低級方案
再這樣下去我真的要變成 250 了，這怎么能忍，立馬打開 Google 研究了一把 Grafana 備份的各種騷操作，發(fā)現(xiàn)大部分備份方案都是通過 shell 腳本調(diào)用 Grafana 的 API 來導(dǎo)出各種配置。備份腳本大部分都集中在這個 gist 中：

https://gist.github.com/crisidev/bd52bdcc7f029be2f295
我挑選出幾個比較好用的，大家也可以自行挑選其他的。

導(dǎo)出腳本
#!/bin/bash

Usage:

export_grafana_dashboards.sh https://admin:REDACTED@grafana.dedevsecops.com

create_slug () {
echo "$1"|iconv?tascii//TRANSLIT|sed?rs/{[}^a?zA?Z0?9]+/?/g|sed?rs{/}^{?}+\Vert ?+$//g | tr A-Z a-z
}

full_url=$1username=$(echo "$ful{l}_{u}rl"|cut?d/?f3|cut?d:?f1)bas{e}_{u}rl=$(echo "$ful{l}_{u}rl"|cut?d@?f2)folder=$(create_slug “$username?${base_url}”)

mkdir “${folder}”
for db_uid in $(curl?s"${full_url}/api/search" | jq -r .[].uid); do
db_json=$(curl?s"${full_url}/api/dashboards/uid/$d{b}_{u}id")d{b}_{s}lug=$(echo "$d{b}_{j}son"|jq?r.meta.slug)d{b}_{t}itle=$(echo “$d{b}_{j}son"|jq?r.dashboard.title)filename="${folder}/KaTeX parse error: Can't use function '\"' in math mode at position 35: …cho "Exporting \?"?{db_title}” to “KaTeX parse error: Can't use function '\"' in math mode at position 11: {filename}\?"?..." echo "{db_json}” | jq -r . > “${filename}”
done
echo “Done”
這個腳本比較簡單，直接導(dǎo)出了所有 Dashboard 的 json 配置，也沒有標(biāo)記目錄信息，如果你用它導(dǎo)出的配置來恢復(fù) Grafana，所有的 Dashboard 都會導(dǎo)入到 Grafana 的 General 目錄下，不太友好。

導(dǎo)入腳本
grafana-dashboard-importer.sh

#!/bin/bash

add the “-x” option to the shebang line if you want a more verbose output

OPTSPEC=":hp:t:k:"

show_help() {
cat << EOF
Usage: $0 [-p PATH] [-t TARGET_HOST] [-k API_KEY]
Script to import dashboards into Grafana
-p Required. Root path containing JSON exports of the dashboards you want imported.
-t Required. The full URL of the target host
-k Required. The API key to use on the target host

-h Display this help and exit.

EOF
}

Check script invocation options

while getopts “$OPTSPEC"optchar;docase"$optchar” in
h)
show_help
exit
;;
p)
DASH_DIR=“$OPTARG";;t)HOST="$OPTARG”;;
k)
KEY=“KaTeX parse error: Undefined control sequence: \? at position 19: …ARG";; \???) ech…OPTARG” >&2
exit 1
;;
😃
echo “Option -$OPTARG requires an argument.” >&2
exit 1
;;
esac
done

if [ -z “$DAS{H}_{D}IR"]||[?z"$HOST” ] || [ -z “$KEY” ]; then
show_help
exit 1
fi

set some colors for status OK, FAIL and titles

SETCOLOR_SUCCESS=“echo -en \033[0;32m”
SETCOLOR_FAILURE=“echo -en \033[1;31m”
SETCOLOR_NORMAL=“echo -en \033[0;39m”
SETCOLOR_TITLE_PURPLE=“echo -en \033[0;35m” # purple

usage log “string to log” “color option”

function log_success() {
if [ $# -lt 1 ]; then
${SETCOLOR_FAILURE}
echo “Not enough arguments for log function! Expecting 1 argument got $#”
exit 1
fi

timestamp=$(date “+%Y-%m-%d %H:%M:%S %Z”)

