csi-s3
s3sync
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| csi-s3 | s3sync | |
|---|---|---|
| 3 | 1 | |
| 739 | 66 | |
| - | - | |
| 0.0 | 7.5 | |
| 7 months ago | 4 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.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
csi-s3
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Learning K3s at Home, troubles with S3 Storage
This is the repo I am trying to use to setup s3 storage for config files of services.
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Question: does anyone know Storage Provider with S3 as persistence layer?
Could just use an S3 as the storage and handle backups with other tools against the bucket. https://github.com/ctrox/csi-s3
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How to scale nginx pod when pod is mounting a volume
You could also use the s3fs CSI for your storage. There may be some learning curve to getting it working. My only word of advise is to use the examples in the repo, the README.md is stale. I made some notes here.
s3sync
What are some alternatives?
nfs-subdir-external-provisioner - Dynamic sub-dir volume provisioner on a remote NFS server.
juicefs - JuiceFS is a distributed POSIX file system built on top of Redis and S3.
nfs-ganesha-server-and-external-provisioner - NFS Ganesha Server and Volume Provisioner.
rclone - "rsync for cloud storage" - Google Drive, S3, Dropbox, Backblaze B2, One Drive, Swift, Hubic, Wasabi, Google Cloud Storage, Yandex Files
csi-gcs - Kubernetes CSI driver for Google Cloud Storage
thanos - Highly available Prometheus setup with long term storage capabilities. A CNCF Incubating project.
topolvm - Capacity-aware CSI plugin for Kubernetes
Gitkube - Build and deploy docker images to Kubernetes using git push
k9s - 🐶 Kubernetes CLI To Manage Your Clusters In Style!
ceph-csi - CSI driver for Ceph
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).
OpenFaaS - OpenFaaS - Serverless Functions Made Simple