第216集Kibana可视化分析平台架构实战:日志分析、监控告警、数据可视化的企业级解决方案
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第216集Kibana可视化分析平台架构实战:日志分析、监控告警、数据可视化的企业级解决方案
前言
在当今数据驱动的企业环境中,如何高效地分析海量日志数据、实现实时监控告警、构建直观的数据可视化界面,已成为企业数字化转型的关键挑战。Kibana作为Elastic Stack的核心组件,为企业提供了强大的数据可视化和分析能力。
本文将深入探讨Kibana可视化分析平台的架构设计与实战应用,从基础搭建到高级优化,从日志分析到监控告警,为企业构建完整的数据分析解决方案提供全面的技术指导。
一、Kibana架构概述与核心特性
1.1 Kibana架构设计
Kibana采用现代化的Web架构设计,基于Node.js构建,提供丰富的可视化组件和强大的查询分析能力。
1.2 核心功能特性
1.2.1 数据发现与分析
- Discover模块:提供强大的数据搜索和过滤能力
- 实时数据流:支持实时数据流分析和历史数据回溯
- 字段统计:自动生成字段统计信息和数据分布
1.2.2 可视化组件
- 图表类型:支持柱状图、折线图、饼图、热力图等多种图表
- 地图可视化:集成地理信息数据,支持地图展示
- 时间序列:专门的时间序列数据可视化组件
1.2.3 仪表板管理
- Dashboard构建:拖拽式仪表板构建工具
- 实时刷新:支持实时数据刷新和自动更新
- 权限控制:细粒度的权限管理和访问控制
1.3 企业级架构优势
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| 架构优势: 高可用性: - 多节点部署 - 负载均衡 - 故障转移 可扩展性: - 水平扩展 - 集群管理 - 资源弹性 安全性: - 身份认证 - 权限控制 - 数据加密 性能优化: - 缓存机制 - 查询优化 - 资源管理
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二、Kibana环境搭建与配置
2.1 系统环境准备
2.1.1 硬件配置要求
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| CPU: 8核心以上 内存: 16GB以上 存储: SSD 500GB以上 网络: 千兆网卡
CPU: 4核心 内存: 8GB 存储: SSD 100GB 网络: 百兆网卡
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2.1.2 软件环境依赖
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| cat /etc/os-release
sudo apt update sudo apt install openjdk-11-jdk
java -version
echo 'export JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64' >> ~/.bashrc source ~/.bashrc
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2.2 Elasticsearch集群部署
2.2.1 Elasticsearch安装配置
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| wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo apt-key add - echo "deb https://artifacts.elastic.co/packages/8.x/apt stable main" | sudo tee /etc/apt/sources.list.d/elastic-8.x.list
sudo apt update sudo apt install elasticsearch
sudo vim /etc/elasticsearch/elasticsearch.yml
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2.2.2 Elasticsearch集群配置
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| cluster.name: production-cluster node.name: node-1 node.roles: [master, data, ingest]
network.host: 0.0.0.0 http.port: 9200 transport.port: 9300
discovery.seed_hosts: ["node1:9300", "node2:9300", "node3:9300"] cluster.initial_master_nodes: ["node-1", "node-2", "node-3"]
xpack.security.enabled: true xpack.security.transport.ssl.enabled: true xpack.security.transport.ssl.verification_mode: certificate xpack.security.transport.ssl.key: /etc/elasticsearch/certs/node-1.key xpack.security.transport.ssl.certificate: /etc/elasticsearch/certs/node-1.crt xpack.security.transport.ssl.certificate_authorities: /etc/elasticsearch/certs/ca.crt
indices.memory.index_buffer_size: 30% indices.queries.cache.size: 10% indices.fielddata.cache.size: 20%
cluster.routing.allocation.disk.threshold.enabled: true cluster.routing.allocation.disk.watermark.low: 85% cluster.routing.allocation.disk.watermark.high: 90% cluster.routing.allocation.disk.watermark.flood_stage: 95%
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2.2.3 JVM参数优化
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-Xms8g -Xmx8g
-XX:+UseG1GC -XX:G1HeapRegionSize=16m -XX:+UseStringDeduplication
-XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap -XX:MaxDirectMemorySize=2g
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2.3 Kibana安装与配置
2.3.1 Kibana安装
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| sudo apt install kibana
sudo systemctl start kibana sudo systemctl enable kibana
sudo systemctl status kibana
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2.3.2 Kibana基础配置
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| server.name: "kibana-server" server.host: "0.0.0.0" server.port: 5601
elasticsearch.hosts: ["https://node1:9200", "https://node2:9200", "https://node3:9200"] elasticsearch.username: "kibana_system" elasticsearch.password: "your_password"
elasticsearch.ssl.certificateAuthorities: ["/etc/kibana/certs/ca.crt"] elasticsearch.ssl.verificationMode: certificate
xpack.security.enabled: true xpack.encryptedSavedObjects.encryptionKey: "your_encryption_key"
server.maxPayloadBytes: 1048576 elasticsearch.requestTimeout: 30000 elasticsearch.shardTimeout: 30000
logging.appenders.file.type: file logging.appenders.file.fileName: /var/log/kibana/kibana.log logging.appenders.file.layout.type: json logging.root.level: info
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2.3.3 Kibana集群配置
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| server.name: "kibana-node-1" server.host: "0.0.0.0" server.port: 5601
