EC2 vs Google Compute Engine: comparing the big players in IaaS

IaaS: EC2 vs Google Compute Engine

EC2 vs Google Compute EngineArguably, Infrastructure as a Service (IaaS) is the most important cloud computing vertical. Within that, in terms of services and features, AWS enjoys the top position, while Google Cloud Platform is slowly catching up. In this post, we’ll discuss major differences between Amazon’s EC2 and Google Compute Engine (GCE).

EC2 vs Google Compute Engine: Regions

Amazon EC2 is spread across 11 different regions: Northern Virginia, Oregon, Northern California, Ireland, Germany, Singapore, Tokyo, China, Sau Paulo, Sydney and US GovCloud.
Google Compute Engine is spread across 3 different regions: us-central1, Europe-west1, and asia-east1. Google does not officially reveal the exact locations of these zones. However, according to this post from Gigaom, us-central1 translates to Oklahoma, and Europe-west1 is in Ireland.

EC2 vs Google Compute Engine: Compute Capacity

AWS Instance types are optimized for different types of workloads, like Compute, Storage, Memory, and GPU. Instance types are divided into different “families” like m3 (balanced), c4 (compute optimized), and t2 (baseline level). In its current form, there is a total of 28 instances types. The use of previous generation instances is not recommended due to performance limitations.
Just like AWS, Google Compute Engine also offers instances based on workload type. Currently, GCE instances are divided into 4 types: Standard machine types, High CPU machine types, High memory machine types and Small machine types. GCE offers a total of 17 instance types.

Amazon EC2Google Compute Engine
TypeMinimum Computing CapacityMaximum Computing CapacityMinimum Computing CapacityMaximum Computing Capacity
General / Standard Purpose1vCPU/3.75GB Memory8vCPU/30GB Memory1vCPU/3.75GB Memory32vCPU/120MB Memory
Compute Optimized / High CPU Instance Type2vCPU/3.75GB Memory36vCPU/60GB Memory2vCPU/1.80GB Memory32vCPU/28.8 Memory
Memory Optimized/ High Memory Instance Type2vCPU/15.25GB Memory32vCPU/244GB Memory2vCPU/13GB Memory32vCPU/208GB Memory
Shared Core1vCPU/1GB Memory2vCPU/4GB Memory1vCPU/0.60GB Memory1vCPU/1.70GB Memory
Storage Optimized4vCPU/30.5GB Memory32vCPU/244GB MemoryN/AN/A
GPU Optimized8vCPU/15GB MemoryN/AN/AN/A

Note : This is a high level comparison table. Instances internal might vary.

EC2 vs Google Compute Engine: Pricing

Amazon EC2 offers three types of pricing models:

  • On-demand – pay for compute capacity by the hour with no long term commitments.
  • Reserved instances – maximize savings by purchasing reserved instances that meet your long term business needs. Reserved instance prices are determined by 4 factors : term (1 or 3 year), operating system, region, and payment options (no upfront, partial upfront, all upfront).
  • Spot instances – bid for instances using a supply and demand model.

Google Compute Engine machine types are charged for a minimum of 10 minutes’ use. After 10 minutes, instances are charged in 1 minute increments, rounded up to the nearest minute. GCE offers both on-demand and sustained usage pricing models. The sustained usage pricing model provides discounts if your instance is used for more than 25% of a month. To maximize savings, GCE also offers inferred instances, i.e., it combines multiple, non-overlapping instances of the same instance type in the same zone into a single instance for billing.

EC2 vs Google Compute Engine: Security Groups, Network ACLs, and Firewalls

As AWS instances are now provisioned within VPCs, Amazon provides the benefit of both Security Groups and Network ACLs. With Security Groups – working as whitelists – you control incoming and outgoing traffic at the instance level. Network ACLs, on the other hand, work at subnet level, and allow or deny specific IP addresses or networks.
Similarly, Google Compute Engine firewalls regulate outgoing traffic from instances using iptables. Google’s Firewall is also a whitelist service.

