I want keep version of all pods (App) in env inside namespace. so i can use them in yaml file to create deployment. or even in ci/cd makes devops easier.
right now developer must set the version in yaml file.
If you want to use the environment variables in menifest file or in yaml file you can simply use the kubernetes secrets & config maps.
where can store the environment and use them during the deployment.
That's about the design principle, and that's the ideal approach to apply for your pipeline.
You don't have to save the exact version of all your Pods inside the manifest file, just use the latest or environment-like tag (e.g staging or production)
And in your pipeline, you could patch the deployment with the corresponding tag based on your build.
One example of this approach:
kubectl patch deployment $YOUR_DEPLOYMENT_NAME -p "{\"metadata\":{\"labels\":{\"image\":\"$YOUR_BUILD_STAGE-$PIPELINE_ID\"}},\"spec\":{\"revisionHistoryLimit\":2,\"template\":{\"spec\":{\"containers\":[{\"name\":\"$YOUR_CONTAINER_NAME\",\"image\":\"$DOCKER_IMAGE_NAME:$YOUR_BUILD_STAGE-$PIPELINE_ID\"}]}}}}"
Related
I want to redeploy an application in k8s using GitOps(ArgoCD) in case of an only config Map change, how ArgoCD will understand to restart the container as we all know without restarting the container new config map is not going to take effect.
Scenario - If one container is running from ArgoCD and I have to modify configmap yaml file in GitHub and ArgoCD will automatically understand and sync the updated values but container will not restart as we are not modifying in Deployment Yaml Files, so how config map will take effect in the container
Found a workaround for the above question, We can include a parameter(Jenkins Build Number) as env variable in the Deployment config and it will be updated on every build from CI Pipeline, so in case of only config Change in Git repo, deployment will also be rolled out because Build number Parameter will change after running the Pipelines and as we all know ArgoCD will automatically be triggered once any change is done in Git repo connected to ArgoCD
ArgoCD itself doesn't handle this, however other tools can. With Helm this is generally handled inside the chart by hashing the config content into an annotation in the pod template. Kustomize offers the configmap and secret generators which put a hash in the object name and rewrite the pod template to include it. There's also operator solutions like Reloader which does a similar trick to Helm but via an operator.
I am setting up kubernetes for an application with 8 microservices,activemq,postgres,redis and mongodb.
After the entire configuration of pods and deployment ,is there any way to create a single master deployment yaml file which will create the entire set of services,replcas etc for the entire application.
Note:I will be using multiple deployment yaml files,statefulsets etc for all above mentioned services.
You can use this script:
NAMESPACE="your_namespace"
RESOURCES="configmap secret daemonset deployment service hpa"
for resource in ${RESOURCES};do
rsrcs=$(kubectl -n ${NAMESPACE} get -o json ${resource}|jq '.items[].metadata.name'|sed "s/\"//g")
for r in ${rsrcs};do
dir="${NAMESPACE}/${resource}"
mkdir -p "${dir}"
kubectl -n ${NAMESPACE} get -o yaml ${resource} ${r} > "${dir}/${r}.yaml"
done
done
Remember to specify what resources you want exported in the script.
More info here
Is there any way to create a single master deployment yaml file which will create the entire set of services,replicas etc for the entire application.
Since you already mentioned kubernetes-helm why don't you actually used it for that exact purpose? In short helm is sort of package manager for Kubernetes, some say similar to yum or apt. It deploys charts which you can actually refer to as packed application. Its pack of all your pre-configured applications which can be deploy as one unit. It's not entirely one file but more collection of files that build so called helm chart.
What are the helm charts?
Well they are basically K8s yaml manifest combined into a single package that can be installed to your cluster. And installing the package is just as simple as running single command such as helm install. Once done the charts are highly reusable which reduces the time for creating dev, test and prod environments.
As an example of a complex helm chart deploying multiple resources you many want to check Stackstorm.
Basically once deployed without any custom config this chart will deploy 2 replicas for each component of StackStorm as well as backends like RabbitMQ, MongoDB and Redis.
Can anyone tell me the deployment flow for deploying the application over Kubernetes or EKS cluster using Jenkins. How is the deployment files updated based on the change of the docker image. If we have multiple deployment files and we change any image for any one of them. Do all of them are redeployed?
Can anyone tell me the deployment flow for deploying the application over Kubernetes or EKS cluster using Jenkins.
Make sure that your Jenkins instance has an IAM Role and updated kubeconfig so that it can access the Kubernetes cluster. If you consider running the pipeline on the Kubernetes cluster, Jenkins X or Tekton Pipelines may be good alternatives that are better designed for Kubernetes.
How is the deployment files updated based on the change of the docker image.
It is a good practice to also keep the deployment manifest in version control, e.g. Git. This can be in the same repository or in a separate repository. For updating the image after a new image is built, consider using yq. An example yq command to update the image in a deployment manifest (one line):
yq write --inplace deployment.yaml 'spec.template.spec.containers(name==<myapp>).image' \
<my-registy-host>/<my-image-repository>/<my-image-name>:<my-tag-name>
If we have multiple deployment files and we change any image for any one of them. Do all of them are redeployed?