elasticsearch.hosts: ["https://elasticsearch-lb:9200"]
kibana.index: ".kibana" kibana.defaultAppId: "home"
optimize.bundleFilter: "!tests" optimize.useBundleCache: true optimize.bundleDir: "/var/lib/kibana/optimize/bundles"
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2.4 安全配置与认证
2.4.1 内置用户管理
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| sudo /usr/share/elasticsearch/bin/elasticsearch-reset-password -u elastic sudo /usr/share/elasticsearch/bin/elasticsearch-reset-password -u kibana_system sudo /usr/share/elasticsearch/bin/elasticsearch-reset-password -u logstash_system
curl -X POST "localhost:9200/_security/user/kibana_admin" \ -H 'Content-Type: application/json' \ -u elastic:your_password \ -d '{ "password": "admin_password", "roles": ["kibana_admin", "superuser"], "full_name": "Kibana Administrator", "email": "admin@company.com" }'
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2.4.2 LDAP集成配置
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| xpack.security.authc.realms.ldap.ldap1: order: 2 url: "ldaps://ldap.company.com:636" bind_dn: "cn=admin,dc=company,dc=com" bind_password: "ldap_password" user_search.base_dn: "ou=users,dc=company,dc=com" user_search.attribute: "uid" group_search.base_dn: "ou=groups,dc=company,dc=com" group_search.attribute: "cn" group_search.user_attribute: "uid"
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2.4.3 SSL证书配置
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| sudo /usr/share/elasticsearch/bin/elasticsearch-certutil ca
sudo /usr/share/elasticsearch/bin/elasticsearch-certutil cert --ca elastic-stack-ca.p12
sudo /usr/share/elasticsearch/bin/elasticsearch-certutil http
sudo chown -R elasticsearch:elasticsearch /etc/elasticsearch/certs/ sudo chmod 600 /etc/elasticsearch/certs/*
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三、Kibana核心功能模块详解
3.1 Discover数据发现模块
3.1.1 数据搜索与过滤
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| { "query": { "bool": { "must": [ { "match": { "message": "error" } }, { "range": { "@timestamp": { "gte": "now-1h", "lte": "now" } } } ], "filter": [ { "term": { "level": "ERROR" } } ] } } }
{ "query": { "bool": { "should": [ { "wildcard": { "message": "*timeout*" } }, { "regexp": { "message": ".*(error|exception|fail).*" } } ], "minimum_should_match": 1 } }, "sort": [ { "@timestamp": { "order": "desc" } } ], "size": 100 }
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3.1.2 字段分析与统计
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| { "aggs": { "field_stats": { "stats": { "field": "response_time" } }, "top_values": { "terms": { "field": "status_code", "size": 10 } }, "date_histogram": { "date_histogram": { "field": "@timestamp", "calendar_interval": "1h" } } } }
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3.2 Visualize可视化模块
3.2.1 基础图表类型
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| { "aggs": { "2": { "terms": { "field": "status_code", "order": { "_count": "desc" }, "size": 10 } } } }
{ "aggs": { "2": { "date_histogram": { "field": "@timestamp", "calendar_interval": "1h", "time_zone": "UTC", "min_doc_count": 1 }, "aggs": { "3": { "avg": { "field": "response_time" } } } } } }
{ "aggs": { "2": { "terms": { "field": "service_name", "order": { "_count": "desc" }, "size": 5 } } } }
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3.2.2 高级可视化组件
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| { "aggs": { "2": { "date_histogram": { "field": "@timestamp", "calendar_interval": "1h", "time_zone": "UTC", "min_doc_count": 1 }, "aggs": { "3": { "terms": { "field": "status_code", "size": 10 } } } } } }
{ "aggs": { "2": { "geohash_grid": { "field": "location", "precision": 3 } } } }
{ "aggs": { "2": { "terms": { "field": "service_name", "order": { "_count": "desc" }, "size": 20 }, "aggs": { "3": { "avg": { "field": "response_time" } }, "4": { "max": { "field": "response_time" } } } } } }
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3.3 Dashboard仪表板模块
3.3.1 仪表板构建
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| { "version": "8.0.0", "kibana": { "version": "8.0.0" }, "dashboard": { "title": "系统监控仪表板", "description": "实时系统性能监控", "panelsJSON": "[{\"version\":\"8.0.0\",\"type\":\"visualization\",\"gridData\":{\"x\":0,\"y\":0,\"w\":12,\"h\":8,\"i\":\"1\"},\"panelIndex\":\"1\",\"embeddableConfig\":{\"savedVis\":{\"title\":\"错误日志统计\",\"type\":\"histogram\"}}},{\"version\":\"8.0.0\",\"type\":\"visualization\",\"gridData\":{\"x\":12,\"y\":0,\"w\":12,\"h\":8,\"i\":\"2\"},\"panelIndex\":\"2\",\"embeddableConfig\":{\"savedVis\":{\"title\":\"响应时间趋势\",\"type\":\"line\"}}}]", "optionsJSON": "{\"darkTheme\":false,\"useMargins\":true,\"syncColors\":false,\"hidePanelTitles\":false}", "timeRestore": true, "timeTo": "now", "timeFrom": "now-1h" } }
