# 部署应用性能分析工具
$ helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
$ helm repo update
$ helm install prometheus prometheus-community/kube-prometheus-stack –namespace monitoring –create-namespace

# 部署应用性能分析工具
$ helm install grafana grafana/grafana –namespace monitoring –set service.type=LoadBalancer

# 部署应用性能分析工具
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: application-insights namespace: monitoring spec: replicas: 1 selector: matchLabels: app: application-insights template: metadata: labels: app: application-insights spec: containers: - name: application-insights image: microsoft/applicationinsights-agent:latest ports: - containerPort: 8080 env: - name: APPLICATIONINSIGHTS_CONNECTION_STRING value: "InstrumentationKey=your-instrumentation-key" EOF

执行输出：

NAME: prometheus
LAST DEPLOYED: Wed Apr 3 12:00:00 2026
NAMESPACE: monitoring
STATUS: deployed
REVISION: 1
TEST SUITE: None

NAME: grafana
LAST DEPLOYED: Wed Apr 3 12:05:00 2026
NAMESPACE: monitoring
STATUS: deployed
REVISION: 1
TEST SUITE: None

deployment.apps/application-insights created

# 优化应用资源配置
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: webapp namespace: default spec: replicas: 3 selector: matchLabels: app: webapp template: metadata: labels: app: webapp spec: containers: - name: webapp image: nginx:latest resources: requests: cpu: "500m" memory: "512Mi" limits: cpu: "1000m" memory: "1Gi" ports: - containerPort: 80 EOF # 配置HPA $ kubectl autoscale deployment webapp --cpu-percent=50 --min=3 --max=10 # 优化应用配置 $ kubectl apply -f - << EOF apiVersion: v1 kind: ConfigMap metadata: name: webapp-config namespace: default data: nginx.conf: | events { worker_connections 1024; } http { keepalive_timeout 65; gzip on; server { listen 80; location / { root /usr/share/nginx/html; index index.html; } } } EOF $ kubectl patch deployment webapp -n default --type=merge -p '{"spec":{"template":{"spec":{"volumes":[{"name":"config","configMap":{"name":"webapp-config"}}],"containers":[{"name":"webapp","volumeMounts":[{"name":"config","mountPath":"/etc/nginx/nginx.conf","subPath":"nginx.conf"}]}]}}}'

执行输出：

deployment.apps/webapp created
horizontalpodautoscaler.autoscaling/webapp created
configmap/webapp-config created
deployment.apps/webapp patched

# 部署应用性能监控
$ helm install application-monitoring prometheus-community/prometheus –namespace monitoring –set alertmanager.enabled=true –set pushgateway.enabled=true

# 配置应用性能告警
$ kubectl apply -f – << EOF apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: name: application-alerts namespace: monitoring spec: groups: - name: application rules: - alert: HighResponseTime expr: avg_over_time(http_request_duration_seconds[5m]) > 1
for: 5m
labels:
severity: warning
annotations:
summary: “高响应时间”
description: “应用响应时间超过1秒”
– alert: HighErrorRate
expr: rate(http_requests_total{status=~”5..”}[5m]) / rate(http_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: “高错误率”
description: “应用错误率超过5%”
EOF

# 部署应用性能可视化
$ helm install application-dashboard grafana/grafana –namespace monitoring –set service.type=LoadBalancer –set dashboardProviders.file.dashboards.application-dashboard.enabled=true

执行输出：

NAME: application-monitoring
LAST DEPLOYED: Wed Apr 3 12:30:00 2026
NAMESPACE: monitoring
STATUS: deployed
REVISION: 1
TEST SUITE: None

prometheusrule.monitoring.coreos.com/application-alerts created

NAME: application-dashboard
LAST DEPLOYED: Wed Apr 3 12:35:00 2026
NAMESPACE: monitoring
STATUS: deployed
REVISION: 1
TEST SUITE: None