${SETCOLOR_SUCCESS}
printf “[%s] KaTeX parse error: Undefined control sequence: \n at position 2: 1\?n?" "timestamp”
${SETCOLOR_NORMAL}
}

function log_failure() {
if [ $# -lt 1 ]; then
${SETCOLOR_FAILURE}
echo “Not enough arguments for log function! Expecting 1 argument got $#”
exit 1
fi

timestamp=$(date “+%Y-%m-%d %H:%M:%S %Z”)

${SETCOLOR_FAILURE}
printf “[%s] KaTeX parse error: Undefined control sequence: \n at position 2: 1\?n?" "timestamp”
${SETCOLOR_NORMAL}
}

function log_title() {
if [ $# -lt 1 ]; then
${SETCOLOR_FAILURE}
log_failure “Not enough arguments for log function! Expecting 1 argument got $#”
exit 1
fi

${SETCOLOR_TITLE_PURPLE}
printf “|-------------------------------------------------------------------------|\n”
printf “|%s|\n” “$1”;
printf “|-------------------------------------------------------------------------|\n”
${SETCOLOR_NORMAL}
}

if [ -d "$DAS{H}_{D}IR"];thenDAS{H}_{L}IST=$(find “KaTeX parse error: Undefined control sequence: \* at position 29: …ndepth 1 -name \?*?.json) if […DASH_LIST” ]; then
log_title “----------------- $DASH_DIR contains no JSON files! -----------------”
log_failure "Directory $DAS{H}_{D}IRdoesnotappeartocontainanyJSONfilesforimport.Checkyourpathandtryagain."exit1elseFILESTOTAL=$(echo “$DASH_LIST” | wc -l)
log_title “----------------- Starting import of $FILESTOTAL dashboards -----------------”
fi
else
log_title “----------------- $DASH_DIR directory not found! -----------------”
log_failure “Directory $DASH_DIR does not exist. Check your path and try again.”
exit 1
fi

NUMSUCCESS=0
NUMFAILURE=0
COUNTER=0

for DASH_FILE in $DAS{H}_{L}IST;doCOUNTER=$((COUNTER + 1))
echo “Import $COUNTER/$FILESTOTAL: $DAS{H}_{F}ILE..."RESULT=$(cat “$DASH_FILE” | jq ‘. * {overwrite: true, dashboard: {id: null}}’ | curl -s -X POST -H “Content-Type: application/json” -H “Authorization: Bearer $KEY""$HOST”/api/dashboards/db -d @-)
if [[ “$RESULT"==?"success"?]];thenlo{g}_{s}uccess"$RESULT”
NUMSUCCESS=$((NUMSUCCESS+1))elselo{g}_{f}ailure"$RESULT”
NUMFAILURE=$((NUMFAILURE + 1))
fi
done

log_title “Import complete. $NUMSUCCESS dashboards were successfully imported. $NUMFAILURE dashboard imports failed.”;
log_title “------------------------------ FINISHED ---------------------------------”;
導(dǎo)入腳本需要目標(biāo)機器上的 Grafana 已經(jīng)啟動，而且需要提供管理員 API Key。登錄 Grafana Web 界面，打開 API Keys：

新建一個 API Key，角色選擇 Admin，過期時間自己調(diào)整：

導(dǎo)入方式：

$ ./grafana-dashboard-importer.sh -t http://<grafana_svc_ip>:<grafana_svc_port> -k <api_key> -p
其中 -p 參數(shù)指定的是之前導(dǎo)出的 json 所在的目錄。

目前的方案痛點在于只能備份 Dashboard，不能備份其他的配置（例如，數(shù)據(jù)源、用戶、秘鑰等），而且沒有將 Dashboard 和目錄對應(yīng)起來，即不支持備份 Folder。下面介紹一個比較完美的備份恢復(fù)方案，支持所有配置的備份恢復(fù)，簡直不要太香。

高級方案
更高級的方案已經(jīng)有人寫好了，項目地址是：

https://github.com/ysde/grafana-backup-tool
該備份工具支持以下幾種配置：

目錄
Dashboard
數(shù)據(jù)源
Grafana 告警頻道（Alert Channel）
組織（Organization）
用戶（User）
使用方法很簡單，跑個容器就好了嘛，不過作者提供的 Dockerfile 我不是很滿意，自己修改了點內(nèi)容：

FROM alpine:latest

LABEL maintainer=“grafana-backup-tool Docker Maintainers https://fuckcloudnative.io”