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3.3.2 实时数据刷新
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| { "refreshInterval": { "pause": false, "value": 5000 }, "time": { "from": "now-1h", "to": "now" } }
{ "refreshInterval": { "pause": false, "value": 10000 }, "autoRefresh": { "enabled": true, "interval": 30000 } }
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3.4.1 查询调试
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| GET /_cat/indices?v
GET /_cluster/health?pretty
GET /_nodes/stats?pretty
GET /_index_template?pretty
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3.4.2 数据操作
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| PUT /logs-2024-12-19 { "settings": { "number_of_shards": 3, "number_of_replicas": 1, "index": { "refresh_interval": "5s" } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "message": { "type": "text", "analyzer": "standard" }, "level": { "type": "keyword" }, "service": { "type": "keyword" } } } }
POST /logs-2024-12-19/_bulk {"index":{}} {"@timestamp":"2024-12-19T10:00:00Z","message":"Application started","level":"INFO","service":"web-app"} {"index":{}} {"@timestamp":"2024-12-19T10:01:00Z","message":"Database connection established","level":"INFO","service":"web-app"} {"index":{}} {"@timestamp":"2024-12-19T10:02:00Z","message":"User login successful","level":"INFO","service":"auth-service"}
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四、日志分析实战应用
4.1 应用日志分析
4.1.1 日志格式标准化
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| input { file { path => "/var/log/app/*.log" start_position => "beginning" codec => "json" } }
filter { date { match => [ "timestamp", "ISO8601" ] } grok { match => { "message" => "%{TIMESTAMP_ISO8601:log_time} \[%{DATA:thread}\] %{LOGLEVEL:level} %{DATA:logger} - %{GREEDYDATA:log_message}" } } if [level] == "ERROR" { multiline { pattern => "^\s+at\s+" what => "previous" } } mutate { remove_field => ["host", "path"] rename => { "log_message" => "message" } } }
output { elasticsearch { hosts => ["localhost:9200"] index => "app-logs-%{+YYYY.MM.dd}" } }
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4.1.2 错误日志监控
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| { "query": { "bool": { "must": [ { "term": { "level": "ERROR" } }, { "range": { "@timestamp": { "gte": "now-1h" } } } ] } }, "aggs": { "error_count": { "value_count": { "field": "_id" } }, "error_by_service": { "terms": { "field": "service", "size": 10 } }, "error_timeline": { "date_histogram": { "field": "@timestamp", "calendar_interval": "5m" } } } }
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4.2 系统日志分析
4.2.1 系统监控配置
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| filebeat.inputs: - type: log enabled: true paths: - /var/log/syslog - /var/log/auth.log - /var/log/kern.log fields: log_type: system fields_under_root: true
- type: log enabled: true paths: - /var/log/nginx/*.log fields: log_type: nginx fields_under_root: true
processors: - add_host_metadata: when.not.contains.tags: forwarded
output.elasticsearch: hosts: ["localhost:9200"] index: "system-logs-%{+yyyy.MM.dd}"
setup.template.settings: index.number_of_shards: 1 index.codec: best_compression
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4.2.2 性能指标分析
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| { "query": { "bool": { "must": [ { "term": { "log_type": "system" } }, { "range": { "@timestamp": { "gte": "now-1d" } } } ] } }, "aggs": { "cpu_usage": { "avg": { "field": "cpu_percent" } }, "memory_usage": { "avg": { "field": "memory_percent" } }, "disk_usage": { "avg": { "field": "disk_percent" } }, "hourly_stats": { "date_histogram": { "field": "@timestamp", "calendar_interval": "1h" }, "aggs": { "avg_cpu": { "avg": { "field": "cpu_percent" } }, "avg_memory": { "avg": { "field": "memory_percent" } } } } } }
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4.3 网络日志分析
4.3.1 网络流量监控
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| packetbeat.interfaces.device: any packetbeat.interfaces.type: af_packet packetbeat.interfaces.buffer_size_mb: 100
