Draft is an open-source tool originally released by Microsoft that helps developers streamline the processes of developing container-based applications running on Kubernetes clusters.
N/A
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
Draft (open source)
Google Kubernetes Engine
Editions & Modules
No answers on this topic
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
Draft (open source)
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
Free and open source under an MIT license.
—
More Pricing Information
Community Pulse
Draft (open source)
Google Kubernetes Engine
Considered Both Products
Draft (open source)
No answer on this topic
Google Kubernetes Engine
Verified User
Anonymous
Chose Google Kubernetes Engine
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 …
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.
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 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.