ENV ARCHIVE_FILE “”

RUN echo “@edge http://dl-cdn.alpinelinux.org/alpine/edge/community” >> /etc/apk/repositories;
apk --no-cache add python3 py3-pip py3-cffi py3-cryptography ca-certificates bash git;
git clone https://github.com/ysde/grafana-backup-tool /opt/grafana-backup-tool;
cd /opt/grafana-backup-tool;
pip3 --no-cache-dir install .;
chown -R 1337:1337 /opt/grafana-backup-tool

WORKDIR /opt/grafana-backup-tool

USER 1337
只有 Dockerfile 不行，還得通過 CI/CD 自動構(gòu)建并推送到 docker.io。不要問我用什么，當(dāng)然是白嫖 GitHub Action，workflow 內(nèi)容如下：

#=================================================

https://github.com/yangchuansheng/docker-image

Description: Build and push grafana-backup-tool Docker image

Lisence: MIT

Author: Ryan

Blog: https://fuckcloudnative.io

#=================================================

name: Build and push grafana-backup-tool Docker image

Controls when the action will run. Triggers the workflow on push or pull request

events but only for the master branch

on:
push:
branches: [ master ]
paths:
- ‘grafana-backup-tool/Dockerfile’
- ‘.github/workflows/grafana-backup-tool.yml’
pull_request:
branches: [ master ]
paths:
- ‘grafana-backup-tool/Dockerfile’
#watch:
#types: started

A workflow run is made up of one or more jobs that can run sequentially or in parallel

jobs:

This workflow contains a single job called “build”

build:
# The type of runner that the job will run on
runs-on: ubuntu-latest

# Steps represent a sequence of tasks that will be executed as part of the job steps: # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it - uses: actions/checkout@v2- name: Set up QEMUuses: docker/setup-qemu-action@v1- name: Set up Docker Buildxuses: docker/setup-buildx-action@v1- name: Login to DockerHubuses: docker/login-action@v1 with:username: ${{ secrets.DOCKER_USERNAME }}password: ${{ secrets.DOCKER_PASSWORD }}- name: Login to GitHub Package Registryenv:username: ${{ github.repository_owner }}password: ${{ secrets.GHCR_TOKEN }}run: echo ${{ env.password }} | docker login ghcr.io -u ${{ env.username }} --password-stdin # Runs a single command using the runners shell - name: Build and push Docker images to docker.io and ghcr.iouses: docker/build-push-action@v2with:file: 'grafana-backup-tool/Dockerfile'platforms: linux/386,linux/amd64,linux/arm/v6,linux/arm/v7,linux/arm64,linux/ppc64le,linux/s390xcontext: grafana-backup-toolpush: truetags: |yangchuansheng/grafana-backup-tool:latestghcr.io/yangchuansheng/grafana-backup-tool:latest#- name: Update repo description#uses: peter-evans/dockerhub-description@v2#env:#DOCKERHUB_USERNAME: ${{ secrets.DOCKER_USERNAME }}#DOCKERHUB_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}#DOCKERHUB_REPOSITORY: yangchuansheng/grafana-backup-tool#README_FILEPATH: grafana-backup-tool/readme.md

這里我不打算解釋 workflow 的內(nèi)容，有點基礎(chǔ)的應(yīng)該都能看懂，實在不行，以后我會單獨寫文章解釋（又可以繼續(xù)水文了~）。這個 workflow 實現(xiàn)的功能就是自動構(gòu)建各個 CPU 架構(gòu)的鏡像，并推送到 docker.io 和 ghcr.io，特么的真香！

就問爽不爽？

你可以直接關(guān)注我的倉庫：

https://github.com/yangchuansheng/docker-image
構(gòu)建好鏡像后，就可以直接運行容器來進行備份和恢復(fù)操作了。如果你想在集群內(nèi)操作，可以通過 Deployment 或 Job 來實現(xiàn)；如果你想在本地或 k8s 集群外操作，可以選擇 docker run，我不反對，你也可以選擇 docker-compose，這都沒問題。但我要告訴你一個更騷的辦法，可以騷到讓你無法自拔。

