Wow! Did Docker give up swarm? I thought there was a time when Docker didn't like the existence of k8s all that much.
Anyways, I envision this being very useful for development, may even replace my docker-compose based test setup.
Anyways, I envision this being very useful for development, may even replace my docker-compose based test setup.
Many people ask why would someone use an orchestrator on a small cluster (dozens of hosts). Why not? Swarm is very easy to manage and maintain, using Puppet or Ansible is not less complicated at all.
The future of Docker, Inc. is of course Docker EE, and the future of Docker EE is _not_ the scheduler, it's everything around it.
The idea that dockerized software somehow is less dependent on configuration management seems to be a popular and completely misguided one. The two trends are completely separate, but I would argue from experience that unless you have absolutely nailed the configuration and integration of all your moving parts, don't even look at containers yet.
Containers tend to lead to more moving parts, not less. And unless you know how to configure them, and perhaps even more importantly how to test them, that will only make matters worse.
Containerization does not result in less moving parts in a given environment; but it does result in less moving parts across the whole development flow (from a developer laptop to a production cluster).
Then everything you do on top of that is handled by the container scheduler, and your containers.
I’ve not seen PXE used anywhere that the DC wasn’t O&O (or essentially close to it). As that’s the exception to the rule these days, isn’t your premise a bit cavalier?
I’ve used PXE a lot in my past [0] to great benefit (well, more specifically iPXE through chainloading), so I’m not detracting from it, just saying it’s applicability is limited for most folks.
[0] I wrote “Genesis” for Tumblr which handled initial machine provisioning from first power-on after racking to being ready for deploys.
Really? Is that a new thing? I don’t remember that last time I was reading the docs, but maybe I missed it (that it’s the “preferred” method rather than being just “an option”).
Seems rather odd to limit your audience like that in the age of “cloud everything” as I think it’s generally more rare that folks fully control their layer 2, but what do I know. :)
But in either case, you want the config to be centrally stored, so you can modify it without having to ssh onto every machine.
If you’re on prem with VMware or openstack there’s better options which you can use, but that’s not exactly baremetal. in those environments CoreOS recommends using different provisioning options more suited for those providers.
This is more than naive. As long as your software needs any kind of configuration, there is a need for configuration management. There will be access tokens, certificates, backend configuration, partner integration of various kinds, and monitoring and backup configuration and you will want guarantees that these are consistent for your various testing and staging environments. You will want to track and bisect changes. You can either roll your own framework for this or use Ansible/Puppet.
Whether you distribute your software pieces with tar balls, linux packages or docker images or completely orthogonal to how you tie these pieces to a working whole. And the need for configuration management absolutely increases when moving towards containerized solutions, not by the change in software packaging format but by the organizational changes most go through where more people are empowered to deploy more software which can only increase integration across your environment.
I see organizations that have ignored this because they believe this magic container dust will alleviate the need of keeping a tight grip over what they run, and find themselves with this logic spread over their whole toolchain instead. That's when they need help cleaning up the mess.
I’d love to know who these mythical folks are?
1) dozens of hosts (heck, hosts >1) is exactly why you need orchestration
2) while there are huge deployments across the globe, I wouldn’t consider “dozens of hosts” small by no means. That’s actually probably above average.
3) k8s is actually easier to maintain than you allude. I see these comments about Swarm over k8s generally from folks who never even tried it (or did so years ago), is that the case here?
It just sounds accurate to say it is like trying to be like Google. Well if it is but less complicated then there is no down side.
The complexity overhead of kubernetes may be premature when you don't have massive requirements
Azure also comes with a Swarm-mode deployment template which is pretty great (https://github.com/Azure/acs-engine/blob/master/docs/swarmmo...). However, setting up and running Swarm has been a pleasure.
UCP = Universal Control Plane (web app to manage clusters and containers)
HRM = Host routing mesh (I think). If I recall correctly, it’s used to control ingress to the cluster via virtual host routing, etc.
They are paid Docker Inc. products. I worked for Docker once upon a time so I’m happy to hear there are happy customers :)
Other than that, how have you found EE ? We have considered paying for it, but after seeing Docker Cloud at 15$ per node per month, we are considering switching to it.
however, it does not do termination. You should trivially include a haproxy/nginx pod/service/vm to do the termination for you.
One of the cool new infrastructure features is Docker Cloud - which allows you to "bring your own nodes" for 15$/node/month and setup Swarm. https://docs.docker.com/docker-cloud/cloud-swarm/using-swarm...
I believe it benched a bit worse than the comp but for most cases you're not going to run into issues.
All you need to do is create a docker service out if traefik/nginx/haproxy/whatever and bind the ports of the service to type "ingress". From then on, all traffic is internal - and you deal with it normally from one docker service to another.
I've been looking for a Dokku replacement for running my side-projects on with easy scalability (by provisioning another server), but I haven't found anything that's suitable for running multiple apps together in a heroku-like way but still able to scale beyond a single server. Do you know of anything like that?
For example, I have ten applications, and each requires a database, a redis instance, a celery instance and two web workers. Dokku lets me deploy these independently of each other, but uses the same nginx instance and proxies them transparently.
As I understand it, Swarm has no notion of multiple projects. Each swarm is running a single deployment, where all containers are equal, is that correct?
Basically, Dokku is a self-hosted Heroku, which is what I need (I want to be able to easily create a project that I can run semi-independently of the others on the same server). My understanding is that, to do that with Swarm, I'd have to have a single termination container that would connect to every app, but apps wouldn't be any more segregated than that. Maybe I'm complicating things, though. Have you used Swarm for such a use case?
I tried the official tutorial, but couldn't get it to work, as the instructions appeared outdated and didn't work for single-host deployments, and were geared more towards Windows and Mac than Linux. Would you happen to have a good "getting started" document? All my apps are already using docker-compose.
EDIT: Also, a machine that's a manager doesn't want to join the swarm as a worker as well, that's why I'm saying that it doesn't appear good for single-server deployments:
> Error response from daemon: This node is already part of a swarm. Use "docker swarm leave" to leave this swarm and join another one.
Also, if you are dead-set on making them entirely separate, every separate "application" is a separate "Stack". So you can stack deploy them separately.
If I had to do what you just told me - single nginx proxying to two different "applications" - i would do this. 1. stack 1 - application 1 + network 1 2. stack 2 - application 2 + network 1 3. stack 3 - nginx + network 1
now you can deploy any of them independently. You can make this even more sophisticated by having each stack on a different overlay network (encrypted as well). And nginx bridging between them.
Not sure why you are facing problem with the official tutorial - btw, a manager is a worker ;) I have a fairly large dev swarms on a single node.
We rolled our own go program that just does go tpl substitution in yaml with overrides like helm. Works on charts out of the box, but instead of talking to a service, it outputs a yaml manifest ready to kubectl apply.
We've thought about open sourcing it. It took us literally a day to put together and had worked without flaw for 8 months in production.
* Render the chart and run it through kube-cloud-build[1] to make sure my containers are all built before I deploy: `helm template /path/to/chart | kube-cloud-build -r repo`
* Deploy with helm: `helm upgrade RELEASE_NAME /path/to/chart`
Has been working really well for me.
Swarm was always much simpler to get started with, so some people will prefer it. But it's clear to me which one won.