EC2 vs Google Compute Engine: Load Balancing

Elastic Load Balancer (ELB) allows you load balance incoming traffic among your backend instances in multiple availability zones (within a single region). This traffic distribution to backend instances happens using a weighted round robin algorithm. Apart from load balancing incoming traffic, ELB also offers session stickiness, cross zone load balancing, and SSL termination. ELB works with AWS’s auto-scaling and supports IPv4 and IPv6 addresses, HTTP and TCP load balancing, and logging.
Google Compute Engine also offers a load balancer. In addition to distributing incoming traffic between backend instances, unlike AWS, it allows balancing between regions, supports content-based routing, and does not require pre-warming.

EC2 vs Google Compute Engine: Storage

Amazon EC2 provides Elastic Block Storage (EBS) volumes for persistent storage. These EBS volumes are offered in 3 types : Magnetic volumes, General Purpose SSD volumes, and Provisioned IOPS SSD volumes. AWS just increased the performance limits on EBS volumes to 16TB capacity with a peak of 20,000 IOPS/volume and 320 MBps max throughput/volume. EBS volumes can be attached to one instance at a time. Amazon also recently enabled encryption for EBS volumes.
Google Compute Engine offers persistent disk storage, available as both standard (HDD) and solid-state (SSD). All data written to disk in Compute Engine is encrypted on the fly and then transmitted and stored in encrypted form. GCE’s Persistent Disks (PD) can be mounted read-write by one VM or read-only by many VMs. Google persistent disk storage offers 3000 Read IOPS/volume and 15,000 Write IOPS/volume for standard disks and 10,000 Read IOPS/volume and 15,000 Write IOPS/volume for Solid-state persistent disks. Each persistent disk can be up to 10TB in size.

EC2 vs Google Compute Engine: Service Level Agreement

Amazon EC2 offers a service level agreement guaranteeing a monthly uptime percentage of 99.95%. If your actual monthly uptime percentage is less than 99.95%, but equal to or greater than 99.0%, Amazon EC2 offers 10% service credit. For less than 99.0%, you receive 30% service credit.
Google Compute Engine also offers a service level agreement ensuring at least 99.95% uptime. If your monthly uptime percentage is between 99.00% – 99.95%, 10% financial credit is received. For 95.00% – 99.00%, 25% financial credit is received. For anything less than 95.00%, you’ll receive a 50% credit.

EC2 vs Google Compute Engine: Operating System Support

Amazon EC2 supports a wide range of operating systems, including Amazon Linux, Red Hat Enterprise Linux, CentOS, Debian, SUSE, Ubuntu, Oracle Enterprise Linux, FreeBSD, and Windows (2003 R2, 2008, 2008 R2, 2012).
Google Compute Engine supports CentOS, Red Hat Enterprise Linux, Debian, SUSE, Ubuntu, and Windows Server 2008R2. Windows Server support is in beta mode.
There is obviously more to making a full feature and performance comparison of  EC2 vs Google Compute Engine, but this is hopefully a good start. AWS and Google both provide plenty of documentation that will allow you to dig much deeper to answer your specific questions.

Written by

Sanket Dangi

Head of Managed Services at REAN Cloud. Before joining REAN Cloud, I was CEO and Founder of StraightArc Solutions which was later acquired by REAN Cloud.I started my career working on cloud computing. Loves to talk about DevOps, System Administration, Scalability, High Availability, Disaster Recovery and Cloud Security. Apart from work, I love to meet people, travel and watch sports.

Related Posts

— February 11, 2019

WaitCondition Controls the Pace of AWS CloudFormation Templates

AWS's WaitCondition can be used with CloudFormation templates to ensure required resources are running.As you may already be aware, AWS CloudFormation is used for infrastructure automation by allowing you to write JSON templates to automatically install, configure, and bootstrap your ...

Read more
  • AWS
— January 24, 2019

The 9 AWS Certifications: Which is Right for You and Your Team?

