I'm just getting started with kubernetes and setting up a cluster on AWS using kops. In many of the examples I read (and try), there will be commands like:
kubectl run my-app --image=mycompany/myapp:latest --replicas=1 --port=8080
kubectl expose deployment my=app --port=80 --type=LoadBalancer
This seems to do several things behind the scenes, and I can view the manifest files created using kubectl edit deployment, and so forth However, i see many examples where people are creating the manifest files by hand, and using commands like kubectl create -f or kubectl apply -f
Am I correct in assuming that both approaches accomplish the same goals, but that by creating the manifest files yourself, you have a finer grain of control?
Would I then have to be creating Service, ReplicationController, and Pod specs myself?
Lastly, if you create the manifest files yourself, how do people generally structure their projects as far as storing these files? Are they simply in a directory alongside the project they are deploying?
The fundamental question is how to apply all of the K8s objects into the k8s cluster. There are several ways to do this job.
Using Generators (Run, Expose)
Using Imperative way (Create)
Using Declarative way (Apply)
All of the above ways have a different purpose and simplicity. For instance, If you want to check quickly whether the container is working as you desired then you might use Generators .
If you want to version control the k8s object then it's better to use declarative way which helps us to determine the accuracy of data in k8s objects.
Deployment, ReplicaSet and Pods are different layers which solve different problems.All of these concepts provide flexibility to k8s.
Pods: It makes sure that related containers are together and provide efficiency.
ReplicaSet: It makes sure that k8s cluster has desirable replicas of the pods
Deployment: It makes sure that you can have different version of Pods and provide the capability to rollback to the previous version
Lastly, It depends on use case how you want to use these concepts or methodology. It's not about which is good or which is bad.
There is a little more nuance to the difference between apply and create than what is already mentioned here. Kubectl create can be used imperatively on the command line or declaratively against a manifest file.
Kubectl apply is used declaratively against a manifest file. You can't use kubectl apply imperatively.
One key difference is when you already have an object and you want to update something. Even if you used a manifest file with kubectl create, you will get an error when you use kubectl create again to update the same resource. But, if you use kubectl apply, you will not get an error. It will update the resource without any issues.
So, the convention is to use kubectl apply to create AND update resources, kubectl create is used to create resources, and kubectl run is used to create a pod with a specific image, namespace, etc. for experimentation and testing with the --dry-run=client option.
Related
I feel like I have a terrible knowledge gap when it comes to managing the resource states within Kubernetes.
Suppose I have 2 deployments in my cluster, foo1 and foo2. They are both defined in separate yaml files, foo1.yaml and foo2.yaml that are both inside a my-dir directory and have been applied with kubectl apply -f my-dir/
Now I want to make a third deployment, but also delete my second deployment. I know that I can do this in 2 steps:
Make another foo3.yaml file inside the directory and then do kubectl apply -f my-dir/foo3.yaml
Run kubectl delete -f my-dir/foo2.yaml to get rid of the second deployment.
My question is, can I do this in one shot by keeping the "desired state" in my directory. i.e. Is there any way that I can delete foo2.yaml, create a new foo3.yaml and then just do kubectl apply -f my-dir/ to let kubernetes handle the deletion of the removed resource file as well? What am I missing here?
The best and easiest way is to use some DevOps tools like jenkins, ansible or terraform for managing your deployments. If you don’t want to use external tools there is a python library for managing kubernetes. You can fetch the details of your kubernetes resources, deployments, pods etc., using this library you can also manage your kubernetes cluster. Similarly if you want to remove the deployment files you just need to add a few more lines for deleting the file.
I am seeing multiple and different explanations for imperative Vs Declarative for Kubernetes - something like Imperative means when we use yaml files to create the resources to describe the state and declarative vice versa.
what is the real and clear difference between these two. I would really appreciate if you can put the group of commands fall under the same - like Create under imperative way etc ..
"Imperative" is a command - like "create 42 widgets".
"Declarative" is a statement of the desired end result - like "I want 42 widgets to exist".
Typically, your yaml file will be declarative in nature: it will say that you want 42 widgets to exist. You'll give that to Kubernetes, and it will execute the steps necessary to end up with having 42 widgets.
"Create" is itself an imperative command, but what you're creating is a Kubernetes cluster. What the cluster should look like is determined by the declarations in the yaml file.
Imperative
Official docs on Managing Kubernetes Objects Using Imperative Commands.
Kubernetes objects can quickly be created, updated, and deleted directly using imperative commands built into the kubectl command-line tool.
kubectl run nginx --generator=run-pod/v1 --image=nginx
kubectl create service nodeport <myservicename>
kubectl delete pod
Declarartive
Kubernetes objects can be created, updated, and deleted by storing multiple object configuration files in a directory and using kubectl apply to recursively create and update those objects as needed. This method retains writes made to live objects without merging the changes back into the object configuration files. kubectl diff also gives you a preview of what changes apply will make.
Official docs on Declarative Management of Kubernetes Objects Using Configuration Files.