packetbeat.protocols: - type: http ports: [80, 8080, 8000, 5000, 8002, 9200] send_headers: ["User-Agent", "Content-Type"] send_all_headers: true
- type: mysql ports: [3306]
- type: redis ports: [6379]
output.elasticsearch: hosts: ["localhost:9200"] index: "network-logs-%{+yyyy.MM.dd}"
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4.3.2 安全事件分析
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| { "query": { "bool": { "should": [ { "term": { "event_type": "login_failed" } }, { "term": { "event_type": "suspicious_activity" } }, { "wildcard": { "message": "*attack*" } } ], "minimum_should_match": 1 } }, "aggs": { "security_events": { "terms": { "field": "event_type", "size": 20 } }, "source_ips": { "terms": { "field": "source_ip", "size": 10 } }, "timeline": { "date_histogram": { "field": "@timestamp", "calendar_interval": "1h" } } } }
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五、监控告警系统构建
5.1 告警规则配置
5.1.1 Watcher告警引擎
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| { "trigger": { "schedule": { "interval": "1m" } }, "input": { "search": { "request": { "search_type": "query_then_fetch", "indices": ["app-logs-*"], "body": { "query": { "bool": { "must": [ { "term": { "level": "ERROR" } }, { "range": { "@timestamp": { "gte": "now-1m" } } } ] } }, "aggs": { "error_count": { "value_count": { "field": "_id" } } } } } } }, "condition": { "compare": { "ctx.payload.aggregations.error_count.value": { "gt": 10 } } }, "actions": { "send_email": { "email": { "to": ["admin@company.com"], "subject": "High Error Rate Alert", "body": { "text": "Error count exceeded threshold: {{ctx.payload.aggregations.error_count.value}}" } } }, "create_incident": { "webhook": { "url": "https://incident-management.company.com/api/incidents", "method": "POST", "headers": { "Content-Type": "application/json" }, "body": { "title": "High Error Rate Detected", "description": "Error count: {{ctx.payload.aggregations.error_count.value}}", "severity": "high", "source": "kibana" } } } } }
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5.1.2 复合告警规则
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| { "trigger": { "schedule": { "interval": "5m" } }, "input": { "search": { "request": { "indices": ["system-logs-*"], "body": { "query": { "bool": { "must": [ { "range": { "@timestamp": { "gte": "now-5m" } } } ] } }, "aggs": { "avg_cpu": { "avg": { "field": "cpu_percent" } }, "avg_memory": { "avg": { "field": "memory_percent" } }, "avg_disk": { "avg": { "field": "disk_percent" } } } } } } }, "condition": { "script": { "source": "return ctx.payload.aggregations.avg_cpu.value > 80 || ctx.payload.aggregations.avg_memory.value > 85 || ctx.payload.aggregations.avg_disk.value > 90" } }, "actions": { "alert_ops_team": { "email": { "to": ["ops@company.com"], "subject": "System Resource Alert", "body": { "text": "CPU: {{ctx.payload.aggregations.avg_cpu.value}}%, Memory: {{ctx.payload.aggregations.avg_memory.value}}%, Disk: {{ctx.payload.aggregations.avg_disk.value}}%" } } } } }
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5.2 告警通知渠道
5.2.1 邮件通知配置
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| xpack.actions.email: default: smtp: host: smtp.company.com port: 587 secure: false auth: user: kibana@company.com pass: your_password from: kibana@company.com reply_to: noreply@company.com
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5.2.2 企业微信集成
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| { "actions": { "wechat_alert": { "webhook": { "url": "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=your_key", "method": "POST", "headers": { "Content-Type": "application/json" }, "body": { "msgtype": "markdown", "markdown": { "content": "## 系统告警\n**告警时间**: {{ctx.trigger.triggered_time}}\n**告警内容**: {{ctx.payload.hits.total.value}} 条错误日志\n**详细信息**: [查看详情](https://kibana.company.com)" } } } } } }
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5.2.3 Slack集成
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| { "actions": { "slack_alert": { "webhook": { "url": "https://hooks.slack.com/services/YOUR/SLACK/WEBHOOK", "method": "POST", "headers": { "Content-Type": "application/json" }, "body": { "channel": "#alerts", "username": "Kibana Alert", "icon_emoji": ":warning:", "text": "系统告警: {{ctx.payload.hits.total.value}} 条错误日志", "attachments": [ { "color": "danger", "fields": [ { "title": "告警时间", "value": "{{ctx.trigger.triggered_time}}", "short": true }, { "title": "错误数量", "value": "{{ctx.payload.hits.total.value}}", "short": true } ] } ] } } } } }