首先需要在本地或集群外安裝 Podman，如果操作系統(tǒng)是 Win10，可以考慮通過 WSL 來安裝；如果操作系統(tǒng)是 Linux，那就不用說了；如果操作系統(tǒng)是 MacOS，請參考我的上篇文章：在 macOS 中使用 Podman。

裝好了 Podman 之后，就可以進行騷操作了，請睜大眼睛。

先編寫一個 Deployment 配置清單（什么？Deployment？是的，你沒聽錯）：

grafana-backup-deployment.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
name: grafana-backup
labels:
app: grafana-backup
spec:
replicas: 1
selector:
matchLabels:
app: grafana-backup
template:
metadata:
labels:
app: grafana-backup
spec:
containers:
- name: grafana-backup
image: yangchuansheng/grafana-backup-tool:latest
imagePullPolicy: IfNotPresent
command: ["/bin/bash"]
tty: true
stdin: true
env:
- name: GRAFANA_TOKEN
value: “eyJr0NkFBeWV1QVpMNjNYWXA3UXNOM2JWMWdZOTB2ZFoiLCJuIjoiYWRtaW4iLCJpZCI6MX0=”
- name: GRAFANA_URL
value: “http://<grafana_ip>:<grafana_port>”
- name: GRAFANA_ADMIN_ACCOUNT
value: “admin”
- name: GRAFANA_ADMIN_PASSWORD
value: “admin”
- name: VERIFY_SSL
value: “False”
volumeMounts:
- mountPath: /opt/grafana-backup-tool
name: data
volumes:
- name: data
hostPath:
path: /mnt/manifest/grafana/backup
這里面的環(huán)境變量根據(jù)自己的實際情況修改，一定不要照抄我的！

不要一臉懵逼，我先來解釋一下為什么要準(zhǔn)備這個 Deployment 配置清單，因為 Podman 可以直接通過這個配置清單運行容器，命令如下：

$ podman play kube grafana-backup-deployment.yaml
我第一次見到這個操作的時候也不禁連連我艸，這也可以？確實可以，不過呢，Podman 只是將其翻譯一下，跑個容器而已，并不是真正運行 Deployment，因為它沒有控制器啊，但是，還是真香！

想象一下，你可以將 k8s 集群中的配置清單拿到本地或測試機器直接跑，再也不用 k8s 集群準(zhǔn)備一份 yaml，docker-compose 再準(zhǔn)備一份 yaml 了，一份 yaml 走天下，服不服？

docker-compose 混到今天這個地步，也是蠻可憐的。

細(xì)心的讀者應(yīng)該能發(fā)現(xiàn)上面的配置清單有點奇怪，Dockerfile 也有點奇怪。Dockerfile 中沒有寫 CMD 或 ENTRYPOINT，Deployment 中直接將啟動命令設(shè)置為 bash，這是因為在我之前測試的過程中發(fā)現(xiàn)該鏡像啟動的容器有點問題，它會陷入一個循環(huán)，備份完了之后又會繼續(xù)備份，不斷重復(fù)，導(dǎo)致備份目錄下生成了一坨壓縮包。目前還沒找到比較好的解決辦法，只能將容器的啟動命令設(shè)置為 bash，等容器運行后再進入容器進行備份操作：

$ podman pod ls
POD ID NAME STATUS CREATED # OF CONTAINERS INFRA ID
728aec216d66 grafana-backup-pod-0 Running 3 minutes ago 2 92aa0824fe7d

$ podman ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
b523fa8e4819 yangchuansheng/grafana-backup-tool:latest /bin/bash 3 minutes ago Up 3 minutes ago grafana-backup-pod-0-grafana-backup
92aa0824fe7d k8s.gcr.io/pause:3.2 3 minutes ago Up 3 minutes ago 728aec216d66-infra

$ podman exec -it grafana-backup-pod-0-grafana-backup bash
bash-5.0$ grafana-backup save
…
…
########################################

backup folders at: OUTPUT/folders/202012111556
backup datasources at: OUTPUT/datasources/202012111556
backup dashboards at: OUTPUT/dashboards/202012111556
backup alert_channels at: OUTPUT/alert_channels/202012111556
backup organizations at: OUTPUT/organizations/202012111556
backup users at: OUTPUT/users/202012111556

created archive at: OUTPUT/202012111556.tar.gz
默認(rèn)情況下會備份所有的組件，你也可以指定備份的組件：

$ grafana-backup save --components=<folders,dashboards,datasources,alert-channels,organizations,users>
比如，我只想備份 Dashboards 和 Folders：