Official docs on Declarative Management of Kubernetes Objects Using Kustomize
Define what you want in an yaml file and use kubectl apply
kubectl apply -f app.yaml
kubectl apply -f <directory>/
kubectl apply -f https://k8s.io/examples/application/simple_deployment.yaml
Imperative command means::: We are not creating any yaml file and directly changing resources like pod service network anything via
Command line so that is imperative command.
Imperative object configuration::: means we are creating any resources as per our requirement in yaml file where we will remove
default value's which we don’t need everything except required things so in that case this is imperative object configuration AND that is CREATE command..
Declarative object configuration:: We don’t care about anything just we need final output so in simple words we copied
yaml from internet and created a pod where motive is to only create pod/resources So in that case we use APPLY command.
Most Kubernetes objects can be created with kubectl create, but if you need e.g. a DaemonSet — you're out of luck.
On top of that, the objects being created through kubectl can only be customized minimally (e.g. kubectl create deployment allows you to only specify the image to run and nothing else).
So, considering that Kubernetes actually expects you to either edit a minimally configured object with kubectl edit to suit your needs or write a spec from scratch and then use kubectl apply to apply it, how does one figure out all possible keywords and their meanings to properly describe the object they need?
I expected to find something similar to Docker Compose file reference, but when looking at DaemonSet docs, I found only a single example spec that doesn't even explain most of it's keys.
The spec of the resources in .yaml file that you can run kubectl apply -f on is described in Kubernetes API reference.
Considering DeamonSet, its spec is described here. It's template is actually the same as in Pod resource.
For the debug and testing purposes I'd like to find a most convenient way launching Kubernetes pods and altering its specification on-the-fly.
The launching part is quite easy with imperative commands.
Running
kubectl run nginx-test --image nginx --restart=Never
gives me exactly what I want: the single pod not managed by any controller like Deployment or ReplicaSet. Easy to play with and cleanup when it needed.
However when I'm trying to edit the spec with
kubectl edit po nginx-test
I'm getting the following warning:
pods "nginx-test" was not valid:
* spec: Forbidden: pod updates may not change fields other than spec.containers[*].image, spec.initContainers[*].image, spec.activeDeadlineSeconds or spec.tolerations (only additions to existing tolerations)
i.e. only the limited set of Pod spec is editable at runtime.
OPTIONS FOUND SO FAR:
Getting Pod spec saved into the file:
kubectl get po nginx-test -oyaml > nginx-test.yaml
edited and recreated with
kubectl apply -f
A bit heavy weight for changing just one field though.
Creating a Deployment not single Pod and then editing spec section in Deployment itself.
The cons are:
additional API object needed (Deployment) which you should not forget to cleanup when you are done
the Pod names are autogenerated in the form of nginx-test-xxxxxxxxx-xxxx and less
convenient to work with.
So is there any simpler option (or possibly some elegant workaround) of editing arbitrary field in the Pod spec?
I would appreciate any suggestion.
You should absolutely use a Deployment here.
For the use case you're describing, most of the interesting fields on a Pod cannot be updated, so you need to manually delete and recreate the pod yourself. A Deployment manages that for you. If a Deployment owns a Pod, and you delete the Deployment, Kubernetes knows on its own to delete the matching Pod, so there's not really any more work.
(There's not really any reason to want a bare pod; you almost always want one of the higher-level controllers. The one exception I can think of is kubectl run a debugging shell inside the cluster.)
The Pod name being generated can be a minor hassle. One trick that's useful here: as of reasonably recent kubectl, you can give the deployment name to commands like kubectl logs
kubectl logs deployment/nginx-test
There are also various "dashboard" type tools out there that will let you browse your current set of pods, so you can do things like read logs without having to copy-and-paste the full pod name. You may also be able to set up tab completion for kubectl, and type
kubectl logs nginx-test<TAB>
One of the points in the kubectl best practices section in Kubernetes Docs state below:
Pin to a specific generator version, such as kubectl run
--generator=deployment/v1beta1
But then a little down in the doc, we get to learn that except for Pod, the use of --generator option is deprecated and that it would be removed in future versions.
Why is this being done? Doesn't generator make life easier in creating a template file for resource definition of deployment, service, and other resources? What alternative is the kubernetes team suggesting? This isn't there in the docs :(
kubectl create is the recommended alternative if you want to use more than just a pod (like deployment).
https://kubernetes.io/docs/reference/kubectl/conventions/#generators says:
Note: kubectl run --generator except for run-pod/v1 is deprecated in v1.12.
This pull request has the reason why generators (except run-pod/v1) were deprecated:
The direction is that we want to move away from kubectl run because it's over bloated and complicated for both users and developers. We want to mimic docker run with kubectl run so that it only creates a pod, and if you're interested in other resources kubectl create is the intended replacement.
For deployment you can try
kubectl create deployment hello-node --image=gcr.io/hello-minikube-zero-install/hello-node
and
Note: kubectl run --generator except for run-pod/v1 is deprecated in v1.12.