Saltstack net-api Runner/Local模块调用分析
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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
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`https://github.com/saltstack/salt.git`中`/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.
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/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.
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/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:
...
在_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,
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/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RunnerClient的async方法.
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/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
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/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.
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/salt/salt/client/mixins.py
def low(self, fun, low):
...
data['return'] = self.functions[fun](*args, **kwargs)
...
小结
- 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.
- 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. - 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
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(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MinionSaltAPIHandler的post方法. 底层只支持local_async方法.
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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
- 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.
- 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.