Reminder to everyone that unless you have a truly massive or complex system, you probably don’t need to run K8s, and will save yourself a ton of headaches avoiding it in favor of a more simple system or using a managed option.
Although I would argue that you need to know what trade offs you are making if you have the right use-case (multiple containers you need to orchestrate, preferably across multiple machines) and you are not using it or a similar tool. There are lots of best-practices and features you get out of the box, that you would have to implement yourself.
You get:
* Deployments and updates (rolling if you so wish)
* Secret management
* Configuration management
* Health Checks
* Load balancing
* Resource limits
* Logging
And so on(not even going into stateful here), but you get the picture. Whatever you don't get out of the box, you can easily add. Want Prometheus? That's an easy helm install away.
Almost every system starts out by being 'simple'. The question is, it going to _stay_ simple? If so, sure, you can docker run your container and forget about it.
I've been holding off setting up a system like Spinnaker because I'd read it was coming (in the form of custom deployment strategies), but can't find anything current on the subject.
https://github.com/kubernetes/kubernetes/tree/master/pkg/con...
At an application level then the strategy consists of having two applications deployed and update the application's ingress after the deployment controller finishes updating the deployments.
That said, if anyone REALLY wants to go the k8s route, it seems like starting with vanilla docker did allow me to get 75% of the work done before I needed to touch k8s itself :)
But, k8s offers a very good way to split the responsibility of managing the infrastructure and managing the applications that run on top. Many people work in medium to big corporations that have a bunch of people that are in charge of managing the compute infrastructure.
I certainly prefer k8s as an API between me and the infrastructure, as opposed to filing tickets and/or using some ad-hoc and often in-house automation that lets me deploy my stuff in a way that is acceptable for the "infrastructure guys".
However, if I use a managed k8s service, I probably don't have to think about any of that. I can focus on the metrics of my application, and not the cluster itself. At least, that's how I think it should work. I haven't used k8s in a while.
That's like saying running windows is the easy part, it's all the add-ons like Microsoft office that make it complicated.
It's running and is more hands off than without it. I'm using a managed digital ocean cluster. I no longer have to worry about patching the OS as it's all handled for me. I also don't have to worry about having a server with a bunch of specialized packages installed, although I suppose only using containers could have gotten me that far.
I haven't had a ton of headaches. So, I guess people's experiences may differ.
It's interesting to me that K8s always draws out the "you probably don't need it" comments.
To me this advice is only useful for tiny startups running a handful of web servers.
Disclaimer: I work at Google Cloud Run.
Cloud Run implements the Knative API, so you can actually take it away and run it on any Kubernetes cluster anywhere on a cloud or in your datacenter.
Source: at mid-sized company who has Istio in the stack.
What ends up happening is that your application consumes services (storage, analytics, etc.). You start using those services from the cloud provider, which makes sense as long as it is the right thing for your business (aligns w/ your cloud-native blueprint).
Kubernetes, by itself, is cloud-provider agnostic.
Overall though it is an amazing service and it is really fast and easy to use.
There is AWS Fargate for Kubernetes, AWS Elastic Kubernetes Service, DigitalOcean Kubernetes, Google Kubernetes Engine etc.
All of which are on the cloud and all of which don't require you to configure host OS etc. Some offer full control over node configuration e.g. EKS whilst others manage that for you e.g. Fargate.
I don't know which part you're not getting, but it appears that this person's intention is not to learn Kubernetes or deal with nodes in the first place.
I run docker compose locally for development. For prod, I just use a different docker compose file (with some values changed, for example the postgres database url etc.). I do this from a 5 USD per month droplet/vm. I can launch multiple services like this for my microservices platform. I can use a hosted database solution for another 15 USD per month, to get backups etc. Also I get a generous 1 TB bandwidth and predictable performance for my system as a whole.
In the past I have used appengine and been bitten by their update times (took more than 20 mins for a single code update, things could have improved now). Also I need to write deployment artifacts for each service.
Now is there any benefit that cloud run (or any paas) could offer compared to this ? Would it be not easier to just stay with docker-compose and defer upgrading to kubernetes until you turn profitable or become unmanageable with a single VM ?
Used nomad/consul/fabio at a previous job for running containers, it was very easy to adopt. Way less new concepts as well.
It's worth mentioning I later chose GCP managed kubernetes for a small cluster to run at my startup. I had to learn a few new things, but I'm not familiar of any "nomad as a service" offerings, so I went with k8s on Google cloud.