charts VS Orkestra

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

Github Repo - Azure/orkestra: Orkestra is a cloud-native release orchestration and lifecycle management (LCM) platform for the fine-grained orchestration of inter-dependent helm charts and their dependencies (github.com)

Orchestration of a group of complex applications with dependencies between themselves and their subcharts/dependencies is hard

Imagine a scenario in which application that depends on Prometheus, Grafana and Istio. Now let's take it a step further and define a dependency between Istio and it's observability components, Prometheus & Grafana, since Istio itself leverages both Prometheus and Grafana for it's control-plane. In other words we now have a dependency DAG where, the application depends-on Istio depends-on Prometheus & Grafana. Now imagine the application depending on other applications that provide PaaS like infrastructure capabilities required to run the application itself

Defining this dependency order allows all components to spin up both, reliably and efficiently

This would make a huge difference when we are dealing with complex applications like 5G network functions running mission-critical workloads across the network and their lifecycle management (installs/upgrades/rollback). Providers, tend to take releases in a "semi-continuous" manner as opposed to true CD. Meaning, when upgrading, multiple applications and their subcharts may be upgraded in a single release. This is a scenario in which defining the dependency ordering between the applications and their subcharts allows the service providers to limit the blast radius if this go wrong, allowing them to fail fast and rollback without impacting all upgrade-ready apps

Introducing Azure Orkestra https://github.com/Azure/Orkestra that provides the aforementioned capabilities using a familiar Kubernetes declarative CRDscalled ApplicationGroups. Orkestra leverages Argo Workflows to generate DAG workflows to deploy all applications with an application group (and optionally a DAG workflow for the subcharts in each application). The DAG on execution generates HelmRelease objects that are then acted upon by flux helm-operator to reliably perform the helm actions (install, delete, upgrade, rollback)

Introducing Azure Orkestra https://github.com/Azure/Orkestra that provides the aforementioned capabilities and features using familiar Kubernetes declarative objects (CRDs) called ApplicationGroups.