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‫Some of the commands you've been using, so far, have

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‫a little bit of automation behind them known as

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‫generators. Generators you can think of like templates.

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‫They essentially create the spec, or the specification,

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‫to apply to the Kubernetes cluster based

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‫on your command line options.

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‫You think of commands like run, and expose,

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‫and create. They often will have generators behind

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‫them that give the template necessary

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‫with all the fields and the defaults that you're not

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‫necessarily specifying at the command line.

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‫Essentially, the point of these generators is to make it

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‫easier for you to use one-line commands, like you've been

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‫used to with Docker, and Docker Compose, and Swarm.

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‫To use those one-line commands in Kubernetes while

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‫leaving some of the more advanced settings up to defaults.

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‫Really, Swarm does this, too.

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‫Swarm has a lot of defaults when you create services and

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‫stacks that are all happening in the background.

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‫You just don't know it. These generators are like that.

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‫Here is an example where we're creating a Deployment

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‫with the create command, and we're giving it a couple of

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‫options to meet the minimum requirements.

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‫It will fill in the rest of the specification

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‫with a generator.

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‫These generators are different for each type of thing

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‫you're creating. Whether it's a service, or deployment,

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‫or a job, or a cron job.

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‫Other stuff we'll talk about later.

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‫Those generators can actually change over

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‫time as each version of Kubernetes comes out.

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‫They might change one or two properties of that

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‫specification.

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‫So, these have versions.

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‫Sometimes if you've seen in documentation you might see

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‫some YAML for Kubernetes, and it says something about beta.

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‫That's often when a generator is first created,

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‫it might have a beta version and then as it graduates

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‫to a mature generator, it'll have a V1.

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‫We can't really get a list of generators at the command

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‫line because it spans different commands and different

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‫options what generators might get used.

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‫The easiest way here throughout all these different

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‫commands to see what would be generated if you type

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‫that command against a cluster, is to use two options.

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‫The dry run, which is a really neat way to show

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‫the output of what you typed, and we'll see that

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‫in a second. Then the -o, which means

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‫output. We're saying we want an output in YAML.

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‫We're essentially saying run this command but don't

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‫technically do it on the cluster.

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‫Just try it out to see what would happen if I did it.

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‫Then at the same time, show me the YAML output

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‫of what would be generated if I finish this command.

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‫You'll get nice little templates essentially.

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‫You could even use that to start creating your own YAML

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‫that we'll use in later lectures.

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‫Finally, generators here.

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‫You might also consider them opinionated defaults.

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‫They really aren't opinionated.

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‫They're super small.

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‫They're usually 10 to 15 lines of YAML.

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‫Just the bare minimum to get a thing started.

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‫They do have opinions, though, which is why they're having

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‫versions. You might see a beta version graduate and

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‫whatnot. I do consider them opinionated

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‫but they're fine, right. They're going to work for most use

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‫cases when you're just trying things out for dev and test.

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‫Let's go through a couple of examples to see these

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‫generators at the command line.

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‫The first one here is a Deployment like we've used before.

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‫The create deployment.

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‫You'll notice that I put the --dry-run at the end.

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‫If you just do a dry run, it will only spit out

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‫the type of resource it would create.

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‫This is similar to the name of the resource we see when we

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‫list it out with a kubectl get command.

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‫If I hit the up arrow there and type -o

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‫yaml on the end, it will then show me

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‫the YAML output that it generated with that command.

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‫We're going to go through YAML specifications

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‫later. For now, you can see the major parts

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‫of what was done in the background when we did that

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‫create deployment command.

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‫First, it shows the API version, the version

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‫of this type of resource.

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‫So, we're using a apps/v1 version

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‫here. The kind is the deployment, and

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‫that's because we're creating a Deployment.

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‫If it was a Job, it was say job.

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‫If it was a Service, it would say service.

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‫That kind of thing. The metadata is always going to be

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‫there for any resource you create.

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‫It will have the timestamp, which is optional, because it

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‫will generate that automatically when you really create

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‫this thing. Then you're going to have labels and then a

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‫name attribute here that you can specify.

