CN112711428B - Dynamic deployment method and system based on ANSIBLE - Google Patents
Dynamic deployment method and system based on ANSIBLE Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000009434 installation Methods 0.000 claims abstract description 14
- 238000004806 packaging method and process Methods 0.000 claims abstract description 7
- 238000012423 maintenance Methods 0.000 abstract description 6
- 230000005540 biological transmission Effects 0.000 abstract description 4
- 239000000306 component Substances 0.000 description 21
- 230000006870 function Effects 0.000 description 5
- 241000283965 Ochotona princeps Species 0.000 description 3
- 244000166124 Eucalyptus globulus Species 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
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- 235000015849 Apium graveolens Dulce Group Nutrition 0.000 description 1
- 235000010591 Appio Nutrition 0.000 description 1
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- 239000008358 core component Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/60—Software deployment
- G06F8/61—Installation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/445—Program loading or initiating
- G06F9/44505—Configuring for program initiating, e.g. using registry, configuration files
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/445—Program loading or initiating
- G06F9/44521—Dynamic linking or loading; Link editing at or after load time, e.g. Java class loading
- G06F9/44526—Plug-ins; Add-ons
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Abstract
The invention discloses a dynamic deployment method and a system based on ANSIBLE, belonging to the field of automatic operation and maintenance; the method comprises the following specific steps: s1, determining a rabkitMQ configuration; s2, writing a receiver.py in a normal process of the machine to receive information; s3, calling up an execution method through cell packaging; s4, determining an Inventory according to the parameters transferred by the mq; s5, determining vars according to the parameters transferred by the mq; s6, executing a playbook to perform installation and deployment; s7, returning a result by rewriting execution of the callback custom stable; s8, sending a callback message to the mq; the invention dynamically determines the inventory by combining the mq parameter transmission mode with the database query, reduces the complexity and risk of manual maintenance, and can receive the execution condition in time by rewriting the callback method; the invention also realizes simultaneous multitasking based on celly, and increases the working efficiency.
Description
Technical Field
The invention discloses a dynamic deployment method and system based on ANSIBLE, and relates to the technical field of automatic operation and maintenance.
Background
It is well known that anstable supports multi-node publishing and remote task execution. By default SSH is used for remote connection. The extension can be performed using various programming languages without installing additional software on the managed node. Meanwhile, the Anstable has the following characteristics:
the modular design is provided, and an Anstable can call a specific module to complete a specific task, and the modular design is a core component and is short and exquisite;
anstable is realized based on Python language, and is realized by three key modules of PyYAML and Jinja2 (templated) through Paramiko (one concurrency connection ssh host function library of Python);
the deployment of the Ancable is simple, and the agentless has no client tool;
operating in a master-slave mode;
supporting the function of a custom module;
supporting a playbook script, and completing continuous tasks according to a sequence;
each command is expected to have idempotent;
the existing manual database dynamic query method has the risks of complicated maintenance and data security, can only execute a single task of query, and has lower working efficiency, so the invention discloses a dynamic deployment method and system based on ANSIBLE, which aims to solve the problems.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a dynamic deployment method and a system based on ANSIBLE, and the adopted technical scheme is as follows: a dynamic deployment method based on ANSIBLE comprises the following specific steps:
s1, determining a rabhitMQ configuration:
def getConnection():
credentials＝pika.PlainCredentials('guest','guest')
connection＝pika.BlockingConnection(
pika.ConnectionParameters(host＝'192.168.1.109',port＝5672,virtual_host＝'/',credentials＝credentials))
return connection
s2, writing a receiver. Py in the normal process of the machine to receive information:
def receive_sth():
print("receive_sth")
connection＝getConnection()
channel＝connection.channel()
channel.exchange_declare(exchange＝exchange_name,exchange_type＝'topic',durable＝False)
