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小知识：用Docker swarm快速部署Nebula Graph集群的教程

一、前言

本文介绍如何使用 Docker Swarm 来部署 Nebula Graph 集群。

%小知识：用Docker swarm快速部署Nebula Graph集群的教程-猿站网-插图

二、nebula集群搭建

2.1 环境准备

机器准备

ip

内存(Gb)

cpu(核数)

192.168.1.166

16

4

192.168.1.167

16

4

192.168.1.168

16

4

在安装前确保所有机器已安装docker

2.2 初始化swarm集群

在192.168.1.166机器上执行

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$ docker swarm init –advertise-addr 192.168.1.166
Swarm initialized: current node (dxn1zf6l61qsb1josjja83ngz) is now a manager.
To add a worker to this swarm, run the following command:
docker swarm join \
–token SWMTKN-1-49nj1cmql0jkz5s954yi3oex3nedyz0fb0xx14ie39trti4wxv-8vxv8rssmk743ojnwacrr2e7c \
192.168.1.166:2377
To add a manager to this swarm, run docker swarm join-token manager and follow the instructions.

2.3 加入worker节点

根据init命令提示内容，加入swarm worker节点，在192.168.1.167 192.168.1.168分别执行

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docker swarm join \
–token SWMTKN-1-49nj1cmql0jkz5s954yi3oex3nedyz0fb0xx14ie39trti4wxv-8vxv8rssmk743ojnwacrr2e7c \
192.168.1.166:2377

2.4 验证集群

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docker node ls
ID       HOSTNAME   STATUS    AVAILABILITY  MANAGER STATUS  ENGINE VERSION
h0az2wzqetpwhl9ybu76yxaen * KF2-DATA-166  Ready    Active    Reachable   18.06.1-ce
q6jripaolxsl7xqv3cmv5pxji  KF2-DATA-167  Ready    Active    Leader    18.06.1-ce
h1iql1uvm7123h3gon9so69dy  KF2-DATA-168  Ready    Active         18.06.1-ce

