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Amazon EC2 vs Google Compute Engine: What are the differences?
Amazon EC2 and Google Compute Engine are two popular cloud computing platforms that allow users to create and manage virtual machines in the cloud. While both offer similar services, there are key differences between them that make each platform suitable for different use cases.
Pricing Model: Amazon EC2 offers both on-demand and reserved instances, allowing users to pay for computing resources on an hourly basis or with a long-term commitment. On the other hand, Google Compute Engine offers sustained use discounts, where users get automatic discounts for long-running workloads, and committed use discounts for sustained usage with one or three-year commitments.
Network Performance: Amazon EC2 provides Enhanced Networking, which uses custom networking interfaces to improve network throughput and reduce latency. It also offers features like Elastic Load Balancers and Virtual Private Clouds. Google Compute Engine uses the Google Cloud Load Balancer for distributing traffic and offers Virtual Private Clouds for secure networking. However, it does not have a specific enhanced networking feature like EC2.
Machine Types: Amazon EC2 offers a wide range of instance types optimized for different workloads, such as compute-optimized, memory-optimized, and storage-optimized instances. Google Compute Engine also offers various machine types, including shared core instances, standard instances, high-memory instances, and high-CPU instances. However, Google does not have a specific storage-optimized instance type like EC2.
Marketplace: Amazon EC2 has a vast marketplace where users can find pre-configured virtual machine images, software, and service offerings contributed by independent software vendors (ISVs), system integrators, and AWS partners. Google Compute Engine also has a marketplace, although it is not as extensive as EC2's marketplace.
Load Balancing: Amazon EC2 offers three types of load balancers, namely the Classic Load Balancer, Application Load Balancer, and Network Load Balancer, which provide layer 4 and layer 7 load balancing capabilities. Google Compute Engine provides the Google Cloud Load Balancer, which offers both global and regional load balancing with SSL termination and content-based routing. However, it does not have the same range of load balancer options as EC2.
Managed Services: Amazon EC2 provides a variety of managed services, including AWS Elastic Beanstalk for deploying web applications and AWS Elastic Kubernetes Service (EKS) for running Kubernetes clusters. Google Compute Engine has its own managed services, such as Google Kubernetes Engine (GKE) for managing Kubernetes clusters and App Engine for deploying web applications. However, it does not have an equivalent service to AWS Elastic Beanstalk.
In Summary, Amazon EC2 and Google Compute Engine differ in pricing models, network performance, available machine types, marketplace offerings, load balancing options, and managed services provided.
Amazon EC2 vs Google Compute Engine: What are the differences?
Introduction
Amazon EC2 and Google Compute Engine are two popular cloud computing platforms that allow users to create and manage virtual machines in the cloud. While both offer similar services, there are key differences between them that make each platform suitable for different use cases.
1. Pricing Model: Amazon EC2 offers both on-demand and reserved instances, allowing users to pay for computing resources on an hourly basis or with a long-term commitment. On the other hand, Google Compute Engine offers sustained use discounts, where users get automatic discounts for long-running workloads, and committed use discounts for sustained usage with one or three-year commitments.
2. Network Performance: Amazon EC2 provides Enhanced Networking, which uses custom networking interfaces to improve network throughput and reduce latency. It also offers features like Elastic Load Balancers and Virtual Private Clouds. Google Compute Engine uses the Google Cloud Load Balancer for distributing traffic and offers Virtual Private Clouds for secure networking. However, it does not have a specific enhanced networking feature like EC2.
3. Machine Types: Amazon EC2 offers a wide range of instance types optimized for different workloads, such as compute-optimized, memory-optimized, and storage-optimized instances. Google Compute Engine also offers various machine types, including shared core instances, standard instances, high-memory instances, and high-CPU instances. However, Google does not have a specific storage-optimized instance type like EC2.
4. Marketplace: Amazon EC2 has a vast marketplace where users can find pre-configured virtual machine images, software, and service offerings contributed by independent software vendors (ISVs), system integrators, and AWS partners. Google Compute Engine also has a marketplace, although it is not as extensive as EC2's marketplace.
5. Load Balancing: Amazon EC2 offers three types of load balancers, namely the Classic Load Balancer, Application Load Balancer, and Network Load Balancer, which provide layer 4 and layer 7 load balancing capabilities. Google Compute Engine provides the Google Cloud Load Balancer, which offers both global and regional load balancing with SSL termination and content-based routing. However, it does not have the same range of load balancer options as EC2.
6. Managed Services: Amazon EC2 provides a variety of managed services, including AWS Elastic Beanstalk for deploying web applications and AWS Elastic Kubernetes Service (EKS) for running Kubernetes clusters. Google Compute Engine has its own managed services, such as Google Kubernetes Engine (GKE) for managing Kubernetes clusters and App Engine for deploying web applications. However, it does not have an equivalent service to AWS Elastic Beanstalk.
