postgres-operator VS charts

yes, precisely. It's UI part that's broken, which cannot list snapshots. Issue is here, no fix since 2020, sadly: https://github.com/zalando/postgres-operator/issues/937

I personally like the Zalando operator better, you can add databases and users by updating the CRD, feature parity between the two on HA is pretty good

https://github.com/zalando/postgres-operator

one of the solutions which made it pretty simple for us to run postgresql in a ha environment (mostly in k8s, but works standalone as well) is zalandos patroni: https://github.com/zalando/patroni it's really solid and worked for us for a few years already.

or for k8s their operator: https://github.com/zalando/postgres-operator (docker image: https://github.com/zalando/spilo) we've also tried other operators which were easier to get started, but they failed miserably (crunchyrolls operator is basically based on the zalando one)

git clone https://github.com/zalando/postgres-operator.git cd postgres-operator

Zalando / Postgres-Operator

Somewhere between here and here i found out about that.

Here's an example of using the PostgreSQL Operator to deploy a high availability PostgreSQL cluster in Kubernetes. In this example, I'll be using the PostgreSQL Operator from Zalando [https://github.com/zalando/postgres-operator] to deploy a PostgreSQL cluster with two nodes.

Here's the operator for a postgres cluster: https://github.com/zalando/postgres-operator

And that repo you linked to has 1846 issues, 161 open. Which doesn't seem extraordinary based on my limited exposure to k8s.

Another example: https://github.com/zalando/postgres-operator/issues with 445 open issues. Why?

Maybe I'm wrong and this is all a good sign of progress, but my impression is that the entire k8s ecosystem is held together with reused duct tape.

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