Saltstack net-api Runner/Local模块调用分析

1 分钟阅读

Contact me

或者用邮件交流 jacky.wucheng@foxmail.com

背景

该分析代码基于salt版本2015.5, 以下”/salt”为代码根目录.

源码路径在

1
    `https://github.com/saltstack/salt.git``/salt/netapi/rest_tornado` 

Runner 模块调用

runner模块之前的调用流程可以参考 这里

runner模块的调用接口是”/run”, 匹配到saltnado.RunSaltAPIHandler类处理.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
    /salt/salt/netapi/rest_tornado/saltnado.py

    RunSaltAPIHandler
        post()
    -> 
    SaltAPIHandler
        disbatch()
            ...
            chunk_ret = yield getattr(self, '_disbatch_{0}'.format(low['client']))(low)
            ret.append(chunk_ret)
            ...
    -> 以调用runner模块为例
    _disbatch_runner() , 这是yield这行代码获取到的函数名.
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
    /salt/salt/netapi/rest_tornado/saltnado.py
    
    @tornado.gen.coroutine
    def _disbatch_runner(self, chunk):
        '''
        Disbatch runner client commands
        '''
        f_call = {'args': [chunk['fun'], chunk]}
        pub_data = self.saltclients['runner'](chunk['fun'], chunk)
        tag = pub_data['tag'] + '/ret'
        try:
            event = yield self.application.event_listener.get_event(self, tag=tag)
            ...
        except TimeoutException:
            ...

_disbatch_runner里调用了self.saltclients['runner'](chunk['fun'], chunk), self.saltclients['runner']是什么可以在class SaltClientsMixIn(object)里找到,

1
2
3
4
5
6
7
8
9
10
11
    /salt/salt/netapi/rest_tornado/saltnado.py
    
    SaltClientsMixIn.__saltclients = {
        'local': local_client.run_job,
        # not the actual client we'll use.. but its what we'll use to get args
        'local_batch': local_client.cmd_batch,
        'local_async': local_client.run_job,
        'runner': salt.runner.RunnerClient(opts=self.application.opts).async,
        'runner_async': None,  # empty, since we use the same client as `runner`
        }
        

所以看RunnerClientasync方法.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
    /salt/salt/client/mixins.py
    
    def async(self, fun, low, user='UNKNOWN'):
        '''
        Execute the function in a multiprocess and return the event tag to use
        to watch for the return
        '''
        async_pub = self._gen_async_pub()

        proc = multiprocessing.Process(
                target=self._proc_function,
                args=(fun, low, user, async_pub['tag'], async_pub['jid']))
        proc.start()
        proc.join()  # MUST join, otherwise we leave zombies all over
        return async_pub

调用了self._proc_function创建了一个进程去执行 fun , 然后将tag返回, 这个tag用来获取命令执行结果event = yield self.application.event_listener.get_event(self, tag=tag).

真正执行fun函数的地方在

1
2
3
4
5
6
7
8
    /salt/salt/client/mixins.py
    
    class AsyncClientMixin(object):
        def _proc_function(self, fun, low, user, tag, jid, daemonize=True):
            ...
            return self.low(fun, low)
            ...
            

最底层的self.low方法调用.

1
2
3
4
5
6
    /salt/salt/client/mixins.py

    def low(self, fun, low):
        ...
        data['return'] = self.functions[fun](*args, **kwargs)
        ...

小结

  1. 通过上面的代码分析来看, 从net-api里的tornado到最终通过low()方法执行结果, 都是通过函数直接调用完成的, 没有通过rpc或者进程间通信. 所以只要你是想通过net-api执行runner模块, net-api和saltmaster必须部署在同一台机器上.
  2. 如果发现salt-api进程特别多, 那说明是_proc_function调用者特别多, 而该进程的执行时间又比较长, 所以这种情况下我们需要分析具体是调用了什么runner模块, 在这块进行优化.
  3. 如果salt-api需要水平扩展, 则需要net-api + saltmaster一块扩展.

Local 模块调用

通过对/salt/salt/netapi/rest_tornado/__init__.py代码中的tornado url映射入口可知

1
2
    (r"/minions/(.*)", saltnado.MinionSaltAPIHandler),
    (r"/minions", saltnado.MinionSaltAPIHandler), 

跟minion有关的操作都是由saltnado.MinionSaltAPIHandler这个类来处理的. 通过代码和PYTHON CLIENT API文档我们也可以知道对”/minions/(.*)”和”/minions/”的GET方法是获取minion信息, 对”/minions”的POST方法是给相应的minion发送命令.

我们看MinionSaltAPIHandlerpost方法. 底层只支持local_async方法.

1
2
3
4
5
6
7
8
9
10
11
12
13
     for low in self.lowstate:
         # if you didn't specify, its fine
         if 'client' not in low:
             low['client'] = 'local_async'
             continue
         # if you specified something else, we don't do that
         if low.get('client') != 'local_async':
             self.set_status(400)
             self.write('We don\'t serve your kind here')
             self.finish()
             return
    self.disbatch()
    

判断client为local_async后, self.disbatch()会调用到_disbatch_local_async方法, 再接着从上文的SaltClientsMixIn.__saltclients我们知道local_client.run_job会被调用到. 在SaltStack源码分析 - 任务处理机制文章中已经解释到了, 接下来会把命令提交到ReqServer的TCP:4506端口,并且监听在EventPublisher ipc上获取结果, 得到结果后从http接口返回.

小结

  1. 虽然发送指令是通过TCP: 4506进行, 可以跨网络提交, 但是获取结果却是要监听在 salt-master 同机器的EventPublisher ipc上, 所以在api的同步调用模式下, salt-api和salt-master是要一块部署的.
  2. 当然从代码来看, salt-api和salt-master也可以分开部署, 前提就是不同步等待EventPublisher ipc上的结果, 而是用异步的方式让master将结果写到外部存储.

参考