In Summary, Amazon EC2 and Google Compute Engine are cloud computing services offering scalable and flexible virtual machine instances. While EC2 by Amazon Web Services (AWS) boasts a longer track record and a vast array of services, Google Compute Engine, part of Google Cloud Platform (GCP), is recognized for its performance efficiency and seamless integration with other Google Cloud services, allowing users to choose based on specific project requirements and preferences.
Albeit restricted to only a few places worlwide compared to its peers in the cloud segment, I am yet to find another provider capable of delivering a score over 5000 (Geekbench) in a benchmark on a single CPU machine, and each machine costs $6 a month. For homelab and experienced users who don't need DBaaS or IaaC's, it's a pretty straightforward choice. A more comprehensive review of Vultr's HF machines can be found here.
Our company builds micro saas applications. Based on the application we decide whether to deploy it over one of our shared servers or on a dedicated server.
We decided to Lightsail over EC2.
Lightsail is a lightweight, simplified product offering that has a dramatically simplified console. The instances run in a special VPC, but this aspect is also provisioned automatically, and invisible in the console.
Lightsail supports optionally peering this hidden VPC with your default VPC in the same AWS region, allowing Lightsail instances to access services like EC2 and RDS in the default VPC within the same AWS account.
Bandwidth is unlimited, but of course free bandwidth is not -- however, Lightsail instances do include a significant monthly bandwidth allowance before any bandwidth-related charges apply.
It has predictable pricing with no surprises at the end.
The flexibility of EC2 leads inevitably to complexity. Whereas for Lighsail there is virtually no learning curve, here. You don't even technically need to know how to use SSH with a private key -- the Lightsail console even has a built-in SSH client -- but there is no requirement that you use it. You can access these instances normally, with a standard SSH client.
DigitalOcean was where I began; its USD5/month is extremely competitive and the overall experience as highly user-friendly.
However, their offerings were lacking and integrating with other resources I had on AWS was getting more costly (due to transfer costs on AWS). Eventually I moved the entire project off DO's Droplets and onto AWS's EC2.
One may initially find the cost (w/o free tier) and interface of AWS daunting however with good planning you can achieve highly cost-efficient systems with savings plans, spot instances, etcetera.
Do not dive into AWS head-first! Seriously, don't. Stand back and read pricing documentation thoroughly. You can, not to the fault of AWS, easily go way overbudget. Your first action upon getting your AWS account should be to set up billing alarms for estimated and current bill totals.
We first selected Google Cloud Platform about five years ago, because HIPAA compliance was significantly cheaper and easier on Google compared to AWS. We have stayed with Google Cloud because it provides an excellent command line tool for managing resources, and every resource has a well-designed, well-documented API. SDKs for most of these APIs are available for many popular languages. I have never worked with a cloud platform that's so amenable to automation. Google is also ahead of its competitors in Kubernetes support.
GCE is much more user friendly than EC2, though Amazon has come a very long way since the early days (pre-2010's). This can be seen in how easy it is to edit the storage attached to an instance in GCE: it's under the instance details and is edited inline. In AWS you have to click the instance > click the storage block device (new screen) > click the edit option (new modal) > resize the volume > confirm (new model) then wait a very long time. Google's is nearly instant.
- In both cases, the instance much be shut down.
There also the preference between "user burden-of-security" and automatic security: AWS goes for the former, GCE the latter.
Most bioinformatics shops nowadays are hosting on AWS or Azure, since they have HIPAA tiers and offer enterprise SLA contracts. Meanwhile Heroku hasn't historically supported HIPAA. Rackspace and Google Cloud would be other hosting providers we would consider, but we just don't get requests for them. So, we mostly focus on AWS and Azure support.
Pros of Amazon EC2
- Quick and reliable cloud servers647
- Scalability515
- Easy management393
- Low cost277
- Auto-scaling271
- Market leader89
- Backed by amazon80
- Reliable79
- Free tier67
- Easy management, scalability58
- Flexible13
- Easy to Start10
- Widely used9
- Web-scale9
- Elastic9
- Node.js API7
- Industry Standard5
- Lots of configuration options4
- GPU instances2
- Simpler to understand and learn1
- Extremely simple to use1
- Amazing for individuals1
- All the Open Source CLI tools you could want.1
Pros of Google Compute Engine
- Backed by google87
- Easy to scale79
- High-performance virtual machines75
- Performance57
- Fast and easy provisioning52
- Load balancing15
- Compliance and security12
- Kubernetes9
- GitHub Integration8
- Consistency7
- Free $300 credit (12 months)4
- One Click Setup Options3
- Good documentation3
- Great integration and product support2
- Escort2
- Ease of Use and GitHub support2
- Nice UI1
- Easy Snapshot and Backup feature1
- Integration with mobile notification services1
- Low cost1
- Support many OS1
- Very Reliable1
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Cons of Amazon EC2
- Ui could use a lot of work13
- High learning curve when compared to PaaS6
- Extremely poor CPU performance3
Cons of Google Compute Engine
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