nifikop
DISCONTINUED
db-operator
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| nifikop | db-operator | |
|---|---|---|
| 1 | 3 | |
| 118 | 112 | |
| - | 6.3% | |
| 7.7 | 6.2 | |
| about 1 year ago | 7 days ago | |
| Go | Go | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
nifikop
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Nifi on EKS CLUSTER
I don't have experience of Nifi, but I'd say your best option is either the operator: https://github.com/Orange-OpenSource/nifikop or the helm chart: https://github.com/cetic/helm-nifi
db-operator
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Database for homelab - in or out of cluster?
For homelab, I'm using in-cluster databases. And I'm doing full volumes backups instead of database dumps. I have funkwhale and gitea that both require postgres. And I'm using postgres that is provided as chart dependency. But my plan is to setup one postgres database in the separate ns, and then use https://github.com/kloeckner-i/db-operator for managing it.
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MySQL operators without the cluster
Look at https://github.com/kloeckner-i/db-operator , byt external secret is missing
- Operators for out-of-cluster databases
What are some alternatives?
helmify - Creates Helm chart from Kubernetes yaml
argocd-operator - A Kubernetes operator for managing Argo CD clusters.
helm-nifi - Helm Chart for Apache Nifi
cluster-example - Terraform cluster example with Druid, Kafka and NiFi
mysql-operator - Kubernetes operator to manage mysql databases and users
postgres-operator - Production PostgreSQL for Kubernetes, from high availability Postgres clusters to full-scale database-as-a-service.
keepalived-operator - An operator to manage VIPs backed by keepalived
egressip-ipam-operator - egressip-ipam-operator
varnish-operator - Run and manage Varnish clusters on Kubernetes
kubernetes-operator-roiergasias - 'Roiergasias' kubernetes operator is meant to address a fundamental requirement of any data science / machine learning project running their pipelines on Kubernetes - which is to quickly provision a declarative data pipeline (on demand) for their various project needs using simple kubectl commands. Basically, implementing the concept of No Ops. The fundamental principle is to utilise best of docker, kubernetes and programming language features to run a workflow with minimal workflow definition syntax. It is a Go based workflow running on command line or Kubernetes with the help of a custom operator for a quick and automated data pipeline for your machine learning projects (a flavor of MLOps).
rbacsync - Automatically sync groups into Kubernetes RBAC
chart-operator - The chart-operator deploys Helm charts.