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5.3 告警规则管理
5.3.1 告警规则模板
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| { "alert_templates": { "error_rate": { "name": "错误率告警", "description": "监控应用错误率", "query": { "bool": { "must": [ { "term": { "level": "ERROR" } }, { "range": { "@timestamp": { "gte": "now-{{interval}}" } } } ] } }, "threshold": 10, "interval": "1m", "actions": ["email", "slack"] }, "response_time": { "name": "响应时间告警", "description": "监控API响应时间", "query": { "bool": { "must": [ { "exists": { "field": "response_time" } }, { "range": { "@timestamp": { "gte": "now-{{interval}}" } } } ] } }, "threshold": 2000, "interval": "5m", "actions": ["email", "wechat"] } } }
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5.3.2 告警规则API
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| curl -X POST "localhost:9200/_watcher/watch/error_rate_alert" \ -H 'Content-Type: application/json' \ -u elastic:your_password \ -d '{ "trigger": { "schedule": { "interval": "1m" } }, "input": { "search": { "request": { "indices": ["app-logs-*"], "body": { "query": { "bool": { "must": [ { "term": { "level": "ERROR" } }, { "range": { "@timestamp": { "gte": "now-1m" } } } ] } }, "aggs": { "error_count": { "value_count": { "field": "_id" } } } } } } }, "condition": { "compare": { "ctx.payload.aggregations.error_count.value": { "gt": 10 } } }, "actions": { "send_alert": { "email": { "to": ["admin@company.com"], "subject": "Error Rate Alert", "body": "Error count: {{ctx.payload.aggregations.error_count.value}}" } } } }'
curl -X GET "localhost:9200/_watcher/watch/error_rate_alert" \ -u elastic:your_password
curl -X POST "localhost:9200/_watcher/watch/error_rate_alert/_execute" \ -u elastic:your_password
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六、数据可视化高级应用
6.1 自定义可视化组件
6.1.1 插件开发
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| import { Plugin as PluginBase } from 'kibana/server'; import { PluginSetup, PluginStart } from './types';
export class CustomVisualizationPlugin extends PluginBase<PluginSetup, PluginStart> { public setup(core: CoreSetup) { core.plugins.visualizations.registerVisualization({ name: 'custom_chart', title: 'Custom Chart', description: 'A custom visualization component', icon: 'visBarVertical', visConfig: { defaults: { chartType: 'line', showLegend: true, showTooltip: true } }, editorConfig: { schemas: [ { group: 'metrics', name: 'metric', title: 'Metric', min: 1, max: 1, aggFilter: ['count', 'avg', 'sum', 'min', 'max'] }, { group: 'buckets', name: 'segment', title: 'Group By', min: 0, max: 1, aggFilter: ['terms', 'date_histogram'] } ] }, toExpressionAst: (vis, params) => { return { type: 'expression', chain: [ { type: 'function', function: 'custom_chart', arguments: { metric: [vis.data.aggs.metric], segment: [vis.data.aggs.segment], chartType: [params.chartType], showLegend: [params.showLegend] } } ] }; } }); }
public start(core: CoreStart) { return {}; } }
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6.1.2 自定义图表渲染
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| import React from 'react'; import { EuiChart, EuiChartTheme } from '@elastic/eui';
export const CustomChartRenderer = ({ visData, visParams }) => { const chartTheme = { chart: { margins: { left: 0.2, right: 0.2, top: 0.2, bottom: 0.2 } }, line: { strokeWidth: 2, pointRadius: 3 }, area: { opacity: 0.3 } };
const chartData = visData.aggs.map(agg => ({ label: agg.label, data: agg.values.map((value, index) => ({ x: agg.buckets[index].key, y: value })) }));
return ( <div className="custom-chart-container"> <EuiChart type={visParams.chartType} data={chartData} theme={chartTheme} showLegend={visParams.showLegend} showTooltip={visParams.showTooltip} /> </div> ); };
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6.2 高级仪表板设计
6.2.1 响应式仪表板
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| { "dashboard": { "title": "响应式监控仪表板", "panelsJSON": "[{\"version\":\"8.0.0\",\"type\":\"visualization\",\"gridData\":{\"x\":0,\"y\":0,\"w\":6,\"h\":4,\"i\":\"1\"},\"panelIndex\":\"1\",\"embeddableConfig\":{\"savedVis\":{\"title\":\"CPU使用率\",\"type\":\"gauge\"}}},{\"version\":\"8.0.0\",\"type\":\"visualization\",\"gridData\":{\"x\":6,\"y\":0,\"w\":6,\"h\":4,\"i\":\"2\"},\"panelIndex\":\"2\",\"embeddableConfig\":{\"savedVis\":{\"title\":\"内存使用率\",\"type\":\"gauge\"}}},{\"version\":\"8.0.0\",\"type\":\"visualization\",\"gridData\":{\"x\":0,\"y\":4,\"w\":12,\"h\":6,\"i\":\"3\"},\"panelIndex\":\"3\",\"embeddableConfig\":{\"savedVis\":{\"title\":\"系统负载趋势\",\"type\":\"line\"}}}]", "optionsJSON": "{\"darkTheme\":false,\"useMargins\":true,\"syncColors\":true,\"hidePanelTitles\":false}", "version": 1, "timeRestore": true, "timeTo": "now", "timeFrom": "now-1h" } }
