# 2. 实施步骤
# 步骤1：优化内核参数
# 步骤2：优化文件系统
# 步骤3：优化网络配置
# 步骤4：验证性能改进

# 3. 应用效果
# 提高了系统的性能
# 减少了系统响应时间
# 提高了系统的可靠性

# 优化内核参数
cat > /etc/sysctl.d/optimization.conf << 'EOF' # 内存优化 vm.swappiness = 10 vm.overcommit_memory = 1 vm.overcommit_ratio = 90 # 网络优化 net.core.somaxconn = 65535 net.ipv4.tcp_max_syn_backlog = 65535 net.ipv4.tcp_fin_timeout = 30 net.ipv4.tcp_keepalive_time = 1200 net.ipv4.tcp_keepalive_probes = 5 net.ipv4.tcp_keepalive_intvl = 15 # 文件系统优化 fs.file-max = 65536 EOF # 应用sysctl配置 sysctl -p /etc/sysctl.d/optimization.conf # 优化文件系统 # 格式化存储设备 mkfs.ext4 -O ^64bit /dev/sdb # 挂载存储设备 mkdir -p /data cat >> /etc/fstab << 'EOF' /dev/sdb /data ext4 defaults,noatime,nodiratime,barrier=0 0 0 EOF mount -a # 优化网络配置 # 配置网络接口 cat > /etc/sysconfig/network-scripts/ifcfg-eth0 << 'EOF' TYPE=Ethernet PROXY_METHOD=none BROWSER_ONLY=no BOOTPROTO=static DEFROUTE=yes IPV4_FAILURE_FATAL=no IPV6INIT=yes IPV6_AUTOCONF=yes IPV6_DEFROUTE=yes IPV6_FAILURE_FATAL=no IPV6_ADDR_GEN_MODE=stable-privacy NAME=eth0 UUID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx DEVICE=eth0 ONBOOT=yes IPADDR=192.168.1.100 NETMASK=255.255.255.0 GATEWAY=192.168.1.1 DNS1=8.8.8.8 DNS2=8.8.4.4 MTU=9000 EOF # 重启网络服务 systemctl restart network # 验证性能改进 # 测试系统响应时间 time dd if=/dev/zero of=/data/test.img bs=1G count=1 oflag=direct # 测试网络性能 iperf3 -s & iperf3 -c localhost -t 60 # 查看系统状态 top vmstat 1 10 iostat -x 1 10

# 2. 实施步骤
# 步骤1：部署Kubernetes集群
# 步骤2：优化容器资源限制
# 步骤3：优化网络配置
# 步骤4：优化存储配置
# 步骤5：验证性能改进

# 3. 应用效果
# 提高了容器的性能
# 减少了容器响应时间
# 提高了系统的可靠性

# 部署Kubernetes集群
kubeadm init –pod-network-cidr=10.244.0.0/16

# 配置kubectl
mkdir -p $HOME/.kube
cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
chown $(id -u):$(id -g) $HOME/.kube/config

# 安装Calico网络插件
kubectl apply -f https://docs.projectcalico.org/manifests/calico.yaml

# 优化容器资源限制
cat > deployment.yaml << 'EOF' apiVersion: apps/v1 kind: Deployment metadata: name: fgedu-app namespace: default spec: replicas: 3 selector: matchLabels: app: fgedu-app template: metadata: labels: app: fgedu-app spec: containers: - name: fgedu-app image: nginx:latest resources: requests: memory: 256Mi cpu: 200m limits: memory: 512Mi cpu: 400m ports: - containerPort: 80 readinessProbe: httpGet: path: / port: 80 initialDelaySeconds: 5 periodSeconds: 10 livenessProbe: httpGet: path: / port: 80 initialDelaySeconds: 15 periodSeconds: 20 EOF kubectl apply -f deployment.yaml # 优化网络配置 # 修改Calico配置 kubectl patch daemonset calico-node -n kube-system --type=merge -p '{"spec":{"template":{"spec":{"containers":[{"name":"calico-node","env":[{"name":"CALICO_MTU","value":"9000"}]}]}}}' # 优化存储配置 # 部署Longhorn kubectl apply -f https://raw.githubusercontent.com/longhorn/longhorn/master/deploy/longhorn.yaml # 创建存储类 cat > storageclass.yaml << 'EOF' apiVersion: storage.k8s.io/v1 kind: StorageClass metadata: name: longhorn provisioner: driver.longhorn.io parameters: numberOfReplicas: "2" staleReplicaTimeout: "30" fromBackup: "" baseImage: "" reclaimPolicy: Delete allowVolumeExpansion: true volumeBindingMode: Immediate EOF kubectl apply -f storageclass.yaml # 验证性能改进 # 测试容器响应时间 kubectl run -i --tty --rm busybox --image=busybox -- sh -c "wget -O - http://fgedu-app.default.svc.cluster.local" # 查看容器状态 kubectl get pods kubectl top pods

