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‫In the last video, I covered Imperative vs.

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‫Declarative. We talked about the specifics in Kubernetes

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‫of one or the other.

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‫Really, when you look at the Kubernetess documentation, it

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‫lends itself towards three, different styles.

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‫There's a subtle difference, but they're

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‫really on a spectrum of all the way on imperative on one

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‫side and all the way declarative on the other.

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‫Then this nice, little option in the middle if you so

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‫choose to use it. In this course, so far,

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‫I've been teaching you the strict, imperative CLI

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‫commands. That includes run, expose.

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‫Maybe we have scale.

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‫We didn't cover edit but it does exactly what you think it

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‫would. It edits a resource in real time.

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‫Or create deployment, which is the new way to do a run.

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‫These are really best for learning how things

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‫work. Learning the resource types and what they do, and

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‫personal projects and really small setups where maybe

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‫you're the only person in charge. You're not trying to

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‫automate. You're not trying to build out a full production

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‫workflow, and CICD, right.

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‫That's great for those.

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‫Then there's this nice middle ground that Kubernetes offers

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‫you with the create commands

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‫that you can either use the create commands themselves, but

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‫you can also use those with a YAML file.

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‫You can use create  -f, and you

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‫can give it one of those specs like we saw earlier.

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‫You can give it a spec, and it will create any of

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‫the objects you have in there. You could have multiple

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‫objects in that file. You could have a deployment, plus a

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‫service, in there.

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‫Maybe some storage needs that you have, networking

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‫setups, whatever. You could have all that one nice file.

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‫Then, if you needed to replace anything in

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‫there, you could edit the file and then use the replace

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‫command, which we haven't covered yet, but it does what you

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‫think it does. Then, there's the delete command, which we

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‫have used, which does what you think it does as well.

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‫The nice thing here is it's kind of middle ground, right.

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‫It forces you to use YAML so that you've documented

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‫what you're doing, and you have this change record if

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‫you're using something like git.

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‫Hopefully you're using git.

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‫The benefit there, though, is for us humans,

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‫we're using the create, or the replace,

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‫or the delete. So, it gives us this explicit verb

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‫to use so we know we're not accidentally

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‫deleting something when we're using a create command.

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‫And we know we're not accidentally deleting something when

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‫we use the replace command.

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‫So that helps, right.

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‫That's a good, middle ground as you get your feet wet in

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‫the YAML specifications that you're going to need to use

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‫when you get to the full, declarative object

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‫model. That is what I was talking about earlier.

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‫That is where you're only using YAML and you're only

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‫using the apply command.

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‫There's other commands to help you with the apply, like the

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‫diff, which will show you the changes you're about to take.

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‫But, apply is simply editing

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‫YAML, running the apply.

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‫Edit some more YAML, run the apply.

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‫This is similar to Swarm where we had Swarm stacks.

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‫If you remember, there's a docker stack deploy command

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‫and in order to update those, you use the same command over

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‫and over and over again.

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‫That's the same style here with their full-on declarative

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‫objects. It's nice that they have documentation, and you'll

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‫see this in the resource links for this lecture, a

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‫very detailed page on these three different types.

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‫I encourage you to check that out.

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‫The real rule I'm going to give to this whole

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‫thing, even if you go read the resource page about it, is

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‫to just not mix the three approaches.

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‫It's more important that you don't mix these three when

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‫you have true production dependencies.

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‫In production, I'm really going to advocate you try to

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‫stick with, as early as you can in your

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‫model of maturity, with the

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‫full-on declarative model using the YAML files

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‫with the apply command.

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‫The sooner you get comfortable with that, the sooner you

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‫are used to documenting that in YAML and

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‫saving it in a git-commit every time you change it, that

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‫process will really benefit you later on.

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‫When anyone wants to see changes you have, they can go look

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‫at the git-log. Most of us are probably doing something

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‫in git today so creating another git repo just to store

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‫these YAMLs isn't going to be a lot of effort for you,

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‫right. Even if you're just doing git locally on your

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‫machine, git locally can

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‫basically help you see the history of changes that

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‫you've done to these YAMLs so that when you forget in six

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‫months what you changed three months ago, you can go back

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‫and look and see what you're doing there.

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‫That is really going to save you a lot of time.

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‫The most important rule is don't mix the approaches.

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‫If you create something with run, it's going to be harder

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‫later to use the apply to manage that resource.

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‫There are little tricks of the trade you can get around

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‫with some of these commands to try to edit objects later

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‫without screwing them up.

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‫But really, if you're going to be doing production, you

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‫probably shouldn't start with those run commands on your

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‫production server. You should probably think long term and

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‫stick with the YAML. My four tips here are

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‫learning the command line like you're doing.

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‫Learn that imperative command line so that you can operate

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‫it locally. And you will need those commands sometimes for

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‫troubleshooting, and testing, and servers as well.

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‫Then as quickly as you can for getting ready for your first

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‫production Kubernetes is to learn the apply command,

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‫the diff command, the YAML specification

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‫for all the resource types you're going to use.

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‫Then storing it in git like I'm saying.

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‫Even if it's just local git or git repos somewhere

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‫that your team can use.

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‫Remember, this method of editing the YAML,

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‫saving the change in git, then applying it with

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‫kubectl apply, then saving it again,

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‫and storing changes in git.

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‫This process will get you down the road

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‫of DevOps automation and to that git-ops

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‫that I mentioned earlier, which is I think where some of

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‫these tools are starting to go. Where we're git centric.

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‫We're doing changes in a git repo just like software

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‫coders do..

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‫We're doing the same thing with this DevOps workflow.

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‫We're sort of adopting the way that they do their change

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‫work in a team for our own operations and tooling.