$ grafana-backup save --components=folders,dashboards
當(dāng)然，你也可以全部備份，恢復(fù)的時候再選擇自己想恢復(fù)的組件：

$ grafana-backup restore --components=folders,dashboards
至此，再也不用怕 Dashboard 被改掉或刪除啦。

最后提醒一下，Prometheus Operator 項目中的 Grafana 通過 Provisioning 的方式預(yù)導(dǎo)入了一些默認(rèn)的 Dashboards，這本來沒有什么問題，但 grafana-backup-tool 工具無法忽略跳過已經(jīng)存在的配置，如果恢復(fù)的過程中遇到已經(jīng)存在的配置，會直接報錯退出。本來這也很好解決，一般情況下到 Grafana Web 界面中刪除所有的 Dashboard 就好了，但通過 Provisioning 導(dǎo)入的 Dashboard 是無法刪除的，這就很尷尬了。

在作者修復(fù)這個 bug 之前，要想解決這個問題，有兩個辦法：

第一個辦法是在恢復(fù)之前將 Grafana Deployment 中關(guān)于 Provisioning 的配置全部刪除，就是這些配置：

volumeMounts:- mountPath: /etc/grafana/provisioning/datasourcesname: grafana-datasourcesreadOnly: false- mountPath: /etc/grafana/provisioning/dashboardsname: grafana-dashboardsreadOnly: false- mountPath: /grafana-dashboard-definitions/0/apiservername: grafana-dashboard-apiserverreadOnly: false- mountPath: /grafana-dashboard-definitions/0/cluster-totalname: grafana-dashboard-cluster-totalreadOnly: false- mountPath: /grafana-dashboard-definitions/0/controller-managername: grafana-dashboard-controller-managerreadOnly: false- mountPath: /grafana-dashboard-definitions/0/k8s-resources-clustername: grafana-dashboard-k8s-resources-clusterreadOnly: false- mountPath: /grafana-dashboard-definitions/0/k8s-resources-namespacename: grafana-dashboard-k8s-resources-namespacereadOnly: false- mountPath: /grafana-dashboard-definitions/0/k8s-resources-nodename: grafana-dashboard-k8s-resources-nodereadOnly: false- mountPath: /grafana-dashboard-definitions/0/k8s-resources-podname: grafana-dashboard-k8s-resources-podreadOnly: false- mountPath: /grafana-dashboard-definitions/0/k8s-resources-workloadname: grafana-dashboard-k8s-resources-workloadreadOnly: false- mountPath: /grafana-dashboard-definitions/0/k8s-resources-workloads-namespacename: grafana-dashboard-k8s-resources-workloads-namespacereadOnly: false- mountPath: /grafana-dashboard-definitions/0/kubeletname: grafana-dashboard-kubeletreadOnly: false- mountPath: /grafana-dashboard-definitions/0/namespace-by-podname: grafana-dashboard-namespace-by-podreadOnly: false- mountPath: /grafana-dashboard-definitions/0/namespace-by-workloadname: grafana-dashboard-namespace-by-workloadreadOnly: false- mountPath: /grafana-dashboard-definitions/0/node-cluster-rsrc-usename: grafana-dashboard-node-cluster-rsrc-usereadOnly: false- mountPath: /grafana-dashboard-definitions/0/node-rsrc-usename: grafana-dashboard-node-rsrc-usereadOnly: false- mountPath: /grafana-dashboard-definitions/0/nodesname: grafana-dashboard-nodesreadOnly: false- mountPath: /grafana-dashboard-definitions/0/persistentvolumesusagename: grafana-dashboard-persistentvolumesusagereadOnly: false- mountPath: /grafana-dashboard-definitions/0/pod-totalname: grafana-dashboard-pod-totalreadOnly: false- mountPath: /grafana-dashboard-definitions/0/prometheus-remote-writename: grafana-dashboard-prometheus-remote-writereadOnly: false- mountPath: /grafana-dashboard-definitions/0/prometheusname: grafana-dashboard-prometheusreadOnly: false- mountPath: /grafana-dashboard-definitions/0/proxyname: grafana-dashboard-proxyreadOnly: false- mountPath: /grafana-dashboard-definitions/0/schedulername: grafana-dashboard-schedulerreadOnly: false- mountPath: /grafana-dashboard-definitions/0/statefulsetname: grafana-dashboard-statefulsetreadOnly: false- mountPath: /grafana-dashboard-definitions/0/workload-totalname: grafana-dashboard-workload-totalreadOnly: false

