To use CCP you have to be familiar with Kubernetes and how it works. I've obviously learned a lot about how to use CCP, which I think will be very valuable in the future, but I haven't really learned anything directly about Kubernetes. I did learn the value of certain features that public providers have, like the autoscaling and preemptable VMs. I saw why those are so awesome. My advice would be to be familiar with what you want to do before you try to implement it. I would suggest utilizing CCP if you intend to deploy and manage a lot of clusters from different resource providers. I've never built one completely from source. I have deployed cube clusters using AWS and GKE. I see them as pretty much the same. I don't think one is completely easier than the other between AWS, GKE, and CCP. We don't have to deploy clusters that often. I either change or deploy the cluster on CCP about once a month. It's not like it's saving me tons of time every day. But compared to deploying a cluster on, let's say, Google, it's probably about the same if you're using the actual graphical interface on their respective websites. It doesn't really save me too much time. Right now, we only use one resource provider and it is on-prem. But let's say I had a cluster on-prem and a cluster on AWS that I created with CCP. That's where the time savings would be in terms of managing the clusters from the same platform. That would definitely save me a lot of time. We do have a couple of genomic workflows that are GPU compatible, but we have not had a chance to use any with CCP. That's because of the resources we have don't include GPUs. I'm still getting into it. We don't really need anything too advanced. For running our genomics workflows, we just need to have a Kubernetes cluster that can access the internet. There are no really complex management services or networking services that we use. CCP has a lot of room to grow. I don't think the version I'm using is by any means its final version. I'm not sure how many official releases they've done or what version they intend to put into full production, as a product. But I would rate the version I have, as a development version, as an eight out of ten. If it becomes what I want it to become, what I think it's going to become in the coming months and years, I would rate it a ten.
What is container management? A container is a unit of software that packages together a single application and all its dependencies to make apps easier to develop, deploy, and manage. Containers are also known as operating-system-level virtualizations. While virtual machines package multiple apps, each with their own operating system, containers run on a shared operating system. This allows them to load and run quickly and reliably and move easily to different computing environments....
To use CCP you have to be familiar with Kubernetes and how it works. I've obviously learned a lot about how to use CCP, which I think will be very valuable in the future, but I haven't really learned anything directly about Kubernetes. I did learn the value of certain features that public providers have, like the autoscaling and preemptable VMs. I saw why those are so awesome. My advice would be to be familiar with what you want to do before you try to implement it. I would suggest utilizing CCP if you intend to deploy and manage a lot of clusters from different resource providers. I've never built one completely from source. I have deployed cube clusters using AWS and GKE. I see them as pretty much the same. I don't think one is completely easier than the other between AWS, GKE, and CCP. We don't have to deploy clusters that often. I either change or deploy the cluster on CCP about once a month. It's not like it's saving me tons of time every day. But compared to deploying a cluster on, let's say, Google, it's probably about the same if you're using the actual graphical interface on their respective websites. It doesn't really save me too much time. Right now, we only use one resource provider and it is on-prem. But let's say I had a cluster on-prem and a cluster on AWS that I created with CCP. That's where the time savings would be in terms of managing the clusters from the same platform. That would definitely save me a lot of time. We do have a couple of genomic workflows that are GPU compatible, but we have not had a chance to use any with CCP. That's because of the resources we have don't include GPUs. I'm still getting into it. We don't really need anything too advanced. For running our genomics workflows, we just need to have a Kubernetes cluster that can access the internet. There are no really complex management services or networking services that we use. CCP has a lot of room to grow. I don't think the version I'm using is by any means its final version. I'm not sure how many official releases they've done or what version they intend to put into full production, as a product. But I would rate the version I have, as a development version, as an eight out of ten. If it becomes what I want it to become, what I think it's going to become in the coming months and years, I would rate it a ten.