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6.2.2 交互式仪表板
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| { "dashboard": { "title": "交互式监控仪表板", "panelsJSON": "[{\"version\":\"8.0.0\",\"type\":\"visualization\",\"gridData\":{\"x\":0,\"y\":0,\"w\":8,\"h\":6,\"i\":\"1\"},\"panelIndex\":\"1\",\"embeddableConfig\":{\"savedVis\":{\"title\":\"服务状态概览\",\"type\":\"table\"}}},{\"version\":\"8.0.0\",\"type\":\"visualization\",\"gridData\":{\"x\":8,\"y\":0,\"w\":4,\"h\":6,\"i\":\"2\"},\"panelIndex\":\"2\",\"embeddableConfig\":{\"savedVis\":{\"title\":\"服务详情\",\"type\":\"metric\"}}}]", "optionsJSON": "{\"darkTheme\":false,\"useMargins\":true,\"syncColors\":true,\"hidePanelTitles\":false,\"syncTooltips\":true}", "filters": [ { "query": { "match": { "service": "{{service_name}}" } } } ] } }
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6.3 数据导出与分享
6.3.1 报表生成
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| { "reporting": { "enabled": true, "kibanaServer": { "hostname": "kibana.company.com", "port": 5601, "protocol": "https" }, "capture": { "browser": { "type": "chromium" }, "screenshot": { "type": "png" } }, "csv": { "maxSizeBytes": 10485760, "scroll": { "size": 500, "duration": "30s" } } } }
POST /api/reporting/generate/pdf { "jobParams": { "objectType": "dashboard", "objectId": "dashboard-id", "title": "系统监控报表", "timeRange": { "from": "now-1d", "to": "now" }, "layout": { "dimensions": { "width": 1920, "height": 1080 } } } }
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6.3.2 数据导出API
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| curl -X POST "localhost:5601/api/reporting/generate/csv" \ -H 'Content-Type: application/json' \ -u admin:password \ -d '{ "jobParams": { "objectType": "search", "objectId": "search-id", "title": "日志数据导出", "searchRequest": { "index": "app-logs-*", "body": { "query": { "match_all": {} }, "size": 10000 } } } }'
curl -X POST "localhost:5601/api/reporting/generate/png" \ -H 'Content-Type: application/json' \ -u admin:password \ -d '{ "jobParams": { "objectType": "visualization", "objectId": "vis-id", "title": "图表导出", "timeRange": { "from": "now-1h", "to": "now" } } }'
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七、性能优化与运维管理
7.1 Kibana性能优化
7.1.1 查询性能优化
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| server.maxPayloadBytes: 1048576 elasticsearch.requestTimeout: 30000 elasticsearch.shardTimeout: 30000
optimize.bundleFilter: "!tests" optimize.useBundleCache: true optimize.bundleDir: "/var/lib/kibana/optimize/bundles"
node.options: "--max-old-space-size=4096"
elasticsearch.maxConcurrentShardRequests: 5 elasticsearch.maxResponseSize: 10485760
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7.1.2 索引优化策略
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| PUT /_index_template/logs-template { "index_patterns": ["logs-*"], "template": { "settings": { "number_of_shards": 3, "number_of_replicas": 1, "index": { "refresh_interval": "30s", "translog": { "flush_threshold_size": "512mb", "sync_interval": "30s" }, "merge": { "scheduler": { "max_thread_count": 1 } } } }, "mappings": { "properties": { "@timestamp": { "type": "date" }, "message": { "type": "text", "analyzer": "standard", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "level": { "type": "keyword" }, "service": { "type": "keyword" } } } } }
PUT /_ilm/policy/logs-policy { "policy": { "phases": { "hot": { "actions": { "rollover": { "max_size": "50GB", "max_age": "7d" } } }, "warm": { "min_age": "7d", "actions": { "allocate": { "number_of_replicas": 0 } } }, "cold": { "min_age": "30d", "actions": { "allocate": { "number_of_replicas": 0 } } }, "delete": { "min_age": "90d" } } } }
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7.2 集群监控与运维
7.2.1 集群健康监控
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| const clusterHealthCheck = async () => { const response = await fetch('http://localhost:9200/_cluster/health?pretty'); const health = await response.json(); const alerts = []; if (health.status === 'red') { alerts.push('集群状态为红色,存在严重问题'); } else if (health.status === 'yellow') { alerts.push('集群状态为黄色,存在警告'); } if (health.active_shards_percent_as_number < 100) { alerts.push(`活跃分片比例: ${health.active_shards_percent_as_number}%`); } if (health.number_of_pending_tasks > 0) { alerts.push(`待处理任务: ${health.number_of_pending_tasks}`); } return { status: health.status, alerts: alerts, metrics: { active_shards: health.active_shards, relocating_shards: health.relocating_shards, initializing_shards: health.initializing_shards, unassigned_shards: health.unassigned_shards } }; };