As companies increasingly shift workloads to the public cloud, cloud computing has moved from a nice-to-have to a core competency in the enterprise. This shift requires a new set of skills to design, deploy, and manage applications in the cloud.As the market leader and most mature p...

Read more
  • AWS
  • AWS certifications
— November 28, 2018

Two New EC2 Instance Types Announced at AWS re:Invent 2018 – Monday Night Live

The announcements at re:Invent just keep on coming! Let’s look at what benefits these two new EC2 instance types offer and how these two new instances could be of benefit to you. If you're not too familiar with Amazon EC2, you might want to familiarize yourself by creating your first Am...

Read more
  • AWS
  • EC2
  • re:Invent 2018
— November 21, 2018

Google Cloud Certification: Preparation and Prerequisites

Google Cloud Platform (GCP) has evolved from being a niche player to a serious competitor to Amazon Web Services and Microsoft Azure. In 2018, research firm Gartner placed Google in the Leaders quadrant in its Magic Quadrant for Cloud Infrastructure as a Service for the first time. In t...

Read more
  • AWS
  • Azure
  • Google Cloud
Khash Nakhostin
— November 13, 2018

Understanding AWS VPC Egress Filtering Methods

In order to understand AWS VPC egress filtering methods, you first need to understand that security on AWS is governed by a shared responsibility model where both vendor and subscriber have various operational responsibilities. AWS assumes responsibility for the underlying infrastructur...

Read more
  • Aviatrix
  • AWS
  • VPC
— November 10, 2018

S3 FTP: Build a Reliable and Inexpensive FTP Server Using Amazon’s S3

Is it possible to create an S3 FTP file backup/transfer solution, minimizing associated file storage and capacity planning administration headache?FTP (File Transfer Protocol) is a fast and convenient way to transfer large files over the Internet. You might, at some point, have conf...

Read more
  • Amazon S3
  • AWS
— October 18, 2018

Microservices Architecture: Advantages and Drawbacks

Microservices are a way of breaking large software projects into loosely coupled modules, which communicate with each other through simple Application Programming Interfaces (APIs).Microservices have become increasingly popular over the past few years. The modular architectural style,...

Read more
  • AWS
  • Microservices
— October 2, 2018

What Are Best Practices for Tagging AWS Resources?

There are many use cases for tags, but what are the best practices for tagging AWS resources? In order for your organization to effectively manage resources (and your monthly AWS bill), you need to implement and adopt a thoughtful tagging strategy that makes sense for your business. The...

Read more
  • AWS
  • cost optimization
— September 26, 2018

How to Optimize Amazon S3 Performance

Amazon S3 is the most common storage options for many organizations, being object storage it is used for a wide variety of data types, from the smallest objects to huge datasets. All in all, Amazon S3 is a great service to store a wide scope of data types in a highly available and resil...

Read more
  • Amazon S3
  • AWS
— September 18, 2018

How to Optimize Cloud Costs with Spot Instances: New on Cloud Academy

One of the main promises of cloud computing is access to nearly endless capacity. However, it doesn’t come cheap. With the introduction of Spot Instances for Amazon Web Services’ Elastic Compute Cloud (AWS EC2) in 2009, spot instances have been a way for major cloud providers to sell sp...

Read more
  • AWS
  • Azure
  • Google Cloud
  • SpotInst
— August 23, 2018

What are the Benefits of Machine Learning in the Cloud?

A Comparison of Machine Learning Services on AWS, Azure, and Google CloudArtificial intelligence and machine learning are steadily making their way into enterprise applications in areas such as customer support, fraud detection, and business intelligence. There is every reason to beli...

Read more
  • AWS
  • Azure
  • Google Cloud
  • Machine Learning
— August 17, 2018

How to Use AWS CLI

The AWS Command Line Interface (CLI) is for managing your AWS services from a terminal session on your own client, allowing you to control and configure multiple AWS services.So you’ve been using AWS for awhile and finally feel comfortable clicking your way through all the services....

Read more
  • AWS