Google Kubernetes Engine vs Joyent Triton: What are the differences?
What is Google Kubernetes Engine? Deploy, manage, and scale containerized applications on Kubernetes, powered by Google Cloud. Container Engine takes care of provisioning and maintaining the underlying virtual machine cluster, scaling your application, and operational logistics like logging, monitoring, and health management.
What is Joyent Triton? Transform an entire data center into an easy to manage, elastic Docker host. Simple and proven. Securely deploy and operate containers with bare metal speed on container-native infrastructure, your cloud or ours.
Google Kubernetes Engine and Joyent Triton can be primarily classified as "Containers as a Service" tools.
Some of the features offered by Google Kubernetes Engine are:
- Docker support - Improve the predictability of your deployments with Docker containers. Containers make it easy to deploy applications across environments.
- Better ops - Give ops a better system, starting with a managed compute cluster. Container Engine takes care of provisioning and maintaining the underlying virtual machines and operational logistics like logging, monitoring, and health management.
- Declarative management - Use declarative syntax to define your application requirements. Container Engine will actively manage your application, ensuring your containers are running and scheduling additional as needed.
On the other hand, Joyent Triton provides the following key features:
- Bare metal performance
- Container-native networking
- Container-native networking
What is Google Kubernetes Engine?
What is Joyent Triton?
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We began our hosting journey, as many do, on Heroku because they make it easy to deploy your application and automate some of the routine tasks associated with deployments, etc. However, as our team grew and our product matured, our needs have outgrown Heroku. I will dive into the history and reasons for this in a future blog post.
We decided to migrate our infrastructure to Kubernetes running on Amazon EKS. Although Google Kubernetes Engine has a slightly more mature Kubernetes offering and is more user-friendly; we decided to go with EKS because we already using other AWS services (including a previous migration from Heroku Postgres to AWS RDS). We are still in the process of moving our main website workloads to EKS, however we have successfully migrate all our staging and testing PR apps to run in a staging cluster. We developed a Slack chatops application (also running in the cluster) which automates all the common tasks of spinning up and managing a production-like cluster for a pull request. This allows our engineering team to iterate quickly and safely test code in a full production environment. Helm plays a central role when deploying our staging apps into the cluster. We use CircleCI to build docker containers for each PR push, which are then published to Amazon EC2 Container Service (ECR). An
upgrade-operator process watches the ECR repository for new containers and then uses Helm to rollout updates to the staging environments. All this happens automatically and makes it really easy for developers to get code onto servers quickly. The immutable and isolated nature of our staging environments means that we can do anything we want in that environment and quickly re-create or restore the environment to start over.
The next step in our journey is to migrate our production workloads to an EKS cluster and build out the CD workflows to get our containers promoted to that cluster after our QA testing is complete in our staging environments.
Since it is mostly backed by Kubernetes, GCE looks really promising. I did run into some fuzzy bugs as I did expect with Alpha.
I recommend giving it a lab-test-try and engage in discussion about Kubernetes.