Docker Enterprise was sold to Mirantis in 2019; that product is now sold as Mirantis Kubernetes Engine. But Docker now offers a 2-product suite that includes Docker Desktop, which they present as a fast way to containerize applications on a desktop; and, Docker Hub, a service for finding and sharing container images with a team and the Docker community, a repository of container images with an array of…
$0
unlimited public repositories
Google Kubernetes Engine
Score 8.1 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
GKE Autopilot Ephemeral Storage Price GB-hr
Pricing
Docker
Google Kubernetes Engine
Editions & Modules
Free
$0
unlimited public repositories
Pro
$5.00
per month per user
Team
$7.00
per month per user
Business
$21
per month per user
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
Docker
Google Kubernetes Engine
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Docker
Google Kubernetes Engine
Considered Both Products
Docker
Verified User
Anonymous
Chose Docker
Our team uses Lando which is built on top of Docker. This makes using Docker even easier.
It is easy to use. we can manage multiple images in docker hub. Docker desktop is for accessing images in our desktop. It is very much user friendly as compare to podman.
Docker is by far the industry leader and mainstay when it comes to virtual machines, its really hard to justify using another service like Vagrant. The upcoming monetization of Docker desktop should make things interesting though.
We need a solution where initially we can use an OS to trigger our pipeline to be used by terraform and then later in ansible. After doing all work it automatically get exited and we can reclaim the space of our VM. So we created a gitlab pipeline and at the initial stage we …
The features and capabilities provided by Docker are incomparable and much vast in nature. Docker is much light weight and easy to onboard into the tech stack. It is also well supported by Container orchestration systems like Kubernetes which will be critical when applications …
Did use containerd or LXC for brief evaluation in the past, but settled on Docker and only see Docker as the mainstay for most organizations I worked in, as the container tool of choice so far. Docker is matured, feature-rich, and reliable enough to be the main choice all …
The reason why we are still using Docker right now is due to that is the best among its peers and suits our needs the best. However, the trend we foresee for the future might indicate Amazon lambda could potentially fit our needs to code enviornmentless in the near future.
Docker provides is effective container management and orchestration platform. It is highly suitable for Linux environments and allows the easy and quick deployment of production applications Other alternatives use replication and management of the virtual machines. Docker …
We have a CICD pipeline, which we wrote using the Gitlab CI file. This is connected directly to our GKE cluster. So, any change in our code will directly start the CICD pipeline. The pipeline first tests the deployment on testing environments. We are also using Helm charts to …
We had to move several products to Google Cloud, and the Google Kubernetes Engine was the option recommended to us, so we investigated it and ran with it. Back then (2019), we were not aware of Cloud Run-provisioned K8s clusters, so our other option was a completely …
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.
In comparison to functionality with EKS and AKS, it has a better upgrade path and the price is lower. Not sure why flannel is the primary overlay network provider but network policies are supported as well.
Google Kubernetes Engine has better upgrades and auto-scale management. Google Kubernetes Engine is also the cheapest option for managed Kubernetes, and Google is the principal contributor to the Kubernetes project.
Our organization went with Google's Kubernetes Engine because we are already significantly invested in the Google Cloud Platform. In our evaluation of Amazon's Elastic Kubernetes Service we were turned off by recent concerns about Amazon becoming overly dominant in the cloud …
You are going to be able to find the most resources and examples using Docker whenever you are working with a container orchestration software like Kubernetes. There will always some entropy when you run in a container, a containerized application will never be as purely performant as an app running directly on the OS. However, in most scenarios this loss will be negligible to the time saved in deployment, monitoring, etc.
Google Kubernetes Engine is well suited for dynamic and large workloads since it can scale up with usage. It is easily configurable, which allows for flexibility. User interface is simple to navigate, which reduces roadblocks for a team with people unfamiliar with Kubernetes. Great if you are already using other GCP services as it integrates well with that.
I have been using Docker for more than 3 years and it really simplifies the modern application development and deployment. I like the ability of Docker to improve efficiency, portability and scalability for developers and operations teams. Another reason for giving this rating is because Docker integrates CI/CD pipelines very well
It's a great product if you learn it. It has flexibility and is very strong. Autoscaling and Resource management make running huge applications a breeze. Using Helm with Kubernetes and Terraform for infrastructure creation can totally automate your CICD pipeline. You also get easy access to CUDA cores for machine learning.
We need a solution where initially we can use an OS to trigger our pipeline to be used by terraform and then later in ansible. After doing all work it automatically get exited and we can reclaim the space of our VM. So we created a gitlab pipeline and at the initial stage we defined a docker file which will be our base image and we performed all our activities inside that image to build infrastructure using terraform. Integration we have done in our gitlab pipeline and finally we remove the docker image so that the space can be reclaimed immediately.
We had to move several products to Google Cloud, and the Google Kubernetes Engine was the option recommended to us, so we investigated it and ran with it. Back then (2019), we were not aware of Cloud Run-provisioned K8s clusters, so our other option was a completely self-managed K8s cluster on Compute Engine VMs, which we did not have the knowledge of and capacity to handle.
It is the only tool in our toolset that has not [had] any issues so far. That is really a mark of reliability, and it's a testimony to how well the product is made, and a tool that does its job well is a tool well worth having. It is the base tool that I would say any organisation must have if they do scalable deployment.