Can I use a Rancher desktop to run workload images on the local machine on the Kubernetes cluster in containers and also offload workload on AWS EKS (run local images on AWS EKS cluster EC2 instances )? I mean can I manage both usages together using one Rancher desktop app?
The workload can be printing numbers from 1-20 using for loop and I want to offload this workload(by creating its image )to AWS EKS cloud or offload the workload to machine2 and run its image in a container and bring the output back to my machine.
I was thinking about using rancher or minikube to run local Kubernetes but I needed a tool which can also offload the work to AWS EKS and also to another machine. (binary usage) So I decided to do some research I am stuck at this point. Can Rancher Solve my problems?
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I am trying to deploy this app. https://github.com/taigaio/taiga-docker . This container is a collection of various images. It uses docker-compose to create the container. It is my understanding that this cannot be run as an image from a GCP Artifact Repo as a docker Image. This needs a VM perhaps?
My question is if there is a way to deploy this container as an Image in a serverless fashion in GCP or any other cloud platform. Any pointers/help is much appreciated.
You can either use Cloud Run (the most Serverless way) or on a VM.
On Cloud Run you can deploy a single image as a Service (Cloud Run Terminology), if you have more than one image you can deploy multiple Services and make them talk to each other
Or on VM, that would be as if you are deploying on your personal laptop
I have an application which consists of 2 docker containers. Both are small and need to interact with each other quite often through rest api.
How can I deploy both of them to a single Virtial Machine in Google Cloud?
Usually, when creating virtual machine, I get to chose a container image to deploy: Deploy a container image to this VM instance.
I can specify one of my images and get it running in the VM. Can I set multiple images?
You can not deploy multiple containers per VM.
Please consider this limitation when deploying containers on VMs:
1.You can only deploy one container for each VM instance. Consider Google Kubernetes Engine if you need to deploy multiple containers per
VM instance.
2.You can only deploy containers from a public repository or from a private repository at Container Registry. Other private repositories
are currently not supported.
3.You can't map a VM instance's ports to the container's ports (Docker's -p option).
4.You can only use Container-Optimized OS images with this deployment method. You can only use this feature through the Google Cloud
Platform Console or the gcloud command-line tool, not the API.
You can use docker-compose to deploy multi-container applications.
To achieve this on Google Cloud, you'll need:
ssh access to VM
docker and docker compose installed on the VM
All the solutions I know to deploy a Docker to EC2 involves running it inside a wrapping Ubuntu.
I want to deploy my Ubuntu docker to EC2 so it will be a standalone EC2 image running by itself.
Is that feasible?
You can not launch EC2 with docker image, EC2 uses AWS AMI to launch instance.
One to way to launch your docker image directly with fargate, which does not manage any instance but will run your image as a standalone container.
AWS Fargate is a compute engine for Amazon ECS that allows you to run
containers without having to manage servers or clusters. With AWS
Fargate, you no longer have to provision, configure, and scale
clusters of virtual machines to run containers. This removes the need
to choose server types, decide when to scale your clusters, or
optimize cluster packing. AWS Fargate removes the need for you to
interact with or think about servers or clusters.
I have a set of docker images running in a Kubernates cluster on GKE. I have a Jenkins server running on a VM in GKE.
I have docker builds and GKE deploys running on the Jenkins server, but I would like to start up a 'local' cluster on the Jenkins server after successful builds, run my dockers in that cluster, run my tests towards the cluster, and then close down the local cluster before deploying the docker images to GKE.
I know about minikube, but they state that you are not able to run nested VM's, and I wonder if this blocks my dream of test my cluster before deploying it?
Do I have to run my local cluster on a physical server to be able to run my tests, or is there a solution to my problem?
Have you considered using kubeadm?
You can run a Kubernetes cluster within your Jenkins VM. Setup is a bit different than minikube and it's still in beta but it will let you test your cluster before the final deployment.
I run Rstudio server mostly from an EC2 instance. However, I´d also like to run it from a cluster at work. They tell me that I can setup docker with rstudio and make it run. Now, I´d also like the Rstudios both on EC2 and work to have the same packages and the same versions available. Any idea how I can do this? Can I have both version point to a dropbox folder? In that case, how can I mount a dropbox folder?
You should setup a docker repository on dockerhub or aws ec2 container service (ecs). ECS is a managed service that allows you to easily deploy docker containers onto a cluster of 1 or more ec2 instances that are running the ecs agent (an aws program that helps that cluster work with the ecs). The Dockerfile should install all packages that you need at build time of the image. I suggest referencing the aws ecs documentation, which includes a walkthrough to get you going very quickly (assuming you have an idea of how docker works): https://aws.amazon.com/documentation/ecs/
You should then always run from that docker image, whether you are running on a local or remote machine. One key advantage of docker is that it keeps your application's environments the same (assuming you use the same build of the image) regardless of the host environment.
I am not sure why would not always run on ECS (we have multiple analysts using RStudio, and ECS lets us provision cpu/memory resources to each one, as well as autoscale as needed). You could install docker on EC2 and manage it that way, but probably easier to just install the ecs agent (or use the ecs optimized ec2 ami which has it preinstalled - the docs above walk through configuring it), and use ECS to launch rstudio services.