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.
$0
GKE Autopilot Ephemeral Storage Price GB-hr
Red Hat OpenShift
Score 9.1 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.
We have a CICD pipeline, which we wrote using the Gitlab CI file. This is connected directly to our GKE cluster. So, any change in our code will directly start the CICD pipeline. The pipeline first tests the deployment on testing environments. We are also using Helm charts to …
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 …
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.
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.
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.
Our organization went with Google's Kubernetes Engine because we are already significantly invested in the Google Cloud Platform. In our evaluation of Amazon's Elastic Kubernetes Service we were turned off by recent concerns about Amazon becoming overly dominant in the cloud …
Red Hat maintains a consistent user interface across their products, and their feature sets facilitate easy and rapid adoption. Configuration as code is the optimal approach for all of them, and they all provide a level of command-line access that ensures teams can work in the …
OCP and OpenShift Virtualization are better for a code based infrastructure our organization is attempting to move towards shortly. VMware has also been acquired which has added instability with their future. We are planning to move all VMware workloads to OpenShift …
I don't have as much experience with the other two, I have heard of them and know they are container management systems. I have the most experience with Red Hat OpenShift.
Red Hat Enterprise Linux (RHEL), Red Hat Data Grid, Red Hat Integration, Red Hat JBoss Enterprise Application Platform and Red Hat Ansible Automation Platform
As a specialized partner in container platform Red Hat OpenShift is our preffered solution. It provides a supported kubernetes platform which contains all the required tools to make the life of customers easier and offer them the same experience accross all hyperscalers, …
I find OpenShift opinionated but also requiring less configuration to be functional than the other platforms that I've mentioned, and Tanzu requires Faustian contracts to be signed.
Google Kubernetes Engine is well suited for dynamic and large workloads since it can scale up with usage. It is easily configurable, which allows for flexibility. User interface is simple to navigate, which reduces roadblocks for a team with people unfamiliar with Kubernetes. Great if you are already using other GCP services as it integrates well with that.
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.
One of the big advantages of Red Hat OpenShift is, especially over Kubernetes itself, is that it provides a lot of built-in operators for doing a lot of different things right out of the box that you don't have to worry about trying to configure. So one of the big ones is, I mean, right in your face is that user interface and being able to work with it inside of a browser. And I think that works very, very well.
I would say that's the logging part because Red Hat OpenShift write tons of locks and if most time in the finance industry, we cannot use the built in logging infrastructure for compliance reasons. And we have to forward the logs out of the system and this is, it's too much, which we forward from one cluster. Most time we'll build up multi clusters, so we speak about 10 or more clusters. And if you send log files from 10 or more clusters, the logging systems are not prepared to take that much load. And then really often you have license problems with the logging system, so that's not really, really fun. So logging could be improved.
Going to stay with this platform for the unforeseeable future. It matches our Target Architecture 2030 strategy internally to adopt more modularized platforms with Open Source on the back-end so that if needed containerized workloads can move to a different platform. With open-source based application telemetry collection being utilized on the back-end, integrating our already existing oTeL observability based platform makes it easier for our apps to be monitored
It's a great product if you learn it. It has flexibility and is very strong. Autoscaling and Resource management make running huge applications a breeze. Using Helm with Kubernetes and Terraform for infrastructure creation can totally automate your CICD pipeline. You also get easy access to CUDA cores for machine learning.
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
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.
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.
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.
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.
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.
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
When you talk about ROIs, I don't have any negative impacts I wanted to call out here. There is no negative impacts. In fact, it's all positive impacts what we set as our milestones towards achieving our goals, towards achieving our greater vision. Red Hat OpenShift has got a big role in it and it is certainly helping us.
