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.
$0.01
Hour
Red Hat OpenShift
Score 9.3 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.
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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.
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More Pricing Information
Community Pulse
Google Compute Engine
Red Hat OpenShift
Considered Both Products
Google Compute Engine
Verified User
Anonymous
Chose Google Compute Engine
Cloud providers offering virtual machines are quite common. I think, Google, however, is arguably one of the top players in the market, with some of the largest (if not the largest) and most advanced server farms in the world. If you're looking for reliability and cost …
The perfect blend of setup flexibility, costing and trust of Google could be my answer to the comparison. This being a server backed service so, ruling out the functions. The Setup flexibility and speed set the GCE apart from Kubernetes. Compliance, regulation and the security …
We have tried using DigitalOcean droplets for some of our minor and non critical VMs. In our experience, Google Compute Engine fares well in comparison the DigitalOcean droplets as they provide better availability, better support and in general, a better experience.
As far as user-friendliness is concerned, I personally rank Google Cloud above both AWS and Azure. Their user interface makes it easy to manage, which is important.
I find Google Compute Engine to be much easier to use than Amazon's EC2 service. The console makes much more sense, permission management is much cleaner, and I'd say the other categories feel on par with EC2: performance, how fine-grained the settings are, connecting to …
The obvious and natural alternatives to GCE are AWS EC2 and Azure VMs. I would say all three are more similar than not. Picking one will most likely depend on what platform you're on already, where your running services are, and which one is more familiar to your team.
When configuring Amazon ECS, it is a bit confusing as you are not able to find the actual issue. You need to enable Additional AppInsights to get detailed level info, which is not a concern when configuring on the Instance Level. Moreover, Azure VM does not provide an …
The Google Cloud computing engine is fair at the top because it bills customers, automatic discounting for extended use, and how fast it can be turned on. We enjoy things around setting it up very easily via APIs and CLI commands, and with the always-on recommendations from …
I have utilised Google Compute Engine in addition to Amazon EC2. Both exhibit excellent performance in terms of consumption, speed, and efficiency.My decision to adopt Google Compute Engine was solely based on how user-friendly it is. more basic UI/UX than EC2.Google's customer …
Google Compute Engine provides on-demand computing resources that are easy to scale up or down according to my organization needs. This allows our business to quickly adapt to changes in demand without having to invest in additional hardware. It also offers a very competitive …
While Amazon EC2 is the best tool for developers to build an app and make it live, It has some downsides too. EC2 requires so much development while Google Compute Engine makes it easy to build an app within a days. EC2 pricing also relatively high compare to Google Compute …
GCE is available in 3 different regions whereas Ec2 is available in 11 different regions. The compute resources offered by the GCE has lower maximum capacity compared to AWS Ec2. The pricing model of GCE offers first 10 mins free and then charging in increments of 10 mins. Both …
I prefer the Compute Engine Over these as it provides us with Better Scalability, Performance, and Reliability Security-related Issues don't arise with the Compute Engine, but yes, in terms of accessing or running, it can be improved a bit as compared to EC2 offered by AWS.
the main reason of choosing GCE is availability and user friendly UI with a very good documentation and API explanations. Great visibility over the infra and security.
The features specific to Google Compute Engine vs Amazon EC2 along with cost and availability are comparable, there may be other services within the vendor which may mean that one is more suitable for specific applications than the other one. We have used both for different …
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 …
AWS has become the de facto standard. Skills in Google Compute Engine and AWS are not easily transferable. Still, after getting to know Google Compute Engine well, productivity can be very high and ROI impressive. There are many additional services offered around Google Compute …
Nothing like OpenShift. Actually, this was our first one. We toyed with maybe doing raw Kubernetes, but with an enterprise company you need an enterprise product.
Comparing the 2, open source Kubernetes is quicker to setup by about 75%, less restrictive, and free of course, but it lacks the security and support of Red Hat, and deploying features is much harder compared to with operators. For buisiness purposes, OpenShift is just more …
Even though Red Hat OpenShift has more overhead than many other Kubernetes flavors, we have selected Red Hat OpenShift because of it's focus on Security and because of it's excellent vendor support.
Red Hat OpenShift has a better security posture than EKS. I enjoy the console on Red Hat OpenShift more as well. I believe there is greater observability for Red Hat OpenShift.