channel.queue_declare(queue_name_receivce)
channel.queue_bind(exchange＝exchange_name,queue＝queue_name_receivce,routing_key＝routing_key_receive)
channel.basic_consume(queue＝queue_name_receivce,on_message_callback＝callback,auto_ack＝True)
channel.start_consuming()
s3, calling an execution method of packaging through a cell:
def callback(ch,method,properties,body):
tasksA.runsth.delay(body)
s4, determining the identity according to the parameters transferred by the mq:
def getInventory(self,svc_id,instance_id):
dbhost＝'192.168.1.45'
dbport＝3306
dbname＝'test'
dbuser＝'root'
password＝'root'
conn＝MySQLdb.connect(host＝dbhost,user＝dbuser,passwd＝password,db＝dbname,charset＝'utf8',port＝dbport)
cur＝conn.cursor()
cur.execute("select code from group_component where id＝'"+id+"'")
s5, determining vars according to the parameters transferred by the mq;
s6, performing playbook to install and deploy:
def playbookrun(self,playbook_path):
context._init_global_context(self.ops)
print playbook_path
playbooks_path＝[]
playbooks_path.append(playbook_path)
playbook＝PlaybookExecutor(playbooks＝playbooks_path,
inventory＝self.inventory,variable_manager＝self.variable_manager,
loader＝self.loader,passwords＝self.passwords)
s7, returning a result by rewriting the execution of the callback custom stable:
class ResultCallback(CallbackBase):
def__init__(self,*args,**kwargs):
#super(ResultsCollector,self).__init__(*args,**kwargs)
self.host_ok＝{}
self.host_unreachable＝{}
self.host_failed＝{}
def v2_runner_on_unreachable(self,result):
self.host_unreachable[result._host.get_name()]＝result
def v2_runner_on_ok(self,result,*args,**kwargs):
self.host_ok[result._host.get_name()]＝result
def v2_runner_on_failed(self,result,*args,**kwargs):
self.host_failed[result._host.get_name()]＝result
s8, sending a callback message to the mq:
def send_sth(message):
connection＝getConnection()
channel＝connection.channel()
channel.exchange_declare(exchange＝exchange_name,exchange_type＝'topic',durable＝False)
channel.basic_publish(exchange＝exchange_name,routing_key＝routing_key_send,body＝json.dumps(message))
print("[x]Sent％r:％r"％(routing_key_send,message))
connection.close()
s4, determining the Inventory according to the parameters transferred by the mq, and obtaining the information required in the corresponding allowable according to the parameters in the storage medium, wherein the specific steps comprise:
s401, querying components to be installed:
components＝[]
for row in cur.fetchall():
components.append(row[0])
s402, circulating a component list, and inquiring ip corresponding to each component:
self.inventory.add_group('all')
for v in components:
sql＝"select a.ip from instance_vm_info a,("
sql＝sql+"select code from group_node where component like'％"+v+"％'and id＝'"+id+"'"
sql＝sql+")b where a.instance_id＝'"+instance_id+"'"
sql＝sql+"and a.node_code＝b.code"
cur.execute(sql)
self.inventory.add_group(v)
for row in cur.fetchall():
self.inventory.add_host(row[0],v)
self.inventory.add_host(row[0],'all')
the specific step of determining vars according to the parameters transferred by the mq in S5 comprises the following steps:
s501, acquiring corresponding vars to form extra-vars in a storage medium;
s502 query parameters are passed to the onsible execution use:
cur.execute("select col_code from group_table_column where id＝'"+id+"'")
extra_vars＝{}
cols＝[]
for row in cur.fetchall():
cols.append(row[0])
cur.execute("select`table_name`from group where id＝'"+id+"'")
data＝cur.fetchone()
""
s＝,
cols_str＝s.join(cols)
table_name＝data[0]
sql＝"select"+cols_str+"from"+table_name+"where instance_id＝'"+instance_id+"'"
cur.execute(sql)
data＝cur.fetchone()
no＝0
print json.dumps(data)
for k in cols:
extra_vars[k]＝data[no]
no＝no+1
cur.close()
self.variable_manager._extra_vars＝extra_vars
the S6 executes the playbook and calls an allowable playbook command to execute the already arranged steps for installing the deployment.
A dynamic deployment system based on ANSIBLE specifically comprises a mode determination module, an information receiving module, a task starting module, a parameter determination module A, a parameter determination module B, a deployment installation module, an analysis receipt module and an analysis feedback module:
a mode determining module: determining a rabkitmq configuration;
an information receiving module: writing a receive. Py in the normal process of the machine to receive information;
the task starting module: calling up an execution method through cell packaging;
parameter determination module a: determining an Inventory according to the parameters transferred by the mq;
parameter determination module B: determining vars according to the parameters transferred by the mq;
deploying an installation module: executing a playbook for installation and deployment;
and (5) an analysis receipt module: returning a result by rewriting the execution of the callback custom stable;
and an analysis feedback module: and sending a callback message to the mq.
