mariadb-operator VS charts

Once you have learnt the basics I would recommend you to contribute to an open source operator like mariadb-operator: https://github.com/mariadb-operator/mariadb-operator

In this blog, we discuss the effective utilization of mariadb-operator to manage MariaDB instances in Kubernetes using CRDS, promoting a declarative approach instead of relying on imperative commands.

v0.0.16 release: https://github.com/mariadb-operator/mariadb-operator/releases/tag/v0.0.16

Refer to the documentation for further detail: https://github.com/mariadb-operator/mariadb-operator/blob/main/docs/GALERA.md

I think I've managed to reproduce your issue using podman rootless KIND, but it does not have to do with Podman at all. It was some RBAC misconfiguration in the last version of the Helm chart that caused the controller to be unable to watch some resources on the Kubernetes API. I've released a v0.0.3 to fix this.

I'm quite happy to announce that, after months of work, I'm releasing today the second alpha version of mariadb-operator, a Kubernetes operator written in Go that enables you to run and operate MariaDB in a cloud native way. Forget about imperative commands, do everything declaratively using CRDs.

I've created an issue for this: https://github.com/mmontes11/mariadb-operator/issues/10

Both of these examples seem pretty obvious and something you wouldn’t mess up, but as your chart grows, so does your values.yaml file. A great example is the Redis chart by Bitnami. I encourage you to scroll through its values file. See you in a minute!

We will write a Terraform module that will take a list of configurations for each required RabbitMQ instance. Luckily for us, we don't have to write the Kubernetes yaml configurations since the helm charts by Bitnami does a great job of doing all the things we discussed above. All we need to do is leverage Terraform Helm Provider and deploy the chart with the required values for our use case.

💡  The full details of helm charts can be referenced in their associated GitHub Repository.

I have a configmap with the ndjson set up under data:, similar to https://github.com/bitnami/charts/issues/6159 and it's subsequent answer.

This way, you can easily deploy any Helm charts from this public repo - https://github.com/bitnami/charts/tree/main/bitnami in just minutes.

The Bitnami Github Pages themselves usually cover everything you need to know. Configure a values.yaml file, or modify that to your liking, and you run helm install, as written in their docs.

The actual reason that our pods are not coming up is found when we review the helm installation that we are trying to run. If you check the dependencies in the GitHub repository (https://github.com/bitnami/charts/blob/main/bitnami/drupal/values.yaml) you find out that persistent storage is enabled by default and set to 8Gi. Also, the helm package uses MariaDB and the database size is specified to a default of 8Gi, thus setting the minimum storage for this installation to be 16Gi.

We're using https://github.com/bitnami/charts/tree/main/bitnami/spark, but I have heard good things about https://github.com/GoogleCloudPlatform/spark-on-k8s-operator as well. Hudi should not need any long running deployments as per the docs https://hudi.apache.org/docs/0.5.1/deployment/#deploying

Bitnami has its own scaffolding published at https://github.com/bitnami/charts/tree/main/template