> look forward to the day that we never have to hear about Kubernetes again.
How do you expect to deploy services in a cluster of multiple nodes communicating over a private software-defined network, then?
How do you expect to deploy services in a cluster of multiple nodes communicating over a private software-defined network, then?
Sure, you may have a few properties in your k8s yaml that change from AWS vs Google vs Azure vs other k8s hosts. That's not something that takes more than a debugging session to get right. That's HUUUGE progress.
"lost" is too strong of a word. To me Docker swarm mode still holds the upper hand in terms of deployment ease and simplicity.
If anyone just wants to bolt together a couple of nodes without much concern regarding performance then Docker swarm mode is perhaps the best option out there at the moment.
However, this is changing very fast. Ubuntu now ships with microk8s which just works and outperforms Docker swarm mode.
Perhaps Docker swarm's worst enemy is how the project was managed and promoted. They had a tool to trivially setup a cluster of nodes with close to zero challenge, but somehow Kubernetes managed to be pushed as the only option.
there u go. As for SDN, why do u even need that? Some simple scripts that manage your server count and their configurations over ssh is all u need.
Do you honestly think this sort of thing, hand-waving included, is a better alternative to
$ kubectl apply -k <kustomize script>
I mean, what are your plans to react to one of your serviceX crapping out? How do you know? How do you recover? How do you roll back? Do you expect to throw more of your ad hoc shell scripts to the mix?
Your example is as good as presenting your deployment strategy as
$ load ""
I dont do rollbacks. If you deploy code that bugs out, you already failed. Because clearly the coders & reviewers did NOT understand the code. Proper testing helps also. And if doom day comes, just deploy a previous commit. It's pretty much the same as what u do with kubernetes. That being said. Kubernetes is indeed much easier for this.
It all comes down to: "do you actually know what you are doing?". If you know what you are doing, all these problems dont happen. If you feel it's important to be able to spin up new servers from scratch every time you deploy. i guess kubernetes is great for that. it's not for me.
As for being able to know what is happening, i do understand that can be impossible sometimes in large companies. Too many developers, too much code. Still, it shouldnt be used as an execuse for breaking the live servers.
Software fails in unforeseen ways, as the goal is for it to not fail but fails anyway. I'm not sure what point you tried to make
> Mostly, they all fail or none of them fail.
No, not really. There is a reason why one of the very basic deployment techniques is to add health checks for each and every service, run a blue-green deployment, and only switch to the new deployment when each and every single health check points to a successful deployment.
The pseudo-code example fails to even do the most basic checks.
Hell, even Ansible supports those.
And, that covers 99.9% of cases anyway. If you want to deploy across multiple nodes run docker compose on multiple nodes and expose the nodes to each other over a vlan that is managed as part of your actual infrastructure where it has a chance of being actually documented and put into a configuration management system.
Indeed, and for a Linux user, you can already build such a system yourself quite trivially by getting an FTP account, mounting it locally with curlftpfs, and then using SVN or CVS on the mounted filesystem.
It doesn’t mean Kubernetes isn’t a useful turnkey solution, especially if it’s managed.
Then your entire engineering org just deploys things.
Need per-application network security policies? Done.
Per app IAM roles? Done.
Secrets management? Done.
Role based access control? Done.
Isolate services to different pools of machines? Done.
Per-app live-updating configuration files across your entire fleet? Done.
CPU, memory or arbitrary per-app metric based auto scaling? Done.
Want to run all this on cheap spot instances? Done.
Want path based HTTP routing within your cluster? Done.
Want an easy deployment mechanism with versioning and rollbacks? Done.
Want simple and consistent service discovery across all your servers? Done.
Want to get advanced and build custom resources to manage groups of other resources whilst taking advantage of k8s management plane in a consistent manner that just works with all the other tooling? Done.
Want to do all this fairly consistently on any cloud vendor, or even on prem? Done.
Want a large pool of candidates familiar with this stack? Done and done.
All those lead to non trivial savings, so you can actually focus on your product and not building a crappy version of Kubernetes by stringing together docker compose instances.
But yes, if you’ve got a single developer and you’re deploying by ssh-ing into a single machine and running git pull, it’s definitely overkill.
Except this breaks less than a homegrown solution would with 100,000x less effort fix, build or maintain.
It's a full time position keeping all the plates spinning in their air, but now It's even harder to debug and reason about. I guess it allows you to quickly start up a new project with some boilerplate configurations though. I wonder if there's a term for that, where you defer things perceived to be "hard" to save time up front. Sort of like a credit card you spend but with technical decisions ...
What does that even mean? Where? Across the entire industry? In specific companies? Empirically how much “more resources”?
Conversely you could ask: if k8s is so terrible and building your own version is so simple, why is the market not doing that?
Everywhere I’ve seen that uses k8s does indeed have full time Devops/platform people, but the ratio to the developers they support is far, far lower than homegrown platforms, as is the time to implement new requirements.
Usually these homegrown solutions get to a specific point in time where there isn’t the internal knowledge to maintain them, and the effort required grows too large. At which point they stagnate. Building on a stagnant, homegrown platform that you don’t know how to improve is not great.
You don't. You get less complexity, actually. Even with Docker, a Docker stack in Docker swarm mode is that simpler and easier to maintain and to monitor and to update and roll back than an unexplainable and impossible to justify docker-compose up.
With Kubernetes, it can be even easier than that. Just grab a distro like Ubuntu, instal microk8s and deploy a kustomize script right out of the bat.
Are you really running away from complexity or just irrationally hating on a tool just because you're oblivious to what it provides for free?