Since ParkMyCloud provides cost control for Amazon Web Services (AWS) along with Google Cloud Platform (GCP) resources, we thought it might be useful to compare AWS vs Google Cloud pricing. Additionally, we will take a look at the terminology and billing differences. There are other “services” involved, such as networking, storage and load balancing, when looking at your overall bill. I am going to be focused mainly on compute charges in this article.  

Note: a version of this post was originally published in 2017. It has been completely rewritten and updated to include the latest AWS pricing and GCP pricing as of October 2019.

AWS and GCP Terminology Differences

As mentioned before, in AWS, the compute service is called “Elastic Compute Cloud” (EC2). The virtual servers are called “Instances”.

In GCP, the service is referred to as “Google Compute Engine” (GCE). The servers are called also called “instances”. 

A notable difference in terminology are GCP’s there are “preemptible” and non-preemptible instances.  Non-preemptible instances are the same as AWS “on demand” instances.  

Preemptible instances are similar to AWS “spot” instances, in that they are a lot less expensive, but can be preempted with little or no notice. GCP preemptible instances can be stopped without being terminated. In November 2017, AWS introduced a similar feature with spot instance hibernation. Flocks of these instances spun up from a snapshot according scaling rules are called “auto scaling groups” in AWS.

The similar concept can be created within GCP using “instance groups”. However, instance groups are really more of a “stack”, which are created using an “instance group template”. As such, they are more closely related to AWS CloudFormation stacks.

AWS vs. GCP Compute Sizing

Both AWS and GCP have a dizzying array of instance sizes to choose from, and doing an apples-to-apples comparison between them can be quite challenging. These predefined instance sizes are based upon number of virtual cores, amount of virtual memory and amount of virtual disk.

They have different categories.

AWS offers:

  • Free tier – inexpensive, burst performance (t3 family)
  • General purpose (m4/m5 family)
  • Compute optimized (c5 family)
  • GPU instances (p3 family)
  • FPGA instances (f1 family)
  • Memory optimized (x1, r5 family)
  • Storage optimized (i3, d2, h1 family)

GCP offers the following predefined types:

  • Free tier – inexpensive, burst performance (f1/g1 family)
  • Standard, shared core (n1-standard family)
  • High memory (n1-highmem family)
  • High CPU (n1-highCPU family)

However, GCP also allows you to make your own custom machine types, if none of the predefined ones fit your workload. You pay for uplifts in CPU/Hr and memory GiB/Hr. You can also add GPUs and premium processors as uplifts.

With respect to pricing, this is how the two seem to compare, by looking at some of the most common “work horses” and focusing on CPU, memory and cost.  

The bottom line:

In general, for most workloads AWS is less expensive on a CPU/Hr basis. For compute intensive workloads, GCP instances are generally less expensive

Also, as you can see from the table, both providers charge uplifts for different operating systems, and those uplifts can be substantial. You really need to pay attention to the fine print. For example, GCP charges a 4 core minimum for all their SQL uplifts (yikes!). And, in the case of Red Hat Enterprise Licensing (RHEL) in GCP, they charge you a 1 hour minimum for the uplifts and in 1 hour increments after that. (We’ll talk more about how the providers charge you in the next section.)

AWS vs. Google Cloud Platform Pricing – Examining the Differences

Cost per hour is only one aspect of the cloud pricing equation, though. To better understand your monthly bill, you must also understand how the cloud providers actually charge you. AWS prices their compute time by the hour, but charges by the second, with a 1 minute minimum.

Google Compute Engine pricing is also listed by the hour for each instance, but they charge you by the minute, rounded up to the nearest minute, with a 10 minute minimum charge. So, if you run for 1 minute, you get charged for 10 minutes. However, if you run for 61 minutes, you get charged for 61 minutes. 

AWS Reserved Instances vs GCP Committed Use

Both providers offer deeper discounts off their normal pricing, for “predictable” workloads that need to run for sustained periods of time, if you are willing to commit to capacity consumption upfront. AWS offers Reserved Instances. Google offers Committed Use Discounts.  Both involve agreeing to pay for the life of the reservation or commitment, though some have you pay up-front versus paying per month. This model of payment can get you some significant discounts over on-demand workloads, but can limit your flexibility as a trade-off. Check out our other posts on AWS Reserved Instances and Google Committed Use Discounts.

GCP Sustained Use Discounts

In addition to the Committed Use Discounts, GCP also has a unique offering with no direct parallel in AWS: Sustained Use Discounts. These provide you with an automatic discount if you run a workload for more that 25% of the month, with bigger discounts for more usage. These discounts can save up to 30% based on your use and instance size. The Google Cloud Pricing Calculator can help figure out how much this will affect your GCP costs.

Conclusion

If you are new to public cloud, once you get past all the confusing jargon, the creative approaches to pricing and the different ways providers charge for usage, the actual cloud services themselves are much easier to use than legacy on-premise services.

The public cloud services do provide much better flexibility and faster time-to-value. 

When comparing AWS vs. Google Cloud pricing, AWS EC2 on-demand pricing may on the surface appear to be more competitive than GCP pricing for comparable compute engines. However, when you examine specific workloads and factor in Google’s approach to charging for CPU/Hr time and their use of Sustained Use Discounts, GCP may actually be less expensive. 

In the meantime, ParkMyCloud will continue to help you turn off non-production cloud resources, when you don’t need them and help save you a lot of money on your monthly cloud bills, regardless of which public cloud provider you use.

Like this post? See also: How much do the differences between cloud providers actually matter? 

About Chris Parlette

Chris Parlette is the Director of Cloud Solutions at ParkMyCloud. Chris helps customers reduce their cloud waste and manage their hybrid infrastructures by drawing on his years of experience working at various software startups. From SaaS to on-prem, virtualization to cloud, monitoring tools to cloud management platforms, and small businesses to large enterprises, Chris has seen it all and loves helping drive improvements to IT management. Chris earned a BS in Computer Science from the University of Maryland. He and his wife, Megan, reside in Silver Spring, MD.

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