We have containerized our .Net Core Web API using Docker and deploying to OpenShift
Below is the process we are following
Docker Image created
Image pushed to jfrog Artifactory from Azure Devops Build Pipeline
We have around 40 OpenShift Clusters where we have to deploy our App
Created Generic YAML template(references docker image with Tag_Name as Variable).
Created the template using OC commandline in all sites.
Now using Azure Devops Release pipeline we have created around 40 stages.
Each stage contains below tasks to trigger the templates
oc project $(project_name)
oc process template_name TAG_NAME="new_tag" | oc apply -f -
Problem:
If I need to deploy a new version of Docker Image(tag), running all the stages
takes lot of time. Is there any better way to run these stages parallel ?
With IIS deployments we can make use of deployment groups, but here in this case is there
a better way of doing it ?
I know that there is a way that if an image is pushed to artifactory all the clusters can
automatically pull that image, but I do not want in this way, I need more control over to
which set of clusters I am deploying.
Related
I am relatively new to AWS and kubernetes. I have created a self-managed kubernetes cluster running in AWS (not using EKS). I have successfully created a pipeline in AWS CodePipeline that builds my container and uploads it to ECR. Currently I am manually deploying the created image in the cluster by running the following commands:
kubectl delete deployment my-service
kubectl apply -f my-service_deployment.yaml
How can I automate this manual step in AWS CodePipeline? How can I run the above commands as part of the pipeline?
Regarding my deployment yaml files, where should I store these files? (currently I store them locally in the master node.)
I am missing some best practices for this process.
Your yaml manifests should'nt be on your master node (never), they should be stored in a Version Control System (just like github/gitlab/bitbucket etc.).
To automate the deployment of your docker image based on new artifact version in ECR, you can use a great tools named FluxCD, it is actually very simple to install (https://fluxcd.io/docs/get-started/) and you can easily configure it to automatically deploy your images in your cluster each time there is a new image on your ECR registry.
This way your codePipeline will build the code, do the tests, build the image, tag it and push it to ECR and FluxCD will deploy it to kubernetes. (it is also natively configurable to deploy on each X minutes (based on your configuration) on your cluster, so even if you bring a little change into your manifests, it will be automatically deployed !
bguess
you can also make use of argo cd its very easy to install and use compared to aws codepipeline.
argo cd was specifically designed for Kubernetes thus offers much better way to deploy to K8s
I am new here, I tried to search for the topic before I post here, this may have been discussed before, please let me know before being to hash on me :)
In my project, after performing some changes on either the DevOps tool sets or infrastructures, we always do some manual sanity test, this normally includes:
Building a new image and update the helm chart
Push the image to Artifactory and perform a "helm update", and see it it runs.
I want to automate the whole thing, and try to get advice from the community, here's some requirement:
Validate Jenkins agent being able to talk to cluster ( I can do this with kubectl get all -n <some_namespace_jenkins_user_has_access_to)
Validate the cluster has access to Github (let's say I am using Argo CD to sync yamls)
Validate the cluster has access to Artifactory and able to pull image ( I don't want to build a new image with new tag and update helm chart, so that to force to cluster to pull new image)
All of the above can be done in command line (so that I can implement using Jenkins groovy)
Any suggestion is welcome.
Thanks guys
Your best bet is probably a combination of custom Jenkins scripts (i.e. running kubectl in Jenkins) and some in-cluster checks (e.g. using kuberhealthy).
So, when your Jenkins pipeline is triggered, it could do the following:
Check connectivity to the cluster
Build and push an image, etc.
Trigger in-cluster checks for testing if the cluster has access to GitHub and Artifactory, e.g. by launching a custom Job in the cluster, or creating a KuberhealthyCheck custom resource if you use kuberhealthy
During all this, the Jenkins pipeline writes the results of its test as metrics to a Pushgateway which is scraped by your Prometheus. The in-cluster checks also push their results as metrics to the Pushgateway, or expose them via kuberhealthy, if you decide to use it. In the end, you should have the results of all checks in the same Prometheus instance where you can react on them, e.g. creating Prometheus alerts or Grafana dashboards.
I tried to start #kubernetes cluster and then run tests and publish results. Do you have any idea on how this can be done?
I created a pipeline but I do not know which yml to use
Which task to add first - kubernetes deploy or something else
We have Kubernetes deployment.yml file>>It takes the container( image )(exampleacr.io/sampleapp) that we going to publish on AKS
App version: app/v1
Service.yml is to just expose the application App version: v1
Both the yml files are to be added .Please refer WAY2 for modifying manually.
WAY 1:
Quick way: Deploy to Azure Kubernetes service will do everything that’s needed because if you use the Deploy to Azure Kubernetes Services template, these variables get defined for you.
Steps:
Create AKS cluster and ACR(container registry) in azure.
In azure Devops:
Create a pipeline>choose any source:for select an application
hosted in git hub
Then select Deploy to Azure Kubernetes service >select your aks
subscription> select the existing cluster>then select the container
registry that you want to put docker image into.keep the remaining
as default
Click on validate and configure
azure pipeline will generate a YAML file.
In the review pipeline YAML of azure-pipelines.yml
You have two stages:Build,deploy
Click save and run:This saves yaml file in master branch and it creates manifests files(deployment.yml and service.yml) for kubernetes deployment.
Click save and run>this will also trigger build.
Reference
WAY2: Using Docker image
To do modifications in the azurepipelines.yml file In the 3rd step from above ,Select Docker image instead of Deploy to Azure Kubernetes service.
Under configure pipeline>If it is in Build.SourcesDirectory in our
application , it will appear as say $
Build.SourcesDirectory/app/Dockerfile
That builds the docker file /pipeline.
In the review pipeline YAML of azure-pipelines.yml
Few things can be modified like
You can change variable tag to repo name: and then deployment and
service.yml file can be added to the yml file by doing few
modifications
Build stage is automatic and no need to modify there.
You have to Add push and deploy stages in yml file as shown in the article
And get source code here
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".
We use Azure Devops process to do a deploy to our staging slot and then we do a straight swap between staging and production.
We note that through the portal interface we can direct a percent of the traffic to staging, is there a method to do this through Azure Devops/CD process so that we direct a percent of traffic to a specific slot and then gradually increase, essentially a canary deployment method via the pipeline using Azure Web App Slots?
Thank you in advance.
Looking at the documentation it looks that is possible:
Next to the Azure portal, you can also use the az webapp traffic-routing set command in the Azure CLI to set the routing
percentages from CI/CD tools like DevOps pipelines or other automation
systems.
you can use this command to increase traffic:
az webapp traffic-routing set --distribution staging=50 --name MyWebApp --resource-group MyResourceGroup
and with Start-Sleep -Seconds 10 you can gradually increase percentage.