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7.2.2 节点监控
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| const nodeMonitoring = async () => { const response = await fetch('http://localhost:9200/_nodes/stats?pretty'); const stats = await response.json(); const nodeStats = Object.values(stats.nodes).map(node => ({ name: node.name, host: node.host, roles: node.roles, jvm: { heap_used_percent: node.jvm.mem.heap_used_percent, gc_collection_time: node.jvm.gc.collectors.old.collection_time_in_millis, gc_collection_count: node.jvm.gc.collectors.old.collection_count }, indices: { docs_count: node.indices.docs.count, store_size: node.indices.store.size_in_bytes, indexing_total: node.indices.indexing.index_total, search_total: node.indices.search.query_total }, os: { cpu_percent: node.os.cpu.percent, load_average: node.os.cpu.load_average, mem_used_percent: node.os.mem.used_percent } })); return nodeStats; };
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7.3 备份与恢复
7.3.1 快照备份
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| curl -X PUT "localhost:9200/_snapshot/backup_repo" \ -H 'Content-Type: application/json' \ -u elastic:password \ -d '{ "type": "fs", "settings": { "location": "/backup/elasticsearch", "compress": true, "max_snapshot_bytes_per_sec": "50mb", "max_restore_bytes_per_sec": "50mb" } }'
curl -X PUT "localhost:9200/_snapshot/backup_repo/snapshot_$(date +%Y%m%d_%H%M%S)" \ -H 'Content-Type: application/json' \ -u elastic:password \ -d '{ "indices": "logs-*,app-logs-*", "ignore_unavailable": true, "include_global_state": false, "metadata": { "taken_by": "backup_script", "taken_because": "scheduled backup" } }'
curl -X GET "localhost:9200/_snapshot/backup_repo/_current" \ -u elastic:password
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7.3.2 数据恢复
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| curl -X POST "localhost:9200/_snapshot/backup_repo/snapshot_20241219_100000/_restore" \ -H 'Content-Type: application/json' \ -u elastic:password \ -d '{ "indices": "logs-*", "ignore_unavailable": true, "include_global_state": false, "rename_pattern": "logs-(.+)", "rename_replacement": "restored-logs-$1" }'
curl -X GET "localhost:9200/_recovery" \ -u elastic:password
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八、企业级最佳实践
8.1 架构设计原则
8.1.1 高可用架构
8.1.2 安全架构设计
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| 安全架构: 网络层安全: - VPN访问 - 防火墙规则 - 网络隔离 应用层安全: - HTTPS加密 - 身份认证 - 权限控制 数据层安全: - 数据加密 - 访问审计 - 备份加密 运维安全: - 操作审计 - 权限最小化 - 定期安全扫描
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8.2 容量规划
8.2.1 存储容量计算
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| const calculateStorageCapacity = (config) => { const { logVolumePerDay, retentionDays, replicationFactor, compressionRatio } = config; const rawDataPerDay = logVolumePerDay; const rawDataTotal = rawDataPerDay * retentionDays; const compressedDataPerDay = rawDataPerDay / compressionRatio; const compressedDataTotal = compressedDataPerDay * retentionDays; const totalStorage = compressedDataTotal * (1 + replicationFactor); const actualStorage = totalStorage * 1.2; return { rawDataPerDay: rawDataPerDay, rawDataTotal: rawDataTotal, compressedDataPerDay: compressedDataPerDay, compressedDataTotal: compressedDataTotal, totalStorage: totalStorage, actualStorage: actualStorage, recommendedStorage: Math.ceil(actualStorage * 1.5) }; };
const config = { logVolumePerDay: 100, retentionDays: 30, replicationFactor: 1, compressionRatio: 3 };
const capacity = calculateStorageCapacity(config); console.log('存储容量规划:', capacity);
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8.2.2 性能容量规划
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| const calculatePerformanceCapacity = (config) => { const { queriesPerSecond, averageResponseTime, peakMultiplier, nodeCount, coresPerNode } = config; const peakQPS = queriesPerSecond * peakMultiplier; const qpsPerCore = 1000; const totalCores = nodeCount * coresPerNode; const maxQPS = totalCores * qpsPerCore; const capacityUtilization = peakQPS / maxQPS; const responseTimeFactor = averageResponseTime / 100; return { peakQPS: peakQPS, maxQPS: maxQPS, capacityUtilization: capacityUtilization, responseTimeFactor: responseTimeFactor, recommendedNodes: Math.ceil(peakQPS / (qpsPerCore * coresPerNode)), isCapacitySufficient: capacityUtilization < 0.8 && responseTimeFactor < 2 }; };
