应用发布系统实践面试题

一、系统架构设计相关问题

1. 问：如何设计一个高可用的Flask应用发布系统的架构？

答：一个生产级别的应用发布系统架构应包含以下组件：

1. 架构组成：

Client -> Nginx -> Flask App Cluster -> Redis/MySQL -> Jenkins -> K8s API
                                    -> Celery Workers
                                    -> RabbitMQ

1. 具体实现：

# config.py
class Config:
    # 数据库配置
    SQLALCHEMY_DATABASE_URI = 'mysql+pymysql://user:pass@localhost/deploy_sys'
    
    # Redis配置
    REDIS_URL = 'redis://localhost:6379/0'
    
    # Celery配置
    CELERY_BROKER_URL = 'amqp://localhost:5672'
    CELERY_RESULT_BACKEND = 'redis://localhost:6379/1'
    
    # Jenkins配置
    JENKINS_URL = 'http://jenkins.example.com'
    JENKINS_USER = 'admin'
    JENKINS_TOKEN = 'your-token'
    
    # K8s配置
    KUBERNETES_CONFIG = '/path/to/kubeconfig'

# app/__init__.py
from flask import Flask
from celery import Celery
from kubernetes import client, config
import jenkins

def create_app(config_class=Config):
    app = Flask(__name__)
    app.config.from_object(config_class)
    
    # 初始化扩展
    db.init_app(app)
    cache.init_app(app)
    
    # 初始化Celery
    celery = make_celery(app)
    
    # 初始化K8s客户端
    config.load_kube_config(app.config['KUBERNETES_CONFIG'])
    
    # 注册蓝图
    from app.api import bp as api_bp
    app.register_blueprint(api_bp, url_prefix='/api')
    
    return app

1. 高可用保证：

• 使用Gunicorn多进程部署

• Redis主从复制

• MySQL主从复制

• RabbitMQ集群

• 应用多副本部署在K8s中

2. 问：如何处理并发部署请求？如何避免同一个项目被重复发布？

答：这需要考虑分布式锁和任务队列的实现：

from flask import current_app
from redis import Redis
from functools import wraps

class DistributedLock:
    def __init__(self, lock_name, expire=60):
        self.redis_client = Redis.from_url(current_app.config['REDIS_URL'])
        self.lock_name = f"deploy_lock:{lock_name}"
        self.expire = expire
    
    def acquire(self):
        return self.redis_client.set(
            self.lock_name, 1, ex=self.expire, nx=True
        )
    
    def release(self):
        self.redis_client.delete(self.lock_name)
    
    def __enter__(self):
        self.acquire()
        return self
    
    def __exit__(self, exc_type, exc_val, exc_tb):
        self.release()

def require_deploy_lock(f):
    @wraps(f)
    def decorated_function(*args, **kwargs):
        project_name = kwargs.get('project_name')
        with DistributedLock(project_name) as lock:
            if not lock:
                return {'error': 'Project is being deployed'}, 409
            return f(*args, **kwargs)
    return decorated_function

@api_bp.route('/deploy/<project_name>', methods=['POST'])
@require_deploy_lock
def deploy_project(project_name):
    # 处理部署请求
    task = celery.send_task('tasks.deploy', args=[project_name])
    return {'task_id': task.id}, 202

二、数据模型设计相关问题

3. 问：如何设计应用发布系统的数据模型？需要考虑哪些关键字段？

答：数据模型设计需要考虑项目信息、发布记录、审批流程等：

from datetime import datetime
from app import db

class Project(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    name = db.Column(db.String(64), unique=True, index=True)
    git_repo = db.Column(db.String(256))
    owner = db.Column(db.String(64))
    team = db.Column(db.String(64))
    created_at = db.Column(db.DateTime, default=datetime.utcnow)
    deployments = db.relationship('Deployment', backref='project', lazy='dynamic')

class Deployment(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    project_id = db.Column(db.Integer, db.ForeignKey('project.id'))
    version = db.Column(db.String(64))
    environment = db.Column(db.String(32))
    status = db.Column(db.String(32))
    started_at = db.Column(db.DateTime, default=datetime.utcnow)
    finished_at = db.Column(db.DateTime)
    deployed_by = db.Column(db.String(64))
    
    def to_dict(self):
        return {
            'id': self.id,
            'project': self.project.name,
            'version': self.version,
            'environment': self.environment,
            'status': self.status,
            'started_at': self.started_at.isoformat(),
            'finished_at': self.finished_at.isoformat() if self.finished_at else None,
            'deployed_by': self.deployed_by
        }

