Google App Engine is Google Cloud's platform-as-a-service offering. It features pay-per-use pricing and support for a broad array of programming languages.
$0.05
Per Hour Per Instance
IBM Cloud Kubernetes Service
Score 7.9 out of 10
Mid-Size Companies (51-1,000 employees)
IBM Cloud Kubernetes Service is a
managed Kubernetes offering, delivering user tools and built-in security for rapid delivery of applications
that users can bind to cloud services related to IBM Watson®, IoT, DevOps
and data analytics. As a certified K8s provider, IBM Cloud Kubernetes
Service provides intelligent scheduling, self-healing, horizontal
scaling, service discovery and load balancing, automated rollouts and
rollbacks, and secret and configuration management. The Kubernetes…
App Engine is such a good resource for our team both internally and externally. You have complete control over your app, how it runs, when it runs, and more while Google handles the back-end, scaling, orchestration, and so on. If you are serving a tool, system, or web page, it's perfect. If you are serving something back-end, like an automation or ETL workflow, you should be a little considerate or careful with how you are structuring that job. For instance, the Standard environment in Google App Engine will present you with a resource limit for your server calls. If your operations are known to take longer than, say, 10 minutes or so, you may be better off moving to the Flexible environment (which may be a little more expensive but certainly a little more powerful and a little less limited) or even moving that workflow to something like Google Compute Engine or another managed service.
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.
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.
There is a slight learning curve to getting used to code on Google App Engine.
Google Cloud Datastore is Google's NoSQL database in the cloud that your applications can use. NoSQL databases, by design, cannot give handle complex queries on the data. This means that sometimes you need to think carefully about your data structures - so that you can get the results you need in your code.
Setting up billing is a little annoying. It does not seem to save billing information to your account so you can re-use the same information across different Cloud projects. Each project requires you to re-enter all your billing information (if required)
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
App Engine is a solid choice for deployments to Google Cloud Platform that do not want to move entirely to a Kubernetes-based container architecture using a different Google product. For rapid prototyping of new applications and fairly straightforward web application deployments, we'll continue to leverage the capabilities that App Engine affords us.
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.
I had to revisit the UI after a year of just setting up and forgetting. The UI got some improvements but the amount of navigation we have to go through to setup a new app has increased but also got easier to setup. Gemini now is integrated and make getting answers faster
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.
Good amount of documentation available for Google App Engine and in general there is large developer community around Google App Engine and other products it interacts with. Lastly, Google support is great in general. No issues so far with them.
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)
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.
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.
We were on another much smaller cloud provider and decided to make the switch for several reasons - stability, breadth of services, and security. In reviewing options, GCP provided the best mixtures of meeting our needs while also balancing the overall cost of the service as compared to the other major players in Azure and AWS.
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].
IBM's CKS does not offers automatic autoscaling nor vertical scaling (automatic). Other services like Google Kubernetes Engine scales up and down very well
Effective integration to other java based frameworks.
Time to market is very quick. Build, test, deploy and use.
The GAE Whitelist for java is an important resource to know what works and what does not. So use it. It would also be nice for Google to expand on items that are allowed on GAE platform.
