Google Kubernetes Engine vs. IBM Cloud Kubernetes Service

If your application is complex, if it's planet-scale, or if you need autoscaling, then Kubernetes is best suited. If your application is straightforward, you can opt for App Engine or Cloud Run. In many cases, you can prefer to run the cloud on GKE. But once you deploy on Kubernetes, you get the flexibility to try different things. But if you don't seek flexibility, it's not an option for you.

Incentivized

IBM Cloud Kubernetes Service also stands out in environments where the workloads vary continuously and require befitting scale. The product excels particularly in microservices structures, wherein the companies would harness the capacity for container orchestration and automated scaling. Still, it may face the challenges due to monolith applications that have not been originally developed for using container technology.

• 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)

Incentivized

• IBM has a strong focus on serverless and Kubernetes. This shows in the platform. Deploying containers to Kubernetes was very easy.
• Deploying a Kubernetes cluster through the GUI is very easy and quick. On top of that, IBM Cloud offers a single node cluster for Free.
• Container Registry is a very good product for managing container images. Integration with Kubernetes was seemless.
• Portability. To transition from Google Cloud Kubernetes to IBM Cloud Kubernetes took almost no effort. We mostly use the CLI and the standard tools such as kubectl were present.

Incentivized

• Support of IPv6.
• Better GitOps.
• A "serverless" Kubernetes so we can install Google config connector will be really awesome.
• Container-native load balancers do not support internal TCP/UDP load balancers or network load balancers.

Incentivized

• I constantly get this error even when everything is well configured prefect.exceptions.AuthorizationError: [{'path': ['auth_info'], 'message': 'AuthenticationError: Forbidden', 'extensions': {'code': 'UNAUTHENTICATED'}}]
• Then sometimes the error disapear without changine anything, happened twice to me. Should there be an issue with the authentication service? Please let's improve or let users know why this may be happening.
• Improve the UX in the browse console when removing many images at once
• UX on the process of installing KeyCloack operator

Incentivized

We have our application running on a CentOS compartment on IBM Cloud Kubernetes Service. We have been utilizing the help since IBM Cloud initially dispatched. We liked the adaptability and versatility that IBM Cloud Kubernetes Service give us. Since we are tiny, the Kubernetes administration is just utilized at present inside my venture bunch.

Incentivized

• Google Kubernetes Engine has a good UI and documentation that facilitates setup and helps get projects moving along quickly
• Its built-in logging integrations with StackDriver make it easier to monitor the application and log issues quickly
• Automated orchestration, deployment, and scaling of nodes and networking are all easily configurable with yaml files

Incentivized

We actually haven't had any real problems in our clusters recently and the results we have gotten from adopting IBM Cloud Kubernetes Service have been beyond even our greatest expectations. The community has helped optimize the use of the system and make it relatively simpler to use.

Incentivized

IBM's cloud is almost infallible.

Incentivized

IBM's cloud has a site in my conuntry (MEXICO) so the network latency was almost 0

Incentivized

Very good Kubernetes distribution with a reasonable total price. Integration with storage and load balancer for ingress and services speed up every process deployment.

Incentivized

The self-guided support was solid, and there are plenty of online videos to guide first time users, but I think one area of improvement is a faster way to transfer a large quantity of files from our local machine to the cloud for storage (Aspera)

Incentivized

Online training is really an important resource for using these tools. IBM's help center is rich in useful information and tips. Also, external guides and tutorials are available (e.g. on youtube), but I followed only IBM ones and I had no difficulties.

Incentivized

Ease of use. Very intuitive. We have been looking for a product that allows us to orchestrate our docker containers in a way where it allows us to effectively scale our applications to production. It also provides us a way of monitoring all our infrastructure in a very clear concise way.

Incentivized

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.

Incentivized

We mainly selected [IBM Cloud Kubernetes Service] because IBM fabric blockchain service is mostly compatible with it. To have all the infrastructure in a single cloud to get the best output we selected the [IBM Cloud Kubernetes Service].

Incentivized

IBM's CKS does not offers automatic autoscaling nor vertical scaling (automatic). Other services like Google Kubernetes Engine scales up and down very well

Incentivized

• When issues came up, we reached out to some folks at GCP and they seemed to be very prompt and attentive to our needs. They were always willing to help and provide additional details or recommendations or links to resources. This kind of support is very helpful as it allows us to navigate GKE with more confidence.

Incentivized

• Reduced cloud computing costs.
• Easier management of applications.
• Extra time investment to learn how to setup applications in Google versus Amazon.

Incentivized

• Increased development speed and agility allows to build features faster and more economically.
• Improved resource utilization helps keep applications running very efficiently, which saves on cloud service expenses.
• Scalability and resilience allows for scaling up or down based on demand, which keeps applications running efficiently and more economically.

Incentivized