三、Jenkins Pipeline集成相关问题

4. 问：如何动态生成和触发Jenkins Pipeline？如何处理Pipeline执行结果？

答：需要实现Jenkins API的集成和Pipeline模板的管理：

import jenkins
from jinja2 import Template

class JenkinsClient:
    def __init__(self, url, username, token):
        self.server = jenkins.Jenkins(url, username=username, password=token)
    
    def create_pipeline_job(self, project_name, pipeline_script):
        """创建Pipeline任务"""
        config_xml = self._generate_pipeline_config(pipeline_script)
        
        if not self.server.job_exists(project_name):
            self.server.create_job(project_name, config_xml)
        else:
            self.server.reconfig_job(project_name, config_xml)
    
    def _generate_pipeline_config(self, pipeline_script):
        template = """
        <?xml version='1.1' encoding='UTF-8'?>
        <flow-definition plugin="workflow-job">
          <definition class="org.jenkinsci.plugins.workflow.cps.CpsFlowDefinition">
            <script>{{pipeline_script}}</script>
            <sandbox>true</sandbox>
          </definition>
        </flow-definition>
        """
        return Template(template).render(pipeline_script=pipeline_script)
    
    def build_job(self, project_name, parameters=None):
        """触发构建"""
        if parameters:
            return self.server.build_job(project_name, parameters=parameters)
        return self.server.build_job(project_name)
    
    def get_build_info(self, project_name, build_number):
        """获取构建信息"""
        return self.server.get_build_info(project_name, build_number)

@celery.task
def handle_jenkins_build(project_name, build_number):
    """处理Jenkins构建结果"""
    jenkins_client = JenkinsClient(
        current_app.config['JENKINS_URL'],
        current_app.config['JENKINS_USER'],
        current_app.config['JENKINS_TOKEN']
    )
    
    build_info = jenkins_client.get_build_info(project_name, build_number)
    
    if build_info['result'] == 'SUCCESS':
        # 更新部署状态
        deployment = Deployment.query.filter_by(
            project_name=project_name,
            status='BUILDING'
        ).first()
        
        if deployment:
            deployment.status = 'SUCCESS'
            deployment.finished_at = datetime.utcnow()
            db.session.commit()
            
            # 触发K8s部署
            deploy_to_kubernetes.delay(project_name, deployment.id)

四、Kubernetes部署相关问题

5. 问：如何实现安全可靠的Kubernetes部署？如何处理滚动更新和回滚？

答：需要实现K8s API的封装和部署策略的管理：

from kubernetes import client, config
from kubernetes.client.rest import ApiException

class KubernetesDeployer:
    def __init__(self, kubeconfig_path):
        config.load_kube_config(kubeconfig_path)
        self.apps_v1 = client.AppsV1Api()
        self.core_v1 = client.CoreV1Api()
    
    def deploy(self, namespace, deployment_name, container_image, replicas=3):
        try:
            # 准备deployment对象
            deployment = {
                'apiVersion': 'apps/v1',
                'kind': 'Deployment',
                'metadata': {
                    'name': deployment_name,
                    'namespace': namespace
                },
                'spec': {
                    'replicas': replicas,
                    'selector': {
                        'matchLabels': {
                            'app': deployment_name
                        }
                    },
                    'template': {
                        'metadata': {
                            'labels': {
                                'app': deployment_name
                            }
                        },
                        'spec': {
                            'containers': [{
                                'name': deployment_name,
                                'image': container_image,
                                'imagePullPolicy': 'Always',
                                'resources': {
                                    'requests': {
                                        'memory': "64Mi",
                                        'cpu': "250m"
                                    },
                                    'limits': {
                                        'memory': "128Mi",
                                        'cpu': "500m"
                                    }
                                },
                                'readinessProbe': {
                                    'httpGet': {
                                        'path': '/health',
                                        'port': 80
                                    },
                                    'initialDelaySeconds': 5,
                                    'periodSeconds': 10
                                }
                            }]
                        }
                    }
                }
            }
            