# 1. 分析应用性能
$ kubectl top pods -n e-commerce
$ kubectl logs -n e-commerce deployment/webapp | grep -i error

# 2. 优化应用配置
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: webapp namespace: e-commerce spec: replicas: 5 selector: matchLabels: app: webapp template: metadata: labels: app: webapp spec: containers: - name: webapp image: nginx:latest resources: requests: cpu: "1" memory: "1Gi" limits: cpu: "2" memory: "2Gi" ports: - containerPort: 80 readinessProbe: httpGet: path: /health port: 80 initialDelaySeconds: 5 periodSeconds: 10 livenessProbe: httpGet: path: /health port: 80 initialDelaySeconds: 15 periodSeconds: 20 EOF # 3.学习交流加群风哥微信: itpux-com 配置缓存 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: redis namespace: e-commerce spec: replicas: 1 selector: matchLabels: app: redis template: metadata: labels: app: redis spec: containers: - name: redis image: redis:latest ports: - containerPort: 6379 resources: requests: cpu: "500m" memory: "1Gi" limits: cpu: "1" memory: "2Gi" --- apiVersion: v1 kind: Service metadata: name: redis namespace: e-commerce spec: selector: app: redis ports: - port: 6379 targetPort: 6379 EOF # 4. 测试应用性能 $ kubectl run load-test --rm -i --tty --image=locustio/locust -- locust -f /locustfile.py --host=http://webapp.e-commerce.svc.cluster.local

执行输出：

NAME CPU(cores) MEMORY(bytes)
webapp-567890abc-12345 500m 512Mi
webapp-567890abc-67890 450m 480Mi
webapp-567890abc-abcde 520m 530Mi

2026-04-03 12:40:00.000 [INFO] Starting load test
2026-04-03 12:40:05.000 [INFO] Users: 100, RPS: 1000, Average response time: 50ms
2026-04-03 12:40:10.000 [INFO] Users: 500, RPS: 5000, Average response time: 80ms
2026-04-03 12:40:15.000 [INFO] Users: 1000, RPS: 10000, Average response time: 120ms

# 1. 分析数据库性能
$ kubectl top pods -n finance
$ kubectl exec -n finance deployment/mysql — mysql -u root -p -e “SHOW GLOBAL STATUS LIKE ‘Slow_queries’;”

# 2. 优化数据库配置
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: mysql namespace: finance spec: replicas: 1 selector: matchLabels: app: mysql template: metadata: labels: app: mysql spec: containers: - name: mysql image: mysql:8.0 env: - name: MYSQL_ROOT_PASSWORD value: "password" - name: MYSQL_DATABASE value: "fgedudb" resources: requests: cpu: "2" memory: "4Gi" limits: cpu: "4" memory: "8Gi" ports: - containerPort: 3306 volumeMounts: - name: mysql-config mountPath: /etc/mysql/conf.d - name: mysql-data mountPath: /var/lib/mysql volumes: - name: mysql-config configMap: name: mysql-config - name: mysql-data persistentVolumeClaim: claimName: mysql-pvc --- apiVersion: v1 kind: ConfigMap metadata: name: mysql-config namespace: finance data: my.cnf: | [mysqld] innodb_buffer_pool_size = 4G innodb_log_file_size = 1G innodb_flush_log_at_trx_commit = 2 innodb_file_per_table = 1 max_connections = 1000 query_cache_type = 0 query_cache_size = 0 slow_query_log = 1 slow_query_log_file = /var/lib/mysql/slow-query.log long_query_time = 1 EOF # 3. 配置数据库索引 $ kubectl exec -n finance deployment/mysql -- mysql -u root -p -e "USE fgedudb; CREATE INDEX idx_user_id ON fgedu_users(user_id);" # 4. 测试数据库性能 $ kubectl run mysql-bench --rm -i --tty --image=percona/percona-toolkit -- pt-query-digest /var/更多学习教程公众号风哥教程itpux_comlib/mysql/slow-query.log