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‫In this case, you're seeing that it's filled a lot of this

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‫in with what I gave it at command line.

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‫I told it I wanted to call it test.

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‫So, it's giving it a name of test.

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‫It's assigning it an app since we're using a Deployment

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‫here, it considers it an app, not a service or something

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‫else. It'ss calling that label test.

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‫These are just defaults out-of-the-box.

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‫Then the spec for the Deployment

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‫is replicas of one.

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‫The selector we'll get into later, but that's essentially

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‫how this thing determines to select the pods inside

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‫this Deployment. It's basically what matches that

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‫Deployment to its pods.

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‫Then strategy. Which we leave blank.

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‫The template here is for the ReplicaSet.

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‫Then you'll see under that spec the containers that it will

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‫create. So, there's a little bit of a nested layer of spec

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‫thing going on here. That's due to the complexity of these

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‫layers, right. We have pods, then ReplicaSets, and then

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‫Deployments on top of that.

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‫You can see that it's creating all that on the fly, and

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‫we'll apply that to the API when we hit

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‫this command.

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‫Let's create a few more here. The second one is using Jobs

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‫instead Deployments. It's usually designed when

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‫you want to create a set of pods that will run once.

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‫It tends to set them with a default to not restart.

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‫In this case, we're going to use the same image, the same

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‫name. We're going to dry run it with the -output

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‫yaml. You'll see how much different it is.

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‫In this case, since we don't have the multiple levels of

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‫a Deployment with ReplicaSet nested inside it, we

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‫don't need the multiple levels of spec.

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‫You'll see, first off, that this one is much shorter.

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‫That's largely due to the fact that with Deployments, it

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‫creates a nested ReplicaSet which then creates

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‫the pod. So, there's multiple levels there.

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‫Where here, we really just have this batch job

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‫creating pods directly for us.

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‫You can see up at the top that the API version and the kind

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‫have both changed.

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‫The metadata is very similar, although in this case, it

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‫didn't create an app label.

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‫The spec is just for the Jobs

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‫and then below it, the spec inside it, inside that

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‫template, is the spec for

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‫each container pod, right.

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‫This one spec would be created for however

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‫many I asked it to create.

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‫We only created one by default.

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‫So, it's going to have one container running Nginx with

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‫the name test. You'll notice that the restart policy

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‫is never. That's the change, really, with

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‫most of these other ways of creating containers in

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‫Kubernetes. They will automatically try to recreate, or

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‫restart. With a job, or later

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‫with a cron job, you'll see that the restart policy is set

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‫to never. Because typically once a job finishes,

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‫it's just done, and you don't want that container recreate

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‫it. Lastly, let's do an expose command.

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‫Even though there's a dry run here,

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‫when you run expose deployment, it's going to check

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‫for that deployment and realize that it doesn't exist, so

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‫it can't give you the sample output because it doesn't

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‫really have the valid input.

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‫In this case, we technically need to create a Deployment.

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‫In this one, we don't need it to be dry run and

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‫output. We just want it to create it.

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‫So, let's just do that.

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‫Then, let's go back up to that expose command and

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‫try it again. Then that dry run will

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‫work this time. We'll have an API version of V1.

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‫You'll notice that the Service is the kind now instead of

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‫Deployment or Job.

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‫Then, we've got other similar labels.

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‫You'll see that the spec is all about ports and protocols

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‫because that's really what a Service is.

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‫It's the combination of network routes

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‫and IP subnetting and TCP or UDP ports,

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‫and stuff like that. Generators aren't necessarily a huge

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‫deal. You don't need to memorize them or learn the

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‫differences between all of them. Because as you'll find a

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‫lot of them with the kubectl run command are going away,

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‫as you'll find out in a minute. Then in a later lecture,

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‫we'll talk more about the types of ways you create

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‫containers and maybe why you won't be using a whole

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‫lot of run and creates in your production workloads.

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‫Remember to delete the test deployment if you created it

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‫for our last command where we tested the expose.