[{"_1":2,"_152":-5,"_153":-5},"loaderData",{"_3":4,"_13":14,"_20":21,"_131":132},"root",{"_5":-5,"_6":-7,"_7":8,"_9":-7,"_10":11,"_12":-7},"currentUser","primaryEmail","siteVerification","6LeIxAcTAAAAAJcZVRqyHh71UMIEGNQ_MXjiZKhI","toast","enableDev",false,"incidentStatus","routes/_layout",{"_15":-5,"_16":17,"_18":17,"_19":11},"username","isAskGordonEnabled",true,"isUsingNewTemplate","showMinimalLanding","routes/_layout.r.$namespace.$reponame",{"_22":23,"_24":-5,"_25":11,"_26":11,"_27":28,"_29":30,"_31":-5,"_32":11,"_33":34,"_83":-5,"_84":85,"_124":-5,"_125":11,"_126":17,"_127":11,"_128":-5,"_129":130},"canonicalUrl","https://hub.docker.com/r/guysoft/kube-s3/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","guysoft","reponame","kube-s3","cloudBuildSource","isAutobuildsAvailable","repo",{"_35":36,"_37":38,"_40":41,"_42":43,"_44":11,"_45":46,"_47":48,"_49":50,"_52":30,"_27":28,"_53":54,"_55":39,"_56":57,"_58":59,"_60":61,"_62":-5,"_63":57,"_64":65,"_66":11,"_67":28,"_68":69,"_74":11,"_75":76,"_80":28,"_81":82},"categories",[],"content_types",[39],"image","date_registered","2020-04-12T18:20:42.860894Z","description","Taken from https://github.com/guysoft/kube-s3.git lets you mount s3 containers","is_private","last_updated","2020-06-15T13:50:32.714521Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[51],"application/vnd.docker.container.image.v1+json","name","pull_count",27501,"repository_type","star_count",0,"status",1,"status_description","active","source","collaborator_count","full_description","## Shared storage with S3 backend\nThe storage is definitely the most complex and important part of an application setup, once this part is \ncompleted, 80% of the tasks are completed.\n\nMounting an S3 bucket into a pod using FUSE allows you to access the data as if it were on the local disk. The \nmount is a pointer to an S3 location, so the data is never synced locally. Once mounted, any pod can read or even write\nfrom that directory without the need for explicit keys.\n\n\nHowever, it can be used to import and parse large amounts of data into a database.\n\n## Overview\n\n![s3-mount](/images/s3-mount.png)\n\n\n## Limitations\nGenerally S3 cannot offer the same performance or semantics as a local file system. More specifically:\n\n - random writes or appends to files require rewriting the entire file\n - metadata operations such as listing directories have poor performance due to network latency\n - eventual consistency can temporarily yield stale data(Amazon S3 Data Consistency Model)\n - no atomic renames of files or directories\n - no coordination between multiple clients mounting the same bucket\n - no hard links\n\n## Before you Begin\nYou need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with \nyour cluster. If you do not already have a cluster, you can create one by using the [Gardener](https://gardener.kubernetes.sap.corp/login).\n\nEnsure that you have create the \"imagePullSecret\" in your cluster.\n```sh \nkubectl create secret docker-registry artifactory --docker-server=.docker.repositories.sap.ondemand.com --docker-username= --docker-password= --docker-email= -n \n```\n\n## Setup\nThe first step is to clone this repository. Next is the Secret for the AWS API credentials of the user that has \nfull access to our S3 bucket. Copy the `configmap_secrets_template.yaml` to `configmap_secrets.yaml` and place \nyour secrets at the right place\n\n```yaml\napiVersion: v1\nkind: ConfigMap\nmetadata:\n name: s3-config\ndata:\n S3_BUCKET: \n AWS_KEY: \n AWS_SECRET_KEY: \n```\n\n## Build and deploy\nChange the settings in the `build.sh` file with your docker registry settings. \n\n```sh\n#!/usr/bin/env bash\n\n########################################################################################################################\n# PREREQUISTITS\n########################################################################################################################\n#\n# - ensure that you have a valid Artifactory or other Docker registry account\n# - Create your image pull secret in your namespace\n# kubectl create secret docker-registry artifactory --docker-server=.docker.repositories.sap.ondemand.com --docker-username= --docker-password= --docker-email= -n \n# - change the settings below arcording your settings\n#\n# usage:\n# Call this script with the version to build and push to the registry. After build/push the\n# yaml/* files are deployed into your cluster\n#\n# ./build.sh 1.0\n#\nVERSION=$1\nPROJECT=kube-s3\nREPOSITORY=cp-enablement.docker.repositories.sap.ondemand.com\n\n\n# causes the shell to exit if any subcommand or pipeline returns a non-zero status.\nset -e\n# set debug mode\n#set -x\n\n.\n.\n.\n.\n\n```\nCreate the S3Fuse Pod and check the status:\n\n```sh\n# build and push the image to your docker registry\n./build.sh 1.0 \n\n# check that the pods are up and running\nkubectl get pods\n\n```\n\n## Check success\nCreate a demo Pod and check the status:\n```sh \nkubectl apply -f ./yaml/example_pod.yaml\n\n# wait some second to get the pod up and running...\nkubectl get pods\n\n# go into the pd and check that the /var/s3 is mounted with your S3 bucket content inside\nkubectl exec -ti test-pd sh\n\n# inside the pod\nls -la /var/s3\n\n```\n\n## Why does this work?\nDocker engine 1.10 added a new feature which allows containers to share the host mount namespace. This feature makes \nit possible to mount a s3fs container file system to a host file system through a shared mount, providing a persistent\nnetwork storage with S3 backend.\n\nThe key part is mountPath: `/var/s3:shared` which enables the volume to be mounted as shared inside the pod. When the \ncontainer starts it will mount the S3 bucket onto `/var/s3` and consequently the data will be available under \n`/mnt/data-s3fs` on the host and thus to any other container/pod running on it (and has `/mnt/data-s3fs` mounted too). 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guysoft/kube-s3

Tags for guysoft/kube-s3