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一百八十二

發布時間：2023/12/20 编程问答 36 豆豆

生活随笔收集整理的這篇文章主要介紹了一百八十二小編覺得挺不錯的,現在分享給大家,幫大家做個參考.

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，發現大部分備份方案都是通過 shell 腳本調用 Grafana 的 API 來導出各種配置。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。

導出腳本
#!/bin/bash

Usage:

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

create_slug () {
echo " $1" | iconv -t ascii//TRANSLIT | sed -r s/[^a-zA-Z0-9]+/-/g | sed -r s/^-+\|-+$ //g | tr A-Z a-z
}

full_url= $1 u s e r n a m e =$ (echo " ${full_url}" | cut -d/ -f 3 | cut -d: -f 1) base_url=$ (echo " ${full_url}" | cut -d@ -f 2) folder=$ (create_slug “ ${username}-$ {base_url}”)

mkdir “${folder}”
for db_uid in $(c u r l ? s "$ {full_url}/api/search" | jq -r .[].uid); do
db_json= $(c u r l ? s "$ {full_url}/api/dashboards/uid/ ${db_uid}") db_slug=$ (echo " ${db_json}" | jq -r .meta.slug) db_title=$ (echo “ ${db_json}" | jq -r .dashboard.title) filename="$ {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，直接導出了所有 Dashboard 的 json 配置，也沒有標記目錄信息，如果你用它導出的配置來恢復 Grafana，所有的 Dashboard 都會導入到 Grafana 的 General 目錄下，不太友好。

導入腳本
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 “ $O P T S P E C " o p t c h a r; d o c a s e "$ optchar” in
h)
show_help
exit
;;
p)
DASH_DIR=“ $O P T A R G ";; t) H O S T = "$ 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 “ $DASH_DIR" ] || [ -z "$ 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 " $DASH_DIR" ]; then DASH_LIST=$ (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 $DASH_DIR does not appear to contain any JSON files for import. Check your path and try again." exit 1 else FILESTOTAL=$ (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 $DASH_LIST; do COUNTER=$ ((COUNTER + 1))
echo “Import $C O U N T E R /$ FILESTOTAL: $DASH_FILE..." RESULT=$ (cat “$DASH_FILE” | jq ‘. * {overwrite: true, dashboard: {id: null}}’ | curl -s -X POST -H “Content-Type: application/json” -H “Authorization: Bearer $K E Y " "$ HOST”/api/dashboards/db -d @-)
if [[ “ $RESULT" == *"success"* ]]; then log_success "$ RESULT”
NUMSUCCESS= $NUMSUCCESS + 1)) else log_failure "$ RESULT”
NUMFAILURE=$((NUMFAILURE + 1))
fi
done

log_title “Import complete. $NUMSUCCESS dashboards were successfully imported. $NUMFAILURE dashboard imports failed.”;
log_title “------------------------------ FINISHED ---------------------------------”;
導入腳本需要目標機器上的 Grafana 已經啟動，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，過期時間自己調整：

導入方式：

$ ./grafana-dashboard-importer.sh -t http://<grafana_svc_ip>:<grafana_svc_port> -k <api_key> -p
其中 -p 參數指定的是之前導出的 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，數據源、用戶、秘鑰等），而且沒有將 Dashboard 和目錄對應起來，即不支持備份 Folder。下面介紹一個比較完美的備份恢復方案，支持所有配置的備份恢復，簡直不要太香。

高級方案
更高級的方案已經有人寫好了，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
數據源
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 自動構建并推送到 docker.io。不要問我用什么，當然是白嫖 GitHub Action，workflow 內容如下：

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

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 的內容，有點基礎的應該都能看懂，實在不行，以后我會單獨寫文章解釋（又可以繼續水文了~）。這個 workflow 實現的功能就是自動構建各個 CPU 架構的鏡像，并推送到 docker.io 和 ghcr.io，特么的真香！

就問爽不爽？

你可以直接關注我的倉庫：

https://github.com/yangchuansheng/docker-image
構建好鏡像后，就可以直接運行容器來進行備份和恢復操作了。如果你想在集群內操作，可以通過 Deployment 或 Job 來實現；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，如果操作系統是 Win10，可以考慮通過 WSL 來安裝；如果操作系統是 Linux，那就不用說了；如果操作系統是 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
這里面的環境變量根據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 集群準備一份 yaml，docker-compose 再準備一份 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。

細心的讀者應該能發現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置為 bash，這是因為在我之前測試的過程中發現該鏡像啟動的容器有點問題，它會陷入一個循環，備份完了之后又會繼續備份，不斷重復，導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
當然，你也可以全部備份，恢復的時候再選擇自己想恢復的組件：

$ 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 的方式預導入了一些默認的 Dashboards，這本來沒有什么問題，但 grafana-backup-tool 工具無法忽略跳過已經存在的配置，如果恢復的過程中遇到已經存在的配置，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 導入的 Dashboard 是無法刪除的，這就很尷尬了。

在作者修復這個 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之前將 Grafana Deployment 中關于 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化，lvscare 掛載/lib/module解決開機啟動ipvs加載問題，修復lvscare社區netlink與3.10內核不兼容問題,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，釘釘群已經集成sealos的機器人實時可以看到sealos的動態。

總結

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一百八十二

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