The parameter determining module A determines the Inventory according to the parameters transferred by the mq, and obtains the information required in the corresponding allowable according to the parameters, wherein the parameter determining module A specifically comprises a component query module and an ip query module:
component query module: querying components to be installed;
ip query module: and circulating the component list, and inquiring the ip corresponding to each component.
The parameter determining module B specifically comprises a parameter combining module and a parameter using module:
parameter combination module: acquiring corresponding vars from a storage medium to form extra-vars;
parameter use module: the query parameters are passed to the allowable execution use.
The deployment installation module executes the playbook and invokes the allowable playbook command to execute the already orchestrated steps for installing the deployment.
The beneficial effects of the invention are as follows: the invention dynamically determines the inventory by combining the mq parameter transmission mode with the database query, reduces the complexity and risk of manual maintenance, and can receive the execution condition in time by rewriting the callback method; the invention also realizes simultaneous multitasking based on celly, and increases the working efficiency.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention; fig. 2 is a schematic diagram of the system of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and specific examples, which are not intended to be limiting, so that those skilled in the art will better understand the invention and practice it.
First, key terms and abbreviations involved in the present invention are explained:
ANSIBLE is a newly-emerging automatic operation and maintenance tool, and based on Python development, realizes functions such as batch system configuration, batch program deployment, batch operation command and the like
Python: programming language
Playbook: minimum execution unit of an ansable
Inventory: host inventory of an onstable
Vars: variable of an ansable
Celery: dynamic parallel framework based on python
Embodiment one:
a dynamic deployment method based on ANSIBLE comprises the following specific steps:
s1, determining a rabkitMQ configuration;
s2, writing a receiver.py in a normal process of the machine to receive information;
s3, calling up an execution method through cell packaging;
s4, determining an Inventory according to the parameters transferred by the mq;
s5, determining vars according to the parameters transferred by the mq;
s6, executing a playbook to perform installation and deployment;
s7, returning a result by rewriting execution of the callback custom stable;
s8, sending a callback message to the mq;
the invention provides a dynamic deployment method based on ANSIBLE, which adopts a rabitMQ as a middleware to realize dynamic parameter transmission, develops based on Python language, adopts an analog plug-in to realize callback, adopts a cell as a concurrence tool, firstly determines the configuration of the rabitMQ according to S1, determines the topic mode of the rabitMQ, determines key information such as routing-key, exchange and the like, and then writes a receive.py file according to S2, wherein the file is used for starting a normal formation in a machine and is used for receiving information sent from various places differently;
based on the self distributed execution function of the cell, calling an execution method through the cell package according to S3, starting a task in a multi-process mode, determining the content according to the parameters transmitted by the mq according to S4, determining vars according to the eucalyptus transmitted by the mq according to S5, and executing the playbook according to S6 for installation and deployment;
the step of rewriting the callbacks according to S7 is mainly to use the execution return result of the custom analysis so as to analyze the callbacks in a highly personalized way and return the execution result to the user, and finally, the analyzed information is returned to the user by sending the callback information to mq according to S8, and the user analyzes the analyzed information according to the custom rule so as to give different feedback to the user;
further, the step S4 of determining the identity according to the parameter transferred by the mq, and obtaining the information required in the corresponding stable from the storage medium according to the parameter, which specifically includes the steps of:
s401, inquiring components to be installed;
s402, circulating a component list, and inquiring an ip corresponding to each component;
s4, determining the Inventory according to the parameters transferred by the mq. According to the transferred parameters, obtaining information such as usernames, passwords, ports, IP, hostnames and the like required in corresponding analog in a certain storage medium, wherein the postgress is used in the invention;
further, the specific step of determining vars according to the parameter transferred by the mq in S5 includes:
s501, acquiring corresponding vars to form extra-vars in a storage medium;
s502, the query parameters are transmitted to an onsible for execution and use;
still further, the S6 executes a playbook, and invokes an allowable playbook command to execute the already-programmed steps for installing the deployment.