The Tanzu Platform seemed overly complicated, and the frequent changes to the portfolio as well as the messaging made us uneasy. We also decided it would not be wise to tie our application platform to a specific infrastructure provider, as Tanzu cannot be deployed on anything …
It is excellent if you have any workloads that need raw computing or plan to have any state-full services running in your environment like DBs (for which you don't want to use Managed services), cache, etc. It also gives you complete control over which versions of software, OS, etc., you need, and thus, you can build anything and deploy it on GCE.
Red Hat OpenShift, despite its complexity and overhead, remains the most complete and enterprise-ready Kubernetes platform available. It excels in research projects like ours, where we need robust CI/CD, GPU scheduling, and tight integration with tools like Jupyter, OpenDataHub, and Quiskit. Its security, scalability, and operator ecosystem make it ideal for experimental and production-grade AI workloads. However, for simpler general hosting tasks—such as serving static websites or lightweight backend services—we find traditional VMs, Docker, or LXD more practical and resource-efficient. Red Hat OpenShift shines in complex, container-native workflows, but can be overkill for basic infrastructure needs.
A simple web-based interface that is a breeze to train new engineers to use. Our experienced engineers never have trouble finding or doing anything on GCE.
Sustained use and Committed use discounts mean we get top-tier VMs for an incredibly competitive price.
Wonderful identity and access management that gives us peace-of-mind when granting access to machines to contractors and other 3rd parties.
Fast VMs, lastest in hardware, and enough RAM to power even the hungriest of our services.
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.
The L7 load balancer can be difficult to get set up. It's limited in its functionality, especially with the container engine.
It's hard to find certain objects on the web console. Often times the things I need to get to are buried in advanced menus.
Google's decision to only support MySQL on their relational DB service means that I have to manage Postgres instances in Compute on my own, managing everything from storage to backups.
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."
Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.
This is the current strategy for the company, most of the products in the organisation are aligning to Openshift and various use cases it support. Also lot of applications are being developed for AI use case, openshift.AI provides opportunity to host and leverage the AI capabilities for these applications
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
Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes
Redhat openshift is generally reliable and available platform, it ensures high availability for most the situations. in fact the product where we put openshift in a box, we ensure that the availability is also happening at node and network level and also at storage level, so some of the factors that are outside of Openshift realm are also working in HA manner.
The raw computer power is excellent; our applications feel snappy, pages load almos instantly for our customers and so on. The primary reason it is not a perfect 10 is that the native tools for monitoring individual VM performance can be complex, making it challenging to easily diagnose specific resource bottlenecks without significant configuration
Overall, this platform is beneficial. The only downsides we have encountered have been with pods that occasionally hang. This results in resources being dedicated to dead or zombie pods. Over time, these wasted resources occasionally cause us issues, and we have had difficulty monitoring these pods. However, this issue does not overshadow the benefits we get from Openshift.
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
I was not involved in the in person training, so i can not answer this question, but the team in my org worked directly with Openshift and able to get the in person training done easily, i did not hear problem or complain in this space, so i hope things happen seamlessly without any issue.
We went thru the training material on RH webesite, i think its very descriptive and the handson lab sesssions are very useful. It would be good to create more short duration videos covering one single aspect of openshift, this wll keep the interest and also it breaks down the complexity to reasonable chunks.
When configuring Amazon ECS, it is a bit confusing as you are not able to find the actual issue. You need to enable Additional AppInsights to get detailed level info, which is not a concern when configuring on the Instance Level. Moreover, Azure VM does not provide an in-browser option; instead, it is Azure Bastion, but for that, you have to enable a dedicated subnet, which is a bit unnecessary.
We utilized the Thycotic Secret Service to manage all our application secrets, resulting in seamless integration with our applications. We developed all the applications using Red Hat Fuse (currently migrated to Quarkus). We used the built-in Kali Linux support of OpenShift to manage and configure the services and API. Additionally, the Red Hat Developer Studio facilitates faster development.
This is a great platform to deployment container applications designed for multiple use cases. Its reasonably scalable platform, that can host multiple instances of applications, which can seamlessly handle the node and pod failure, if they are configured properly. There should be some scalability best practices guide would be very useful
Scalability means flexibility and less upfront costs
Can become expensive when hard set compute requirements are clear, but things like Spot VMs can help here too, or just having your own infrastructure and scaling up with Google. This is for more advanced cases though
Ramp up time is long, but after that it is quick to do many things and ROI is awesome
It has allowed us to see where we need to be in the container world. I'm going to call it a net neutral impact, not negative or positive. It has given us a sense of what we are ready for and what we're not ready for. You know where you stand.
You don't know what you don't know, so it helps us know what we want to know.