Google Compute Engine is an infrastructure-as-a-service (IaaS) product from Google Cloud. It provides virtual machines with carbon-neutral infrastructure which run on the same data centers that Google itself uses.
$0
per month GB
Google Kubernetes Engine
Score 7.6 out of 10
N/A
Google Kubernetes Engine supplies containerized application management powered by Kubernetes which includes Google Cloud services including load balancing, automatic scaling and upgrade, and other Google Cloud services.
$0.04
vCPU-hr Autopilot Mode
Pricing
Google Compute Engine
Google Kubernetes Engine
Editions & Modules
Preemptible Price - Predefined Memory
0.000892 / GB
Hour
Three-year commitment price - Predefined Memory
$0.001907 / GB
Hour
One-year commitment price - Predefined Memory
$0.002669 / GB
Hour
On-demand price - Predefined Memory
$0.004237 / GB
Hour
Preemptible Price - Predefined vCPUs
0.006655 / vCPU
Hour
Three-year commitment price - Predefined vCPUS
$0.014225 / CPU
Hour
One-year commitment price - Predefined vCPUS
$0.019915 / vCPU
Hour
On-demand price - Predefined vCPUS
$0.031611 / vCPU
Hour
Autopilot Mode - 3 year commitment price (USD)
$0
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - 1 year commitment price (USD)
$0.0000438
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - Regular Price
$0.0000548
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - Spot Price
$0.0000548
GKE Autopilot Ephemeral Storage Price GB-hr
Autopilot Mode - Spot Price
$0.0014767
GKE Autopilot Pod Memory Price GB-hr
Autopilot Mode - 3 year commitment price (USD)
$0
GKE Autopilot Pod Memory Price GB-hr
Autopilot Mode - 1 year commitment price (USD)
$0.0039380
GKE Autopilot Pod Memory Price GB-hr
Autopilot Mode - Regular Price
$0.0049225
GKE Autopilot Price GB-hr
Autopilot Mode - Spot Price
$0.0133
GKE Autopilot vCPU Price vCPU-hr
Autopilot Mode - 3 year commitment price (USD)
$0.02
GKE Autopilot vCPU Price vCPU-hr
Autopilot Mode - 1 year commitment price (USD)
$0.0356000
GKE Autopilot vCPU Price vCPU-hr
Autopilot Mode - Regular Price
$0.0445
vCPU Price vCPU-hr
Standard Mode
$0.10
per hour
Cluster Management
$0.10
per cluster per hour
Cluster Management
$74.40 monthly credit
per month per hour
Standard Mode - Free Version
Free
per hour
Offerings
Pricing Offerings
Google Compute Engine
Google Kubernetes Engine
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Prices vary according to region (i.e US central, east, & west time zones). Google Compute Engine also offers a discounted rate for a 1 & 3 year commitment.
The perfect blend of setup flexibility, costing and trust of Google could be my answer to the comparison. This being a server backed service so, ruling out the functions. The Setup flexibility and speed set the GCE apart from Kubernetes. Compliance, regulation and the security …
We have tried using DigitalOcean Droplets for some of our minor and non critical VMs. In our experience, Google Compute Engine fares well in comparison the DigitalOcean Droplets as they provide better availability, better support and in general, a better experience.
When configuring Amazon ECS, it is a bit confusing as you are not able to find the actual issue. You need to enable Additional AppInsights to get detailed level info, which is not a concern when configuring on the Instance Level. Moreover, Azure VM does not provide an …
The best GCP products - GKE for containerization workload fit to the VM machines specified for different application type (monolithic). These services can be easily integrated with each other with additional benefits.
AWS's UI could use a lot of work, and their API documentation was much worse compared to Google's, which was already tough to read and figure out. Google's free trial of their services through a platform credit (which AWS doesn't offer), also helped us test their compute …
You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.
If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.
Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs
Engine upgrade rollout strategy - well documented and configurable
Integration with other Google Cloud services like the Compute Engine, SaaS databases, and some cloud networking like Cloud Armor
Graphical interface for a lot of operations - either for a quick peek/overview or actual work done by administrators and/or developers (via the Google Cloud Console, for example)
Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.
Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.
Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes
It works great all the time except for occasional issues, but overall, I am very happy with the performance. It delivers on the promise it makes and as per the SLAs provided. Networking is great with a premium network, and AZs are also widespread across geographies. Overall, it is a great infra item to have, which you can scale as you want.
The documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
Google support was great and their presence on site was very helpful in dealing with various issues.
Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.
Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine Learning for ease of usability. It's always good to have an eco-system of products from Google as it's one of the most used search engine and IoT services provider, which helps with ease of integration and updates in the future.
GKE spins up new nodes a LOT faster than AKS. GKE's auto scaler runs a lot smoother than AKS. GKE has a lot more Kubernetes features baked in natively.
When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.