执行输出：

from PG视频:www.itpux.com

NAME CPU(cores) MEMORY(bytes)
mysql-567890abc-12345 1500m 3500Mi

+———————+———-+———-+———-+———-+———-+———-+———-+———-+———-+
| Host | # Queries | QPS | Slow | % Slow | Errors | Warnings | Bytes | Bytes | Duration |
+———————+———-+———-+———-+———-+———-+———-+———-+———-+———-+
| 10.244.1.10:54321 | 10000 | 1000 | 10 | 0.10% | 0 | 0 | 10.00 MB | 1.00 KB | 10.00 s |
+———————+———-+———-+———-+———-+———-+———-+———-+———-+———-+

Query ID: 1234567890
Time range: 2026-04-03 12:50:00 to 2026-04-03 12:55:00
Unique SQL: SELECT * FROM fgedu_users WHERE user_id = ?
Count: 1000, Exec time: 1.00 s, Lock time: 0.00 s, Rows sent: 1, Rows examine: 1000

# 索引创建成功
Query OK, 0 rows affected (0.10 sec)

# 性能测试结果
# Average query time: 0.更多视频教程www.fgedu.net.cn10ms
# 95th percentile: 0.50ms
# 99th percentile: 1.00ms

# 1. 分析微服务性能
$ kubectl top pods -n microservices
$ kubectl logs -n microservices deployment/api-gateway | grep -i error

# 2. 优化微服务配置
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: api-gateway namespace: microservices spec: replicas: 3 selector: matchLabels: app: api-gateway template: metadata: labels: app: api-gateway spec: containers: - name: api-gateway image: nginx:latest resources: requests: cpu: "1" memory: "1Gi" limits: cpu: "2" memory: "2Gi" ports: - containerPort: 80 readinessProbe: httpGet: path: /health port: 80 initialDelaySeconds: 5 periodSeconds: 10 livenessProbe: httpGet: path: /health port: 80 initialDelaySeconds: 15 periodSeconds: 20 --- apiVersion: apps/v1 kind: Deployment metadata: name: user-service namespace: microservices spec: replicas: 2 selector: matchLabels: app: user-service template: metadata: labels: app: user-service spec: containers: - name: user-service image: node:latest resources: requests: cpu: "500m" memory: "512Mi" limits: cpu: "1" memory: "1Gi" ports: - containerPort: 3000 EOF # 3. 配置服务网格 $ helm repo add istio https://istio-release.storage.googleapis.com/charts $ helm install istio-base istio/base --namespace istio-system --create-namespace $ helm install istiod istio/istiod --namespace istio-system --set meshConfig.accessLogFile=/dev/stdout # 4. 测试微服务性能 $ kubectl run load-test --rm -i --tty --image=locustio/locust -- locust -f /locustfile.py --host=http://api-gateway.microservices.svc.cluster.local

执行输出：

NAME CPU(cores) MEMORY(bytes)
api-gateway-567890abc-12345 800m 900Mi
api-gateway-567890abc-67890 750m 850Mi
api-gateway-567890abc-abcde 820m 920Mi
user-service-567890abc-12345 450m 480Mi
user-service-567890abc-67890 420m 450Mi

NAME: istio-base
LAST DEPLOYED: Wed Apr 3 13:00:00 2026
NAMESPACE: istio-system
STATUS: deployed
REVISION: 1
TEST SUITE: None

NAME: istiod
LAST DEPLOYED: Wed Apr 3 13:05:00 2026
NAMESPACE: istio-system
STATUS: deployed
REVISION: 1
TEST SUITE: None

2026-04-03 13:10:00.000 [INFO] Starting load test
2026-04-03 13:10:05.000 [INFO] Users: 100, RPS: 500, Average response time: 30ms
2026-04-03 13:10:10.000 [INFO] Users: 500, RPS: 2500, Average response time: 50ms
2026-04-03 13:10:15.000 [INFO] Users: 1000, RPS: 5000, Average response time: 80ms