            # 执行部署
            self.apps_v1.create_namespaced_deployment(
                namespace=namespace,
                body=deployment
            )
            
            # 等待部署完成
            self._wait_for_deployment(namespace, deployment_name)
            
            return True
            
        except ApiException as e:
            current_app.logger.error(f"Exception when calling Kubernetes API: {e}")
            return False
    
    def _wait_for_deployment(self, namespace, deployment_name, timeout=300):
        """等待部署完成"""
        start_time = time.time()
        
        while time.time() - start_time < timeout:
            response = self.apps_v1.read_namespaced_deployment_status(
                name=deployment_name,
                namespace=namespace
            )
            
            if (response.status.available_replicas == response.status.replicas and
                response.status.replicas == response.status.ready_replicas):
                return True
                
            time.sleep(10)
            
        raise TimeoutError("Deployment did not complete within timeout")
    
    def rollback(self, namespace, deployment_name):
        """执行回滚"""
        try:
            # 获取部署历史
            deployment = self.apps_v1.read_namespaced_deployment(
                name=deployment_name,
                namespace=namespace
            )
            
            # 回滚到上一个版本
            deployment.spec.template.spec.containers[0].image = (
                deployment.spec.template.spec.containers[0].image.split(':')[0] +
                ':previous'
            )
            
            self.apps_v1.patch_namespaced_deployment(
                name=deployment_name,
                namespace=namespace,
                body=deployment
            )
            
            return True
            
        except ApiException as e:
            current_app.logger.error(f"Exception when rolling back: {e}")
            return False

五、监控和日志相关问题

6. 问：如何实现应用发布过程的监控和日志收集？

答：需要实现完整的监控和日志系统：

from elasticsearch import Elasticsearch
from prometheus_client import Counter, Histogram
import structlog

# Prometheus metrics
deployment_counter = Counter(
    'deployment_total',
    'Total number of deployments',
    ['project', 'environment', 'status']
)

deployment_duration = Histogram(
    'deployment_duration_seconds',
    'Time spent in deployment',
    ['project', 'environment']
)

# 结构化日志
logger = structlog.get_logger()

class DeploymentMonitor:
    def __init__(self, elasticsearch_url):
        self.es = Elasticsearch([elasticsearch_url])
    
    def record_deployment(self, deployment_data):
        """记录部署信息"""
        # 更新Prometheus指标
        deployment_counter.labels(
            project=deployment_data['project'],
            environment=deployment_data['environment'],
            status=deployment_data['status']
        ).inc()
        
        # 记录结构化日志
        logger.info(
            "deployment_completed",
            project=deployment_data['project'],
            environment=deployment_data['environment'],
            status=deployment_data['status'],
            duration=deployment_data['duration']
        )
        
        # 存储到Elasticsearch
        self.es.index(
            index="deployments",
            document=deployment_data
        )
    
    def get_deployment_stats(self, project_name, time_range):
        """获取部署统计信息"""
        query = {
            "query": {
                "bool": {
                    "must": [
                        {"match": {"project": project_name}},
                        {"range": {"timestamp": {"gte": time_range}}}
                    ]
                }
            },
            "aggs": {
                "status_stats": {
                    "terms": {"field": "status"}
                },
                "avg_duration": {
                    "avg": {"field": "duration"}
                }
            }
        }
        
        return self.es.search(index="deployments", body=query)

@celery.task
def monitor_deployment(deployment_id):
    """监控部署任务"""
    with deployment_duration.labels(
        project=deployment.project,
        environment=deployment.environment
    ).