helm-promotion-sample-app
traefik-helm-chart
helm-promotion-sample-app | traefik-helm-chart | |
---|---|---|
12 | 11 | |
40 | 971 | |
- | 2.0% | |
0.0 | 8.6 | |
almost 2 years ago | 4 days ago | |
Smarty | Smarty | |
- | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
helm-promotion-sample-app
- What is the best way to set your environment configuration?
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How do you handle env variables for pods?
Here is an example with Helm https://github.com/codefresh-contrib/helm-promotion-sample-app/tree/master/chart. Same idea for Kustomize
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Similar chart in different environments and overriding values
More context https://codefresh.io/docs/docs/ci-cd-guides/environment-deployments/
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Soup: GitOps operator for Kubernetes focused on simplicity
The question cannot be easily answered in a Reddit comment. You can see the suggested flow here. https://codefresh.io/docs/docs/ci-cd-guides/environment-deployments/ It is with Codefresh (the company I work for) but it would be similar with Github actions.
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Am I using Helm right?
Example: helm-promotion-sample-app/chart at master · codefresh-contrib/helm-promotion-sample-app · GitHub
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Using Helm to Deploy a Kubernetes Application to Multiple Environments (QA/Stage/Prod)
You can find an example application that follows this practice at: https://github.com/codefresh-contrib/helm-promotion-sample-app/tree/master/chart
traefik-helm-chart
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Unfork with ArgoCD
helm chart Traefik Ingress
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Kubernetes confuses the heck out of me
For an example, consider the NGINX Ingress Controller Helm Chart and the Traefik Ingress Controller Helm Chart. Both of these charts install an IngressController but they have their own set of features, configuration, and operation. While they do similar things, they are not the same. Rather than having to pull a bunch of yaml files from a github repo, you can execute a helm install after telling helm where the definition of the charts comes from for a given application. Helm will then go and fetch all the manifests contained in the chart and populate values into the manifest from its defined defaults merged with any values that you specify as an override (or option). If another version of the application comes out, rather than having to update everything, you can just run helm upgrade to update the release to a newer chart version (which may update the internal application code). If the chart version didn't change, but you need a newer release version, a lot of times this is handled by a version variable that you can specify. You just update that (either on the command line or in a values file) and run helm upgrade to change the manifests that get pushed and automatically your deployments will get updated.
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Collecting Traefik metrics?
Traefik was deployed using Traefik's chart (https://github.com/traefik/traefik-helm-chart). Reading the default values.yaml file, I understand that the Prometheus metrics endpoint is enabled by default. I can confirm that I see the metrics when I access the pod on port 9100/metrics/.
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Newbie question: Deploying Traefik
You can Just use the Traefik V2 Helm Chart https://github.com/traefik/traefik-helm-chart
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Why did my K8S Traefik proxy stop working?
You can find the CRDs in Traefik's helm chart repo
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Every Sufficiently Advanced Configuration Language Is Wrong
A thousand times, yes. I've wanted to write this same article. Thanks for saving me the time!
The industry is going to great lengths to avoid writing configuration in any ubiquitous imperative programming language. We're seeing the proliferation of hyper-specialized, clunky declarative languages with sub-par tooling and package ecosystems. In what world are templates acceptable code? I don't mean to pick on anything specific, but this[0] is the most recent example I've come across, and it's far from the most unreadable examples.
[0]: https://github.com/traefik/traefik-helm-chart/blob/master/tr...
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Traefik + Wordpress, Apache showing pod IP instead of domain name
I have Traefik 2 as my ingress controller acting as the reverse proxy, deployed via Helm. I am using the Bitnami Helm chart to deploy wordpress.
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Traefik Middleware (redirectScheme) in k3s
You can then use helm to remove the old traefik deployment and install from wherever you'd prefer. I used the official traefik helm. I made sure that I copied the values from /var/lib/rancher/k3s/server/manifests/traefik.yaml to my values file (retrieved from https://github.com/traefik/traefik-helm-chart/blob/master/traefik/values.yaml). Here I also added the helm operator ports.web.redirectTo: websecure (per u/soundwave_rk).
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Helm, just because?
Traefik Helm chart has 402 stars, but the problem here is that 100 people can use it and they don't add stars since they don't log in to GitHub for it. I don't star Debian packages either.
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MetalLB and Traefik for a home Kubernetes Cluster
I installed Traefik by helm. You'll need to install helm on the machine you're running kubectl on, then you can follow their instructions at https://github.com/traefik/traefik-helm-chart to install.
What are some alternatives?
charts - HAProxy Ingress helm charts
k3s - Lightweight Kubernetes
Universal-Kubernetes-Helm-Charts - Some universal helm charts used for deploying services onto Kubernetes. All-in-one best-practices
charts - Bitnami Helm Charts
argo-cd - Declarative Continuous Deployment for Kubernetes
charts - TrueNAS SCALE Apps Catalogs & Charts
unlimited-test-environments-manifests - Unlimited test environments with Kubernetes (manifests)
stolon-chart - Kubernetes Helm chart to deploy HA Postgresql cluster based on Stolon
soup - GitOps continuous deployment and management tool for Kubernetes focused on simplicity.
charts - The User-Community Airflow Helm Chart is the standard way to deploy Apache Airflow on Kubernetes with Helm. Originally created in 2017, it has since helped thousands of companies create production-ready deployments of Airflow on Kubernetes.
pyinfra - pyinfra turns Python code into shell commands and runs them on your servers. Execute ad-hoc commands and write declarative operations. Target SSH servers, local machine and Docker containers. Fast and scales from one server to thousands.