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8.3 运维最佳实践
8.3.1 监控指标
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| 关键监控指标: Kibana指标: - 响应时间 - 并发用户数 - 内存使用率 - CPU使用率 Elasticsearch指标: - 集群健康状态 - 分片状态 - 索引性能 - 查询性能 系统指标: - 磁盘使用率 - 网络流量 - 系统负载 - 内存使用率
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8.3.2 告警策略
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| 告警策略: 紧急告警: - 集群状态为红色 - 服务不可用 - 磁盘空间不足10% 重要告警: - 集群状态为黄色 - 响应时间超过阈值 - 内存使用率超过80% 一般告警: - 错误日志数量异常 - 索引性能下降 - 网络连接异常
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九、故障排查与问题解决
9.1 常见问题诊断
9.1.1 性能问题诊断
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| curl -X GET "localhost:5601/api/status" | jq
curl -X GET "localhost:9200/_nodes/stats/jvm,indices,os" | jq
curl -X GET "localhost:9200/_nodes/stats/indices/search" | jq '.nodes[].indices.search.query_time_in_millis'
curl -X GET "localhost:9200/_cat/indices?v&s=store.size:desc"
curl -X GET "localhost:9200/_cat/shards?v&s=state,node"
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9.1.2 连接问题诊断
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| curl -X GET "localhost:5601/api/status" | jq '.status.overall.state'
curl -X GET "localhost:9200/_cluster/health" | jq '.status'
telnet localhost 9200 telnet localhost 5601
sudo ufw status sudo iptables -L
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9.2 日志分析
9.2.1 Kibana日志分析
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| tail -f /var/log/kibana/kibana.log
grep "ERROR" /var/log/kibana/kibana.log | tail -20
grep "slow" /var/log/kibana/kibana.log | tail -20
grep "connection" /var/log/kibana/kibana.log | tail -20
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9.2.2 Elasticsearch日志分析
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| tail -f /var/log/elasticsearch/elasticsearch.log
grep "GC" /var/log/elasticsearch/elasticsearch.log | tail -20
grep "shard" /var/log/elasticsearch/elasticsearch.log | tail -20
grep "cluster" /var/log/elasticsearch/elasticsearch.log | tail -20
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9.3 故障恢复
9.3.1 服务重启
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| sudo systemctl restart kibana sudo systemctl status kibana
sudo systemctl restart elasticsearch sudo systemctl status elasticsearch
sudo systemctl is-active kibana sudo systemctl is-active elasticsearch
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9.3.2 数据恢复
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| curl -X POST "localhost:9200/_snapshot/backup_repo/snapshot_name/_restore" \ -H 'Content-Type: application/json' \ -d '{ "indices": "index_name", "ignore_unavailable": true, "include_global_state": false }'
curl -X POST "localhost:9200/_reindex" \ -H 'Content-Type: application/json' \ -d '{ "source": { "index": "old_index" }, "dest": { "index": "new_index" } }'
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十、总结与展望
10.1 技术总结
通过本文的深入探讨,我们全面了解了Kibana可视化分析平台的架构设计与实战应用。从基础搭建到高级优化,从日志分析到监控告警,Kibana为企业提供了强大的数据可视化和分析能力。
10.1.1 核心价值
- 数据可视化:提供丰富的图表类型和交互式仪表板
- 实时分析:支持实时数据流分析和历史数据回溯
- 监控告警:构建完整的监控告警体系
- 企业级特性:高可用、可扩展、安全可靠
10.1.2 技术优势
- 易用性:直观的用户界面和简单的操作流程
- 灵活性:支持自定义可视化和插件开发
- 性能:优化的查询引擎和缓存机制
- 集成性:与Elastic Stack深度集成
10.2 最佳实践建议
10.2.1 架构设计
- 高可用设计:采用多节点部署和负载均衡
- 安全加固:实施全面的安全策略和访问控制
- 性能优化:合理配置资源和优化查询
- 监控运维:建立完善的监控和告警体系
10.2.2 运维管理
- 容量规划:根据业务需求合理规划资源
- 备份策略:建立完善的备份和恢复机制
- 故障处理:制定详细的故障排查和恢复流程
- 持续优化:定期评估和优化系统性能
10.3 未来发展趋势
10.3.1 技术发展方向
- AI集成:机器学习算法在数据分析中的应用
- 云原生:容器化和微服务架构的演进
- 实时性:更强大的实时数据处理能力
- 智能化:自动化运维和智能告警
10.3.2 应用场景扩展
- 业务分析:从技术监控扩展到业务分析
- 安全分析:增强的安全威胁检测和分析
- IoT数据:物联网设备数据的可视化分析
- 边缘计算:边缘环境下的数据分析能力
10.4 学习建议
10.4.1 技术学习路径
- 基础掌握:熟悉Elastic Stack基础组件
- 实践应用:通过实际项目积累经验
- 高级特性:深入学习高级功能和优化技巧
- 持续更新:关注技术发展和最佳实践
10.4.2 职业发展建议
- 技能提升:持续学习相关技术和工具
- 项目经验:参与大型项目的架构设计
- 社区参与:积极参与开源社区和技术交流
- 认证获取:获得相关技术认证和资质
结语
Kibana作为现代企业数据分析的重要工具,为企业提供了强大的数据可视化和分析能力。通过合理的架构设计、完善的配置管理、有效的性能优化和可靠的运维保障,企业可以构建高效、稳定、安全的数据分析平台。
在数字化转型的浪潮中,掌握Kibana等数据分析工具已成为技术人员的必备技能。希望本文能够为读者提供全面的技术指导和实践参考,助力企业在数据驱动的道路上取得更大的成功。
让我们继续探索数据世界的无限可能,用技术的力量推动企业的发展和创新!
关键词:Kibana、Elasticsearch、数据可视化、日志分析、监控告警、企业级架构、运维实战、性能优化、安全配置、故障排查
相关技术:Elastic Stack、Logstash、Beats、Watcher、Canvas、Lens、Machine Learning、APM、SIEM
适用场景:企业级日志分析、系统监控、业务分析、安全分析、运维管理、数据可视化、实时监控、告警系统