如何设置自动缩放 RabbitMQ 集群 AWS [英] How to set up autoscaling RabbitMQ Cluster AWS
问题描述
我正在尝试从 SQS 转移到 RabbitMQ 以进行消息传递服务.我希望构建一个稳定的高可用性排队服务.现在我要使用集群.
I'm trying to move away from SQS to RabbitMQ for messaging service. I'm looking to build a stable high availability queuing service. For now I'm going with cluster.
当前实施,我有三台带有 RabbitMQ 的 EC2 机器,在 AMI 中安装了管理插件,然后我明确地转到每台机器并添加
Current Implementation , I have three EC2 machines with RabbitMQ with management plugin installed in a AMI , and then I explicitly go to each of the machine and add
sudo rabbitmqctl join_cluster rabbit@<hostnameOfParentMachine>
HA 属性设置为 all 并且同步工作.并且在它上面有一个负载均衡器,并分配了 DNS.到目前为止,这件事奏效了.
With HA property set to all and the synchronization works. And a load balancer on top it with a DNS assigned. So far this thing works.
预期实施:创建一个自动扩展的集群环境,在该环境中,上升/下降的机器必须动态加入/移除集群.实现这一目标的最佳方法是什么?请帮忙.
Expected Implementation: Create an autoscaling clustered environment where the machines that go Up/Down has to join/Remove the cluster dynamically. What is the best way to achieve this? Please help.
推荐答案
2 年前我也有类似的配置.
I had a similar configuration 2 years ago.
我决定使用 amazon VPC,默认情况下我的设计总是有两个 RabbitMQ 实例运行,并在集群中配置(称为主节点).rabbitmq 集群支持 内部亚马逊负载均衡器.
I decided to use amazon VPC, by default my design had two RabbitMQ instances always running, and configured in cluster (called master-nodes). The rabbitmq cluster was behind an internal amazon load balancer.
我创建了一个配置了 RabbitMQ 和管理插件的 AMI(称为master-AMI"),然后我配置了自动缩放规则.
I created an AMI with RabbitMQ and management plug-in configured (called "master-AMI"), and then I configured the autoscaling rules.
如果发出自动缩放警报,则会启动新的主 AMI.此 AMI 第一次执行时执行以下脚本:
if an autoscaling alarm is raised a new master-AMI is launched. This AMI executes the follow script the first time is executed:
#!/usr/bin/env python
import json
import urllib2,base64
if __name__ == '__main__':
prefix =''
from subprocess import call
call(["rabbitmqctl", "stop_app"])
call(["rabbitmqctl", "reset"])
try:
_url = 'http://internal-myloadbalamcer-xxx.com:15672/api/nodes'
print prefix + 'Get json info from ..' + _url
request = urllib2.Request(_url)
base64string = base64.encodestring('%s:%s' % ('guest', 'guest')).replace('
', '')
request.add_header("Authorization", "Basic %s" % base64string)
data = json.load(urllib2.urlopen(request))
##if the script got an error here you can assume that it's the first machine and then
## exit without controll the error. Remember to add the new machine to the balancer
print prefix + 'request ok... finding for running node'
for r in data:
if r.get('running'):
print prefix + 'found running node to bind..'
print prefix + 'node name: '+ r.get('name') +'- running:' + str(r.get('running'))
from subprocess import call
call(["rabbitmqctl", "join_cluster",r.get('name')])
break;
pass
except Exception, e:
print prefix + 'error during add node'
finally:
from subprocess import call
call(["rabbitmqctl", "start_app"])
pass
脚本使用 HTTP APIhttp://internal-myloadbalamcer-xxx.com:15672/api/nodes"找到节点,然后选择一个并将新的AMI绑定到集群.
The scripts uses the HTTP API "http://internal-myloadbalamcer-xxx.com:15672/api/nodes" to find nodes, then choose one and binds the new AMI to the cluster.
作为 HA 策略,我决定使用它:
As HA policy I decided to use this:
rabbitmqctl set_policy ha-two "^two." ^
"{""ha-mode"":""exactly"",""ha-params"":2,"ha-sync-mode":"automatic"}"
好吧,加入相当"容易,问题是决定何时可以从集群中删除节点.
Well, the join is "quite" easy, the problem is decide when you can remove the node from the cluster.
您不能根据自动缩放规则删除节点,因为您可以将消息发送到您必须使用的队列.
You can’t remove a node based on autoscaling rule, because you can have messages to the queues that you have to consume.
我决定执行一个定期运行到两个主节点实例的脚本:
I decided to execute a script periodically running to the two master-node instances that:
- 通过 API http://node:15672/api/queues
- 如果所有队列的消息计数为零,我可以从负载均衡器中删除该实例,然后从 rabbitmq 集群中删除.
我大致就是这么干的,希望能帮到你.
This is broadly what I did, hope it helps.
我编辑了答案,因为有这个插件可以提供帮助:
I edited the answer, since there is this plugin that can help:
我建议看这个:https://github.com/rabbitmq/rabbitmq-autocluster一个>
插件已移至RabbitMQ官方仓库,可以轻松解决此类问题
The plugin has been moved to the official RabbitMQ repository, and can easly solve this kind of the problems
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