2.5 配置docker stack

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vi docker-stack.yml

配置如下内容

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version: 3.6
services:
metad0:
image: vesoft/nebula-metad:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –local_ip=192.168.1.166
– –ws_ip=192.168.1.166
– –port=45500
– –data_path=/data/meta
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-166
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.166:11000/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 11000
published: 11000
protocol: tcp
mode: host
– target: 11002
published: 11002
protocol: tcp
mode: host
– target: 45500
published: 45500
protocol: tcp
mode: host
volumes:
– data-metad0:/data/meta
– logs-metad0:/logs
networks:
– nebula-net
metad1:
image: vesoft/nebula-metad:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –local_ip=192.168.1.167
– –ws_ip=192.168.1.167
– –port=45500
– –data_path=/data/meta
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-167
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.167:11000/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 11000
published: 11000
protocol: tcp
mode: host
– target: 11002
published: 11002
protocol: tcp
mode: host
– target: 45500
published: 45500
protocol: tcp
mode: host
volumes:
– data-metad1:/data/meta
– logs-metad1:/logs
networks:
– nebula-net
metad2:
image: vesoft/nebula-metad:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –local_ip=192.168.1.168
– –ws_ip=192.168.1.168
– –port=45500
– –data_path=/data/meta
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-168
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.168:11000/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 11000
published: 11000
protocol: tcp
mode: host
– target: 11002
published: 11002
protocol: tcp
mode: host
– target: 45500
published: 45500
protocol: tcp
mode: host
volumes:
– data-metad2:/data/meta
– logs-metad2:/logs
networks:
– nebula-net
storaged0:
image: vesoft/nebula-storaged:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –local_ip=192.168.1.166
– –ws_ip=192.168.1.166
– –port=44500
– –data_path=/data/storage
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-166
depends_on:
– metad0
– metad1
– metad2
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.166:12000/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 12000
published: 12000
protocol: tcp
mode: host
– target: 12002
published: 12002
protocol: tcp
mode: host
volumes:
– data-storaged0:/data/storage
– logs-storaged0:/logs
networks:
– nebula-net
storaged1:
image: vesoft/nebula-storaged:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –local_ip=192.168.1.167
– –ws_ip=192.168.1.167
– –port=44500
– –data_path=/data/storage
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-167
depends_on:
– metad0
– metad1
– metad2
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.167:12000/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 12000
published: 12000
protocol: tcp
mode: host
– target: 12002
published: 12004
protocol: tcp
mode: host
volumes:
– data-storaged1:/data/storage
– logs-storaged1:/logs
networks:
– nebula-net
storaged2:
image: vesoft/nebula-storaged:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –local_ip=192.168.1.168
– –ws_ip=192.168.1.168
– –port=44500
– –data_path=/data/storage
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-168
depends_on:
– metad0
– metad1
– metad2
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.168:12000/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 12000
published: 12000
protocol: tcp
mode: host
– target: 12002
published: 12006
protocol: tcp
mode: host
volumes:
– data-storaged2:/data/storage
– logs-storaged2:/logs
networks:
– nebula-net
graphd1:
image: vesoft/nebula-graphd:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –port=3699
– –ws_ip=192.168.1.166
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-166
depends_on:
– metad0
– metad1
– metad2
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.166:13000/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 3699
published: 3699
protocol: tcp
mode: host
– target: 13000
published: 13000
protocol: tcp
#  mode: host
– target: 13002
published: 13002
protocol: tcp
mode: host
volumes:
– logs-graphd:/logs
networks:
– nebula-net
graphd2:
image: vesoft/nebula-graphd:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –port=3699
– –ws_ip=192.168.1.167
– –log_dir=/logs
– –v=2
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-167
depends_on:
– metad0
– metad1
– metad2
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.167:13001/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 3699
published: 3640
protocol: tcp
mode: host
– target: 13000
published: 13001
protocol: tcp
mode: host
– target: 13002
published: 13003
protocol: tcp
#  mode: host
volumes:
– logs-graphd2:/logs
networks:
– nebula-net
graphd3:
image: vesoft/nebula-graphd:nightly
env_file:
– ./nebula.env
command:
– –meta_server_addrs=192.168.1.166:45500,192.168.1.167:45500,192.168.1.168:45500
– –port=3699
– –ws_ip=192.168.1.168
– –log_dir=/logs
– –v=0
– –minloglevel=2
deploy:
replicas: 1
restart_policy:
condition: on-failure
placement:
constraints:
– node.hostname == KF2-DATA-168
depends_on:
– metad0
– metad1
– metad2
healthcheck:
test: [“CMD”, “curl”, “-f”, “http://192.168.1.168:13002/status”]
interval: 30s
timeout: 10s
retries: 3
start_period: 20s
ports:
– target: 3699
published: 3641
protocol: tcp
mode: host
– target: 13000
published: 13002
protocol: tcp
#  mode: host
– target: 13002
published: 13004
protocol: tcp
mode: host
volumes:
– logs-graphd3:/logs
networks:
– nebula-net
networks:
nebula-net:
external: true
attachable: true
name: host
volumes:
data-metad0:
logs-metad0:
data-metad1:
logs-metad1:
data-metad2:
logs-metad2:
data-storaged0:
logs-storaged0:
data-storaged1:
logs-storaged1:
data-storaged2:
logs-storaged2:
logs-graphd:
logs-graphd2:
logs-graphd3:
docker-stack.yml

编辑 nebula.env

加入如下内容

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TZ=UTC
USER=root

nebula.env

2.6 启动nebula集群

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docker stack deploy nebula -c docker-stack.yml

三、集群负载均衡及高可用配置

Nebula Graph的客户端目前(1.X)没有提供负载均衡的能力，只是随机选一个graphd去连接。所以生产使用的时候要自己做个负载均衡和高可用。

%小知识：用Docker swarm快速部署Nebula Graph集群的教程-1猿站网-插图

图3.1

将整个部署架构分为三层，数据服务层，负载均衡层及高可用层。如图3.1所示

负载均衡层：对client请求做负载均衡，将请求分发至下方数据服务层

高可用层: 这里实现的是haproxy的高可用，保证负载均衡层的服务从而保证整个集群的正常服务

3.1 负载均衡配置

haproxy使用docker-compose配置。分别编辑以下三个文件

Dockerfile 加入以下内容

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FROM haproxy:1.7
COPY haproxy.cfg /usr/local/etc/haproxy/haproxy.cfg
EXPOSE 3640

