CoreOS rkt / Container Linux (project ended) vs. Google Kubernetes Engine

It is very well suited for local testing where one knows what is being worked on and knows all the dependencies of the software project. On the other hand, it would be less appropriate in situations where a simple chroot can do the trick without the overhead of running a Go application.

Incentivized

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.

Incentivized

• Running a secure container without messing up with low-level details
• Very clear and straightforward approach to building a container
• A way to go for new projects thinking of containers
• Comprehensive and well-written documentation compatible with UNIX keep it simple way of thinking

Incentivized

• Deployment of a new GKE cluster is really fast in comparison to other cloud providers.
• GCP is ahead other vendors and always provide the most up to date Kubernetes version.
• GKE automation for master upgrade and the worker nodes pool works really well.

Incentivized

• Market share, it's often very difficult to find new talent who use CoreOS rkt.
• Lack of wow features, CoreOS rkt doesn't necessarily offer any immediate advantages over other container solutions.

Incentivized

• Not as intuitive as it could be
• Documentation could be better, especially for people using other Google Cloud tools
• Not the preferred Kubernetes Engine for many apps

Incentivized

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.

Incentivized

Google support is excellent and helpful, but the first answer is always so bureaucratic no matter how many logs, evidence, and information you sent.

Incentivized

We evaluated CoreOS rkt and Docker when selecting software solutions for my department. We ended up using CoreOS rkt because of how well it fits with CoreOS and the choice of gRPC for the API. We provide a managed service that runs CoreOS on a bare metal server, CoreOS rkt was a logical choice for compatibility. We also found that developers were having better scusess interacting with gRPC than other container engines REST protocols. It was a close race but eventually there were just enough small benefits to push CoreOS rkt in front of the competition.

Incentivized

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.

Incentivized

• Developers spend less time configuring and more time coding.
• Less time training developers as CoreOS rkt lets them use whatever hardware and operating system they want.
• Reduced our IT costs, solutions are containerized using CoreOS rkt meaning they can write one solution with many developers in mind.

Incentivized

• Compared to other big K8s providers it has the best price/performance factors.
• Upgrade process from stable to regular versions
• Old stable releases: 1.15/1.16 should be in a stable branch.

Incentivized