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Google Kubernetes Engine

Google Kubernetes Engine

Overview

What is Google Kubernetes Engine?

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.

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Recent Reviews
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

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Pricing

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Autopilot Mode - 3 year commitment price (USD)

$0

Cloud
GKE Autopilot Ephemeral Storage Price GB-hr

Autopilot Mode - 1 year commitment price (USD)

$0.0000438

Cloud
GKE Autopilot Ephemeral Storage Price GB-hr

Autopilot Mode - Regular Price

$0.0000548

Cloud
GKE Autopilot Ephemeral Storage Price GB-hr

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://cloud.google.com/kubernetes…

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Starting price (does not include set up fee)

  • $0.04 vCPU-hr Autopilot Mode
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Product Details

What is Google Kubernetes Engine?

Google Kubernetes Engine Video

A Short Explanation into Google Kubernetes Engine

Google Kubernetes Engine Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

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.

Google Kubernetes Engine starts at $0.0445.

Reviewers rate Usability and Support Rating highest, with a score of 9.

The most common users of Google Kubernetes Engine are from Enterprises (1,001+ employees).
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Comparisons

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Reviews and Ratings

(67)

Attribute Ratings

Reviews

(1-2 of 2)
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Borislav Traykov | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Two products I work on are using Google Kubernetes Engine clusters. For the most part, the development efforts mostly go as far as "put service in container," so stuff such as scalability is left to 3rd party components that we use. The Google Kubernetes Engine can use a specific Google-provided ingress controller that is very beneficial when it comes to integrating with other services/products such as Cloud Armor, but it's also vendor-specific, so it has its own quirks and learning curve. Thus, we use the Google Kubernetes Engine just like a regular managed Kubernetes cloud service. The products we have in the Google Kubernetes Engine cluster deal with data piping, collection, and even some machine learning. The major problem that the Google Kubernetes Engine solves for us is a completely managed cloud Kubernetes service - we have an easier time managing our clusters (updates, scaling, and uptime SLA), doing physical and virtual migrations (moving nodes geographically, data in volumes, etc.).
  • 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)
  • It cannot reach true zero scale - they have a competing(?) product for that - Cloud Run Kubernetes clusters. It seems like the Google Kubernetes Engine may not be as flexible as some people need - in terms of costs and infrastructure.
  • Some networking for the Google Kubernetes Engine is way too "hidden" from other similar services from Google Cloud - like network whitelisting (for the control plane), external IPs(s) are not a part of the VPC network overview, data storage.
  • We had to make a hack for node-specific changes (max open file descriptors) because we put Elastic in our Google Kubernetes Engine clusters. These changes were made as hacks because there is still no official API/command approach to have such a form of control over the cluster's infrastructure.
The Google Kubernetes Engine clusters are very good at being a managed cloud K8s platform - lots of documentation, features, and updates are available. It's also newbie-friendly - for both administrators and developers. Unfortunately, currently, it cannot reach true zero scale - thus, costs (rent for the service) are still involved even if you are barely using it.

Thankfully, it's possible to have alternatives in Google Cloud:
  • Your own K8s cluster on Compute Engine VMs - you manage it completely; it will have access to a lot of Google Cloud services.
  • Cloud Run cluster - less documented but more flexible
  • Anthos clusters - you can use this service for a lot of types of K8s clusters - Google Kubernetes Engine, Cloud Run, on-prem, AWS, Azure
  • Ease of use and being newbie-friendly - several teams had to start using Google Kubernetes Engine without any prior K8s knowledge, so they managed to learn and apply on the fly.
  • Integration with other Google Cloud services - SaaS database, networking, etc.
  • Ability to use multiple geographical locations - migrations across locations or cross-zone/region clusters.
  • Positive: Allowed us to start and produce working software regardless of our experience level.
  • Positive: Integration with other Google Cloud services that we wanted to use anyway.
  • Negative: It's kinda clunky, and some scenarios seem Google Kubernetes Engine-specific instead of being more integrated with other Google Cloud services or the web UI.
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.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
We are a B2C PrivacyTech company running multiple GKE clusters in different regions. I am the only DevOps engineer at the company responsible for all GCP-related.
  • Uptime
  • Reliability
  • Easy UI
  • Logging
  • Cost visibility
  • Dull UI
GKE compared to Azure is a lot easier to quickly bootstrap a project for demo purposes. GKE has much better integration with the Kubernetes open-source project and GKE is the first provider to adopt the newest features and it looks like many of the features on the Kubernetes are well suited for GCP purposes.
  • Reliability
  • Customer support
  • Fast running
  • Positive: ROI - GCP excels at value for money wise
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.
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