# 2. 实施步骤
# 步骤1：部署PostgreSQL
# 步骤2：优化PostgreSQL配置
# 步骤3：优化索引设计
# 步骤4：优化查询语句
# 步骤5：验证性能改进

# 3. 应用效果
# 提高了数据库的性能
# 减少了查询响应时间
# 提高了系统的可靠性

# 部署PostgreSQL
dnf install -y postgresql-server postgresql-contrib
postgresql-setup –initdb
systemctl start postgresql
systemctl enable postgresql

# 优化PostgreSQL配置
cat > /var/lib/pgsql/data/postgresql.conf << 'EOF' # 基本配置 listen_addresses = '*' port = 5432 max_connections = 200 # 内存配置 shared_buffers = 8GB work_mem = 64MB maintenance_work_mem = 2GB # 存储配置 effective_cache_size = 24GB random_page_cost = 1.1 synchronous_commit = on # 写入配置 wal_buffers = 32MB checkpoint_completion_target = 0.9 max_wal_size = 2GB min_wal_size = 1GB # 查询优化 random_page_cost = 1.1 effective_io_concurrency = 200 # 统计信息 autovacuum = on autovacuum_max_workers = 4 autovacuum_naptime = 10min autovacuum_vacuum_scale_factor = 0.05 autovacuum_analyze_scale_factor = 0.025 # 扩展 shared_preload_libraries = 'pg_stat_statements' pg_stat_statements.max = 10000 pg_stat_statements.track = all EOF # 重启PostgreSQL服务 systemctl restart postgresql # 创建测试表和索引 psql -U postgres << 'EOF' -- 创建测试表 CREATE TABLE fgedu_users ( id SERIAL PRIMARY KEY, name VARCHAR(100) NOT NULL, email VARCHAR(255) NOT NULL, age INT, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); -- 创建索引 CREATE INDEX idx_fgedu_users_email ON fgedu_users(email); CREATE INDEX idx_fgedu_users_created_at ON fgedu_users(created_at); -- 插入测试数据 INSERT INTO fgedu_users (name, email, age) SELECT 'User ' || generate_series(1, 1000000), 'user' || generate_series(1, 1000000) || '@fgedu.net.cn', floor(random() * 100)::int FROM generate_series(1, 1000000); -- 分析表 ANALYZE fgedu_users; -- 测试查询性能 EXPLAIN ANALYZE SELECT * FROM fgedu_users WHERE email = 'user500000@fgedu.net.cn'; EXPLAIN ANALYZE SELECT * FROM fgedu_users WHERE created_at > ‘2023-01-01’;
EXPLAIN ANALYZE SELECT age, COUNT(*) FROM fgedu_users GROUP BY age ORDER BY age;
EOF

# 验证性能改进
# 查看查询性能
psql -U postgres -c “SELECT * FROM pg_stat_statements ORDER BY mean_time DESC LIMIT 10;”

# 查看索引使用情况
psql -U postgres -c “SELECT * FROM pg_stat_user_indexes WHERE relname = ‘fgedu_users’;”

# 查看表统计信息
psql -U postgres -c “SELECT * FROM pg_stat_user_tables WHERE relname = ‘fgedu_users’;”

# 2. 实施步骤
# 步骤1：部署Java应用
# 步骤2：优化JVM参数
# 步骤3：优化Tomcat配置
# 步骤4：优化代码
# 步骤5：验证性能改进

# 3. 应用效果
# 提高了应用的性能
# 减少了响应时间
# 提高了系统的可靠性

# 部署Java应用
dnf install -y java-11-openjdk-devel maven

# 构建应用
mvn clean package

# 优化JVM参数
cat > /etc/systemd/system/myapp.service << 'EOF' [Unit] Description=My Spring Boot Application After=network.target [Service] Type=simple User=myapp ExecStart=/usr/bin/java -Xms4G -Xmx8G -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:ParallelGCThreads=8 -XX:ConcGCThreads=2 -XX:InitiatingHeapOccupancyPercent=70 -jar /opt/myapp/myapp.jar Restart=on-failure [Install] WantedBy=multi-user.target EOF # 启动应用服务 systemctl daemon-reload systemctl start myapp systemctl enable myapp # 优化Tomcat配置（如果使用Tomcat） cat > /etc/tomcat/server.xml << 'EOF'

EOF

# 重启Tomcat服务
systemctl restart tomcat

# 验证性能改进
# 测试响应时间
ab -n 1000 -c 100 http://localhost:8080/myapp/

# 查看JVM状态
jstat -gc $(pgrep -f myapp.jar) 1000 10

# 查看应用日志
tail -f /var/log/myapp.log