Hi. I'm Scott

[ This is part 3 of the series. Check-out the Introduction and AWS .] Google's Cloud Computing platform was unknown to me when I started this experiment. I knew it was there, and I knew people used it. Just not as many as Amazon or Azure. However, if an organization could rival Amazon's technology footprint, it would have to be the massive efforts of the ubiquitous search and email giant. Unlike AWS, Google's computing platform offers a $300 credit for the first year of service and Always Free service model; you can read more about GCP Free Tier . With a free $300 in burning a hole in my pocket, I build a machine using the 'n1-standard-1' template and placed it in the US-Central(Iowa) region. The n1-standard is a 1vCPU machine with 3.75GB of RAM, running Debian Linux. With the exception of the region, all of these configurations are similar to the t2.micro instances built in AWS. NOTE: There are shared core f1-micro and g1-small instances that I could have bu

In part one , we introduced the use case of a CPU intense workload and baseline data from my MacMini. Since I last checked, Amazon Web Services hosts roughly 70% of all cloud computing resources. For all practical purposes, it IS the cloud; Microsoft, Oracle, and Google all struggling to catch-up. Since my cloud experience is mostly Amazon-related, I decided to start there.  I created three, free-tier EC2 (t2.micro) instances running Amazon Linux. At the time, free-tier provides only 1 vCPU, 1GB of memory and 8GB of storage, with more available if you want to mount your S3 bucket or add EBS storage. Right away, my MacMini has an advantage, since it's a 2 processor machine, and Amazon only gives me one.  But what does the free-tier get you in terms of CPU performance? The answer is not much.  The CPUs are Intel Xeon processors, running at 2.40gHz. Interesting, the SETI benchmark for Integer and Floating-Point operations fell well below what MacMini.