Nope, Kubernetes Yaml is declarative so it "understand" what is changed and only "drives" the necessary deployments to its "desired state" - since the other deployments already are in its "desired state".
i'm working on a continuous deployment routine for a kubernetes application: everytime i push a git tag, a github action is activated which calls kubectl apply -f kubernetes to apply a bunch of yaml kubernetes definitions
let's say i add yaml for a new service, and deploy it -- kubectl will add it
but then later on, i simply delete the yaml for that service, and redeploy -- kubectl will NOT delete it
is there any way that kubectl can recognize that the service yaml is missing, and respond by deleting the service automatically during continuous deployment? in my local test, the service remains floating around
does the developer have to know to connect kubectl to the production cluster and delete the service manually, in addition to deleting the yaml definition?
is there a mechanism for kubernetes to "know what's missing"?
You need to use a CI/CD tool for Kubernetes to achieve what you need. As mentioned by Sithroo Helm is a very good option.
Helm lets you fetch, deploy and manage the lifecycle of applications,
both 3rd party products and your own.
No more maintaining random groups of YAML files (or very long ones)
describing pods, replica sets, services, RBAC settings, etc. With
helm, there is a structure and a convention for a software package
that defines a layer of YAML templates and another layer that
changes the templates called values. Values are injected into
templates, thus allowing a separation of configuration, and defines
where changes are allowed. This whole package is called a Helm
Chart.
Essentially you create structured application packages that contain
everything they need to run on a Kubernetes cluster; including
dependencies the application requires. Source
Before you start, I recommend you these articles explaining it's quirks and features.
The missing CI/CD Kubernetes component: Helm package manager
Continuous Integration & Delivery (CI/CD) for Kubernetes Using CircleCI & Helm
There's no such way. You can deploy resources from yaml file from anywhere if you can reach the node and configure kube config. So kubernetes will not know how to respond on a file deletion. If you still want to do this, you can write a program (a go code) which checks the availability of files in one place and deletes the corresponding resource whenever the file gets deleted.
There's one way via kubernetes is by using kubernetes operator, and whenever there is any change in your files you can update the crd used to deploy resources via operator.
Before deleting the yaml file, you can run kubectl delete -f file.yaml, this way all the resources created by this file will be deleted.
However, what you are looking for, is achieving the desired state using k8s. You can do this by using tools like Helmfile.
Helmfile, allow you to specify the resources you want to have all in one file, and it will achieve the desired state every time you run helmfile apply
In My CICD, I am:
generating a new image with a unique tag. foo:dev-1339 and pushing it to my image repo (ECR).
Then I am using a rolling update to update my deployment.
kubectl rolling-update frontend --image=foo:dev-1339
But I have a conflict here.
What if I also need to update some part of my deployment object as stored in a deployment.yaml file. Lets say harden a health check or add a parameter?
Then when I re apply my deployment object as a whole it will not be in sync with the current replica set, the tag will get reverted and I will lose that image update as it exists in the cluster.
How do I avoid this race condition?
A typical solution here is to use a templating layer like Helm or Kustomize.
In Helm, you'd keep your Kubernetes YAML specifications in a directory structure called a chart, but with optional templating. You can specify things like
image: myname/myapp:{{ .Values.tag | default "latest" }}
and then deploy the chart with
helm install myapp --name myapp --set tag=20191211.01
Helm keeps track of these values (in Secret objects in the cluster) so they don't get tracked in source control. You could check in a YAML-format file with settings and use helm install -f to reference that file instead.
In Kustomize, your CI tool would need to create a kustomize.yaml file for per-deployment settings, but then could set
images:
- name: myname/myapp
newTag: 20191211.01
If you trust your CI tool to commit to source control then it can check this modified file in as part of its deployment sequence.
Imperative vs Declarative workflow
There is two fundamental ways of using kubectl for applying changes to your cluster. The Imperative way, when you do commands is a good way for experimentation and development environment. kubectl rolling-updated is an example of an imperative command. See Managing Kubernetes using Imperative Commands.
For a production environment, it is recommended to use a Declarative workflow, by editing manifest-files, store them in a Git-repository. Automatically start a CICD work when you commit or merge. kubectl apply -f <file> or more interesting kubectl apply -k <file> is an example of this workflow. See Declarative Management using Config files or more interesting Declarative Management using Kustomize
CICD for building image and deployment
Building an artifact from source code, including a container image may be done in a CICD pipeline. Managing application config and applying it to the Kubernetes cluster may also be done in a CICD pipeline. You may want to automatize it all, e.g. for doing Continuous Deployment and combine both pipelines to a single long pipeline. This is a more complicated setup and there is no single answer on how to do it. When the build-parts is done, it may trigger an update of the image field in the app configuration repository to trigger the configuration-pipeline.
Unfortunately there is no solution, either from the command line or through the yaml files
As per the doc here, "...a Deployment is a higher-level controller that automates rolling updates of applications declaratively, and therefore is recommended" over the use of Replication Controllers and kubectl rolling-update. Updating the image of a Deployment will trigger Deployment's rollout.
An approach could be to update the Deployment configuration yaml (or json) under version control in the source repo and apply the changed Deployment configuration from the version control to the cluster.