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
Red Hat OpenShift
Score 8.8 out of 10
N/A
OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.
$0.08
per hour
Pricing
Google Compute Engine
Red Hat OpenShift
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
No answers on this topic
Offerings
Pricing Offerings
Google Compute Engine
Red Hat OpenShift
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.
Pricing scale is good. Google Cloud Compute provides additional facilities free of cost (limited storage). Received one year free credits to get started. Nearest regions are available. Others amenities including free repository service available. UI is modern and fast to load. …
[Red Hat] OpenShift is better as an actual environment, whereas Linode and GCE are more cloud-based VPS services. It depends on how fine you want your control, or if you want to have a certain underlying OS. Red Hat [OpenShift] will do more for you as a platform, but if you …
Google Compute Engine is so easy to implement and run. It doesn't require much knowledge to build an app since they provide multiple options to choose from with their prebuilt sample list. We can easily make customization on any website app we built for our client according to their needs and make changes if required.
I've seen multiple universities that have quite investments in Red Hat enterprise virtualization. They don't want to go with the VMware route due to the expense. So Red Hat OpenShift virtualization is a natural fit for them in that environment. I've also seen a lot of VMware customers that are not able financially to sustain the cost increases with the product. So they're looking for an alternative. And Red Hat OpenShift virtualization fills that need.
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
One thing is the way how it works with the GitHubs model on an enterprise business, how the hub and spoke topology works. Hub cluster topology works the way how there is a governance model to enforce policies. The R back models, the Red Hat OpenShift virtualization that supports the cube board and developer workspace is one big feature within. So yes, these are all some features I would call out.
So I don't know that this is a specific disadvantage for Red Hat OpenShift. It's a challenge for anything that Kubernetes face is. There's an extremely large learning curve associated with it and once you get to the point where you're comfortable with it, it's really not bad. But beating that learning curve is a challenge. I've done a couple presentations on our implementation of Red Hat OpenShift at various conferences and one of the slides I always have in there is a tweet from years ago that said, "I tried to teach somebody Kubernetes once. Now neither of us knows what it is."
Leverage OpenShift Online constantly at both the free and paid tiers. While AWS is convenient, it often brings more administration than I want to deal with for a quick application (i.e. Drupal or Wordpress blog). OpenShift also simplifies the DNS registration and ability to share application environments with team members
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.
The virtualization part takes some getting used to it you are coming from a more traditional hypervisor. Customization options are not intuitive to these users. The process should be more clear. Perhaps a guide to Openshift Virtualization for users of RHV, VMware, etc. would ease this transition into the new platform
The Google Compute Engine is constantly up, healthy, and available. I have never experienced any issues with it loading or functioning.Since it is accessible everywhere in the world, it is always available with low latency for all regions.However, I have occasionally seen problems with various NoSQL databases' availability, such as MongoDB, in terms of speed.Overall though, it's always accessible.
Google Compute Engine's performance is up to the standard and I don't really have any complain about that. But website itself does not load quickly and there is a very noticeable delay when the website loads. And no, our system did not our slow down when we integrated Google Compute Engine in our system.
Openshift performance is based on the underlying infrastructure, the K8s design, and the applications' design. Cloud-native applications should have resilience baked in and should not depend on infrastructure resilience. Standard stateful apps may still depend on the underlying infrastructure. It depends on the approach.
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.
Every time we need to get support all the Red Hat team move forward looking to solve the problem. Sometimes this was not easy and requires the scalation to product team, and we always get a response. Most of the minor issues were solved with the information from access.redhat.com
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.
Our developer community is using Red Hat OpenShift for years and they are familiar and comfortable with the product. Red Hat OpenShift UI makes it easier for new developers to adopt without knowing much of Kubernetes. Our platform team feels it’s easy to mange the cluster and upgrades. Other options has more operation overhead and less friendly to developers not have in-depth knowledge of Kubernetes.
It's easy to understand what are being billed and what's included in each type of subscription. Same with the support (Std or Premium) you know exactly what to expect when you need to use it. The "core" unit approach on the subscription made really simple to scale and carry the workloads from one site to another.