Dockerfile

docker-compose.yml加入以下内容

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version: “3.2”
services:
haproxy:
container_name: haproxy
build: .
volumes:
– ./haproxy.cfg:/usr/local/etc/haproxy/haproxy.cfg
ports:
– 3640:3640
restart: always
networks:
– app_net
networks:
app_net:
external: true

docker-compose.yml

haproxy.cfg加入以下内容

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global
daemon
maxconn 30000
log 127.0.0.1 local0 info
log 127.0.0.1 local1 warning
defaults
log-format %hr\ %ST\ %B\ %Ts
log global
mode http
option http-keep-alive
timeout connect 5000ms
timeout client 10000ms
timeout server 50000ms
timeout http-request 20000ms
# custom your own frontends && backends && listen conf
#CUSTOM
listen graphd-cluster
bind *:3640
mode tcp
maxconn 300
balance roundrobin
server server1 192.168.1.166:3699 maxconn 300 check
server server2 192.168.1.167:3699 maxconn 300 check
server server3 192.168.1.168:3699 maxconn 300 check
listen stats
bind *:1080
stats refresh 30s
stats uri /stats

3.2 启动haproxy

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docker-compose up -d

3.2 高可用配置

注：配置keepalive需预先准备好vip (虚拟ip)，在以下配置中192.168.1.99便为虚拟ip

在192.168.1.166 、192.168.1.167、192.168.1.168上均做以下配置

安装keepalived

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apt-get update && apt-get upgrade && apt-get install keepalived -y

更改keepalived配置文件/etc/keepalived/keepalived.conf（三台机器中 做如下配置，priority应设置不同值确定优先级）

192.168.1.166机器配置

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global_defs {
router_id lb01 #标识信息，一个名字而已；
}
vrrp_script chk_haproxy {
script “killall -0 haproxy” interval 2
}
vrrp_instance VI_1 {
state MASTER
interface ens160
virtual_router_id 52
priority 999
# 设定MASTER与BACKUP负载均衡器之间同步检查的时间间隔，单位是秒
advert_int 1
# 设置验证类型和密码
authentication {
# 设置验证类型，主要有PASS和AH两种
auth_type PASS
# 设置验证密码，在同一个vrrp_instance下，MASTER与BACKUP必须使用相同的密码才能正常通信
auth_pass amber1
}
virtual_ipaddress {
# 虚拟IP为192.168.1.99/24;绑定接口为ens160;别名ens169:1，主备相同
192.168.1.99/24 dev ens160 label ens160:1
}
track_script {
chk_haproxy
}
}

167机器配置

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global_defs {
router_id lb01 #标识信息，一个名字而已；
}
vrrp_script chk_haproxy {
script “killall -0 haproxy” interval 2
}
vrrp_instance VI_1 {
state BACKUP
interface ens160
virtual_router_id 52
priority 888
# 设定MASTER与BACKUP负载均衡器之间同步检查的时间间隔，单位是秒
advert_int 1
# 设置验证类型和密码
authentication {
# 设置验证类型，主要有PASS和AH两种
auth_type PASS
# 设置验证密码，在同一个vrrp_instance下，MASTER与BACKUP必须使用相同的密码才能正常通信
auth_pass amber1
}
virtual_ipaddress {
# 虚拟IP为192.168.1.99/24;绑定接口为ens160;别名ens160:1，主备相同
192.168.1.99/24 dev ens160 label ens160:1
}
track_script {
chk_haproxy
}
}

168机器配置

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global_defs {
router_id lb01 #标识信息，一个名字而已；
}
vrrp_script chk_haproxy {
script “killall -0 haproxy” interval 2
}
vrrp_instance VI_1 {
state BACKUP
interface ens160
virtual_router_id 52
priority 777
# 设定MASTER与BACKUP负载均衡器之间同步检查的时间间隔，单位是秒
advert_int 1
# 设置验证类型和密码
authentication {
# 设置验证类型，主要有PASS和AH两种
auth_type PASS
# 设置验证密码，在同一个vrrp_instance下，MASTER与BACKUP必须使用相同的密码才能正常通信
auth_pass amber1
}
virtual_ipaddress {
# 虚拟IP为192.168.1.99/24;绑定接口为ens160;别名ens160:1，主备相同
192.168.1.99/24 dev ens160 label ens160:1
}
track_script {
chk_haproxy
}
}

keepalived相关命令

?
1
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5
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# 启动keepalived
systemctl start keepalived
# 使keepalived开机自启
systemctl enable keeplived
# 重启keepalived
systemctl restart keepalived

四、其他

离线怎么部署？把镜像更改为私有镜像库就成了，有问题欢迎来勾搭啊。

%小知识：用Docker swarm快速部署Nebula Graph集群的教程-2猿站网-插图

到此这篇关于用Docker swarm快速部署Nebula Graph集群的文章就介绍到这了,更多相关Docker 部署Nebula Graph集群内容请搜索服务器之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持服务器之家！

原文链接：https://www.cnblogs.com/qflyue/p/13734795.html

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