Embodiment two:
a dynamic deployment system based on ANSIBLE specifically comprises a mode determination module, an information receiving module, a task starting module, a parameter determination module A, a parameter determination module B, a deployment installation module, an analysis receipt module and an analysis feedback module:
a mode determining module: determining a rabkitmq configuration;
an information receiving module: writing a receive. Py in the normal process of the machine to receive information;
the task starting module: calling up an execution method through cell packaging;
parameter determination module a: determining an Inventory according to the parameters transferred by the mq;
parameter determination module B: determining vars according to the parameters transferred by the mq;
deploying an installation module: executing a playbook for installation and deployment;
and (5) an analysis receipt module: returning a result by rewriting the execution of the callback custom stable;
and an analysis feedback module: sending a callback message to the mq;
the invention provides a dynamic deployment system based on ANSIBLE, which adopts a rabitMQ as a middleware to realize dynamic parameter transmission, develops based on Python language, adopts an analog plug-in to realize callback, adopts a cell as a concurrence tool, firstly determines the configuration of the rabitMQ through a mode determining module, determines the key information such as routing-key, exchange and the like by using the topic mode of the rabitMQ, and then writes a receiving.py file through an information receiving module, wherein the file is used for starting a normal formation in a machine and is used for receiving information sent from various places differently;
based on the self distributed execution function of the cell, a task starting module is used for calling an execution method through cell packaging, a task is started in a multi-process mode, then a parameter determining module A determines the content according to the parameters transmitted by the mq, a parameter determining module B determines vars according to the eucalyptus transmitted by the mq, and a deployment and installation module is used for executing a playbook to carry out installation and deployment;
the step of rewriting the callbacks by the analysis receipt module mainly uses the execution return result of the custom to enable highly personalized analysis and return to the user execution result, and finally sends a callback message to mq through the analysis feedback module, returns the analyzed message to the user, and the user analyzes the analyzed message according to the custom rule to give different feedback to the user;
further, the parameter determining module a determines the identity according to the parameter transferred by the mq, and obtains the information required in the corresponding allowable according to the parameter, where the parameter determining module a specifically includes a component query module and an ip query module:
component query module: querying components to be installed;
ip query module: and circulating the component list, and inquiring the ip corresponding to each component.
Further, the parameter determining module B specifically includes a parameter combining module and a parameter using module:
parameter combination module: acquiring corresponding vars from a storage medium to form extra-vars;
parameter use module: the query parameters are transmitted to an onsible for execution;
still further, the deployment installation module executes a playbook, calls an allowable playbook command to execute the already orchestrated steps for installing the deployment.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (3)
1. A dynamic deployment method based on ANSIBLE is characterized by comprising the following specific steps:
s1, determining a rabkitMQ configuration;
s2, writing a receiver.py in a normal process of the machine to receive information;
s3, calling up an execution method through cell packaging;
s4, determining the Inventory according to the parameters transferred by the mq, further, the S4 determines the Inventory according to the parameters transferred by the mq, and obtaining the information required in the corresponding stable according to the parameters in the storage medium, wherein the specific steps comprise:
s401, inquiring components to be installed;
s402, circulating a component list, and inquiring an ip corresponding to each component;
s4, determining an entry according to the parameters transferred by the mq; according to the transferred parameters, obtaining information such as usernames, passwords, ports, IP, hostnames and the like required in corresponding analog in a certain storage medium, wherein the postgress is used in the invention;
s5, determining vars according to the parameters transferred by the mq, wherein the specific steps of determining vars according to the parameters transferred by the mq in S5 comprise:
s501, acquiring corresponding vars to form extra-vars in a storage medium;
s502, the query parameters are transmitted to an onsible for execution and use;
still further, the S6 executes a playbook, and calls an allowable playbook command to execute the already arranged steps for installing the deployment;
s6, executing a playbook to perform installation and deployment;
s7, returning a result by rewriting execution of the callback custom stable;
s8 sends a callback message to mq.
2. The method of claim 1, wherein S6 executes a playbook, calls an allowable playbook command to execute the already orchestrated steps for installing the deployment.
3. A ANSIBLE-based dynamic deployment system characterized in that said system uses the method of claim 1.
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Citations (3)
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|---|---|---|---|---|
| WO2017202211A1 (en) * | 2016-05-26 | 2017-11-30 | 中兴通讯股份有限公司 | Method and device for installing service version on virtual machine |
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2021
- 2021-01-18 CN CN202110060660.9A patent/CN112711428B/en active Active
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| WO2017202211A1 (en) * | 2016-05-26 | 2017-11-30 | 中兴通讯股份有限公司 | Method and device for installing service version on virtual machine |
| CN109213496A (en) * | 2018-08-29 | 2019-01-15 | 郑州云海信息技术有限公司 | A kind of realization method and system for disposing OpenStack |
| CN110460670A (en) * | 2019-08-19 | 2019-11-15 | 浪潮云信息技术有限公司 | A kind of application cluster framework Automation arranging method based on Terraform and Ansible |
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