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 8.6 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.
Well, in our case, because I have two use cases, one is with the operator, which obviously is super easy with OpenShift because it's just click, click start aside from the issue from the operator. But that's a different interview. And the other point is for the web portal that our portal team uses, it's very easy. Two perform a task needed for them to do their deployment, their pipelines, and their daily Java.
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
It provides you with a landing pad to modernize what you have in a phased approach so you don't have to do it all at once, right? You can take small pieces of work and implement those on OpenShift over time. It enables us to be able to implement things like GI ops configuration as a service, and infrastructure as a service using the tools that are native to OpenShift, which gives us far greater reliability and consistency as far as monitoring for any kind of drift and configuration or unauthorized changes. So it pretty much gives us a lot of visibility on things that are otherwise relatively difficult to see using the old means of doing what we do. So it provides us with a modern set of tools to accomplish all those objectives.
Network of observability, so having one single screen to see to have some network-related metrics for the pod levels. Also at the cluster itself level and more importantly is ease of use for troubleshooting when there's any timeout. This has been the single kind of issue I've been facing for my three years of experience with OpenShift and it hasn't been an easy task for such troubleshooting.
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.
As I said before, the obserability is one of the weakest point of OpenShift and that has a lot to do with usability. The Kibana console is not fully integrated with OpenShift console and you have to switch from tab to tab to use it. Same with Prometheus, Jaeger and Grafan, it's a "simple" integration but if you want to do complex queries or dashboards you have to go to the specific console
GCE is highly available system. So far we have not experienced any planned or unplanned outages. We do experience application errors however they are not GCE reated. GCE provides us with wide ranges of option to make systems highly available like block storage, global load balancing, GPU accelerators and Machine Managers which manages different VMs.
It's good in terms of Performance, as compared to other VMs or Compute Engine Services by other providers. Google Compute Engine integrates seamlessly with other Google Cloud Platform services, allowing users to leverage a wide range of tools and services without significant performance degradation.
Applications deployed to OpenShift clusters stay responsive when peak load hits or when the traffic dies down - since the platform reacts by scaling out or scaling in the deployed applications elastically - achieved through' policy sense and response automation - leveraging monitoring, measuring (metrics), auto-scaling to meet SLAs, SLOs, and SLIs. This approach works for stateless or stateful business logic hosting applications. The deployed applications perform consistently, stably, and securely across many deployment platforms - public clouds, private data centers, at the edge, or on factory floors - hosted by bare metal or virtual environments.
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.
Their customer support team is good and quick to respond. On a couple of occassions, they have helped us in solving some issues which we were finding a tad difficult to comprehend. On a rare occasion, the response was a bit slow but maybe it was because of the festival season. Overall a good experience on this front.
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.
We had some existing apps and were looking for a platform to modernize our app deployments and scale for future growth. Based on Kubernetes, OpenShift offers more flexibility and customization. We could deploy any type of containerized application, not just Cloud Foundry-specific ones. I particularly liked the built-in security and its focus on rapid and automated deployments. Moreover, our cloud strategy isn't set in stone. OpenShift's flexibility means we could deploy on-prem, in multiple public clouds, or use a hybrid approach - something other products couldn't offer as expected.
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.
I'll say a lot of positive impact because when we started making this product aware to all the application domains in our business, they saw how easy to use. I mean we are giving a lot of control to the development team, how they can scale their application, how can they check the health of the application, and what action they can take if they are in any kind of failure or even meeting the business's SLA. So there are a lot of capabilities and those are really new features they can use. Those I think are a good use of OpenShift.