…
…
volumes:
- name: grafana-datasources
secret:
secretName: grafana-datasources
- configMap:
name: grafana-dashboards
name: grafana-dashboards
- configMap:
name: grafana-dashboard-apiserver
name: grafana-dashboard-apiserver
- configMap:
name: grafana-dashboard-cluster-total
name: grafana-dashboard-cluster-total
- configMap:
name: grafana-dashboard-controller-manager
name: grafana-dashboard-controller-manager
- configMap:
name: grafana-dashboard-k8s-resources-cluster
name: grafana-dashboard-k8s-resources-cluster
- configMap:
name: grafana-dashboard-k8s-resources-namespace
name: grafana-dashboard-k8s-resources-namespace
- configMap:
name: grafana-dashboard-k8s-resources-node
name: grafana-dashboard-k8s-resources-node
- configMap:
name: grafana-dashboard-k8s-resources-pod
name: grafana-dashboard-k8s-resources-pod
- configMap:
name: grafana-dashboard-k8s-resources-workload
name: grafana-dashboard-k8s-resources-workload
- configMap:
name: grafana-dashboard-k8s-resources-workloads-namespace
name: grafana-dashboard-k8s-resources-workloads-namespace
- configMap:
name: grafana-dashboard-kubelet
name: grafana-dashboard-kubelet
- configMap:
name: grafana-dashboard-namespace-by-pod
name: grafana-dashboard-namespace-by-pod
- configMap:
name: grafana-dashboard-namespace-by-workload
name: grafana-dashboard-namespace-by-workload
- configMap:
name: grafana-dashboard-node-cluster-rsrc-use
name: grafana-dashboard-node-cluster-rsrc-use
- configMap:
name: grafana-dashboard-node-rsrc-use
name: grafana-dashboard-node-rsrc-use
- configMap:
name: grafana-dashboard-nodes
name: grafana-dashboard-nodes
- configMap:
name: grafana-dashboard-persistentvolumesusage
name: grafana-dashboard-persistentvolumesusage
- configMap:
name: grafana-dashboard-pod-total
name: grafana-dashboard-pod-total
- configMap:
name: grafana-dashboard-prometheus-remote-write
name: grafana-dashboard-prometheus-remote-write
- configMap:
name: grafana-dashboard-prometheus
name: grafana-dashboard-prometheus
- configMap:
name: grafana-dashboard-proxy
name: grafana-dashboard-proxy
- configMap:
name: grafana-dashboard-scheduler
name: grafana-dashboard-scheduler
- configMap:
name: grafana-dashboard-statefulset
name: grafana-dashboard-statefulset
- configMap:
name: grafana-dashboard-workload-total
name: grafana-dashboard-workload-total
第二個辦法就是刪除 Prometheus Operator 自帶的 Grafana，自己通過 Helm 或者 manifest 部署不使用 Provisioning 的 Grafana。

如果你既不想刪除 Provisioning 的配置，也不想自己部署 Grafana，那只能使用上文提到的低級方案了。

Kubernetes 1.18.2 1.17.5 1.16.9 1.15.12離線安裝包發(fā)布地址http://store.lameleg.com ，歡迎體驗。 使用了最新的sealos v3.3.6版本。 作了主機名解析配置優(yōu)化，lvscare 掛載/lib/module解決開機啟動ipvs加載問題， 修復(fù)lvscare社區(qū)netlink與3.10內(nèi)核不兼容問題,sealos生成百年證書等特性。更多特性 https://github.com/fanux/sealos 。歡迎掃描下方的二維碼加入釘釘群 ，釘釘群已經(jīng)集成sealos的機器人實時可以看到sealos的動態(tài)。

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