoped Hadoop and Spark clusters, very compelling to folks coming from EMR, and I wrote on that topic here.

So while I attempted to clarify one bit of debate around just one piece of the puzzle (compute), your chief argument is much broader, and is far from false on Google Cloud. In fact, one may very easily argue that Google is a market leader in offering higher-level services, and I gave just a couple of points of evidence for you to ponder.

I look forward to hearing your thoughts!

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