charts VS spark-operator

I'm using this prometheus helm chart.

I did this using the incubator/raw chart ( https://github.com/helm/charts/tree/master/incubator/raw ), by creating a k8s Job.

I've installed Prometheus operator 0.34 (which works as expected) on cluster A (main prom)Now I want to use the federation option,I mean collect metrics from other Prometheus which is located on other K8S cluster B

So I am using the helm chart stable/traefik to deploy a reverse proxy to my cluster. I need to customise it beyond what is possible with the variables I can set for the template.

It may be that we just migrated to Bitnami's chart when the old "stable" chart was deprecated

Edit: I'm using Postgresql Stable Chart version 5.3.10

I'm using the official stable/prometheus-operator chart do deploy Prometheus with helm.

I am using using https://github.com/helm/charts/tree/master/stable/airflow helm chart and building v1.10.8 puckle/docker-airflow image with kubernetes installed on it and using that image in the helm chart,But I keep getting

I have spent days now trying to figure out a dependency issue I'm experiencing with (Py)Spark running on Kubernetes. I'm using the spark-on-k8s-operator and Spark's Google Cloud connector.

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

The SparkOperator must be installed before we can use Spark on Kubernetes. Google created this operator, which is available on Github. In a nutshell, the operator is in charge of monitoring the cluster for specific events related to the spark job, as known as kind: SparkApplication

Spark-Operator (as I understand, Spark-Operator integrates well with K8s while vanilla Spark integration with K8s seems extremely complex to maintain)

Spark on K8s Operator is a project from Google that allows submitting spark applications on Kubernetes cluster using CustomResource Definition SparkApplication. It uses mutating admission webhook to modify the pod spec and add the features not officially supported by spark-submit.

In this section, you use Helm to deploy the Kubernetes Operator for Apache Spark from the incubator Chart repository. Helm is a package manager you can use to configure and deploy Kubernetes apps.

Additional details of how SparkApplications are run can be found in the design documentation.

GoogleCloudPlatform/spark-on-k8s-operator (Go): Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.