Best-in-market managed Kubernetes solution
We use GKE to deploy our in-hours custom-made applications along with popular public applications like prometheus/grafana. The …
Starting at $0.04 vCPU-hr Autopilot Mode
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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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Pricing
Autopilot Mode - 3 year commitment price (USD)
$0
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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
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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…
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Starting price (does not include set up fee)
- $0.04 vCPU-hr Autopilot Mode
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What is Google Kubernetes Engine?
Google Kubernetes Engine Video
A Short Explanation into Google Kubernetes Engine
Google Kubernetes Engine Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
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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Reviews
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January 22, 2022
Google Kubernetes Engine: Kubernetes clusters offer an easy-to-start experience and good integration with other Google Cloud services
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.
- 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.
January 06, 2022
My experience as a first employee at a startup company using GKE
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
- Reliability
- Customer support
- Fast running
- Positive: ROI - GCP excels at value for money wise
- Azure Kubernetes Service (AKS)
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.
May 15, 2020
Good decision with GKE
GKE provides a seamless installation method across a whole organization. It is a fair starting point with Kubernetes technologies. Managed Kubernetes allows deploying application test pipelines for software companies with a reasonable overall price. Moreover, the number of POP helps setup quite reliable installation in a regional way.
- Deployment method (single, zonal, regional).
- Lifecycle management (stable, regular, rapid).
- Integrated GCE services (loadbalancers).
- Multi-regional deployment (better reliability).
- GPU node availability.
- Integrated market place.
- Compared to other big K8s providers it has the best price/performance factors.
- Upgrade process from stable to regular versions
- Old stable releases: 1.15/1.16 should be in a stable branch.
- Azure Kubernetes Service (AKS)
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.
February 21, 2020
Goggle Kubernetes delivered from who knows Google Kubernetes
Google has made the setup of Google Kubernetes Engine easy in the Google Cloud, it comes somewhere in the middle of Iaas and Paas, the user interface is very intuitive, and you can manage your cluster directly through the web interface. It is an excellent tool with lesser management overhead with servers or Kubernetes installation, etc. At the same time gives you the flexibility to manage the cluster and related settings. You can scale up with a few clicks or set up automated scaling based on traffic and various parameters.
- Automated orchestration, deployment, and scaling of containers
- Integrated Logging
- Persistent storage configuration and options.
- Routes and external DNS integration
- It's not necessary to buy licenses like other Kubernetes based products.
- It's not required to buy blades, hosts, and virtualization.
- Amazon Elastic Container Service (Amazon ECS)
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.