技术知识库/技术文档/其他/容器服务平台-操作手册/搭建与使用遥测系统.md created
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技术知识库/技术文档/其他/容器服务平台-操作手册/搭建与使用遥测系统.md
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技术知识库/技术文档/其他/容器服务平台-操作手册/搭建与使用遥测系统.md
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# 遥测服务架构图
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# 部署遥测应用
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通过如下docker-compose文件启动应用：
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```yml
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version: '3'
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services:
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# 遥测数据采集
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otel:
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image: otel/opentelemetry-collector-contrib
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container_name: otel
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networks:
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- default
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- collector
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ports:
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- 4317:4317
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volumes:
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- ./etc/otel/otel-collector-config.yaml:/etc/otelcol-contrib/config.yaml
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restart: unless-stopped
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# 踪迹存储，可替换为jaeger
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tempo:
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image: grafana/tempo
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container_name: tempo
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networks:
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- default
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volumes:
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- ./etc/tempo/tempo.yaml:/etc/tempo/config.yml
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- ./data/tempo:/data/tempo
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command: ["-config.file=/etc/tempo/config.yml"]
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restart: unless-stopped
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# 日志存储，可替换为ElasticSearch
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loki:
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image: grafana/loki
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container_name: loki
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networks:
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- default
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volumes:
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- ./etc/loki/local-config.yaml:/etc/loki/local-config.yaml
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- ./data/loki:/data/loki
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restart: unless-stopped
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# 指标存储
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prometheus:
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image: prom/prometheus
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container_name: prometheus
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networks:
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- default
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extra_hosts:
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- "host.docker.internal:host-gateway"
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volumes:
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- ./etc/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml
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- ./data/prometheus:/prometheus
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restart: unless-stopped
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# 可视化
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grafana:
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image: grafana/grafana-oss
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container_name: grafana
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networks:
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- default
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# For more information on this configuration, see the complete reference guide at
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# https://grafana.com/docs/grafana/latest/setup-grafana/configure-grafana/
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enviroment:
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# Run Grafana behind a reverse proxy
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# https://grafana.com/tutorials/run-grafana-behind-a-proxy/
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- GF_SERVER_DOMAIN=https://www.rzdata.net
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- GF_SERVER_ROOT_URL = %(protocol)s://%(domain)s/grafana/
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- GF_SERVER_SERVE_FROM_SUB_PATH=true
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ports:
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- 3000:3000
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volumes:
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- ./data/grafana:/var/lib/grafana
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restart: unless-stopped
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networks:
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default:
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driver: bridge
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collector:
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driver: bridge
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```
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tempo配置文件：
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```yml
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# For more information on this configuration, see the complete reference guide at
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# https://grafana.com/docs/tempo/latest/configuration/
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stream_over_http_enabled: true
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# Configure the server block.
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server:
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# Listen for all incoming requests on port 3200.
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http_listen_port: 3200
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# The distributor receives incoming trace span data for the system.
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distributor:
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receivers: # This configuration will listen on all ports and protocols that tempo is capable of.
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otlp:
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protocols:
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grpc: # This example repository only utilises the OTLP gRPC receiver on port 4317.
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# The ingester receives data from the distributor and processes it into indices and blocks.
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ingester:
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trace_idle_period: 10s # The length of time after a trace has not received spans to consider it complete and flush it.
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max_block_bytes: 1_000_000 # Cut the head block when it hits this size or
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max_block_duration: 5m # this much time passes
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# The compactor block configures the compactor responsible for compacting TSDB blocks.
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compactor:
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compaction:
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compaction_window: 1h # Blocks in this time window will be compacted together.
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max_block_bytes: 100_000_000 # Maximum size of a compacted block.
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block_retention: 1h # How long to keep blocks. Default is 14 days, this demo system is short-lived.
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compacted_block_retention: 10m # How long to keep compacted blocks stored elsewhere.
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# Configuration block to determine where to store TSDB blocks.
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storage:
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trace:
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backend: local # Use the local filesystem for block storage. Not recommended for production systems.
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block:
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bloom_filter_false_positive: .05 # Bloom filter false positive rate. lower values create larger filters but fewer false positives.
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# Write Ahead Log (WAL) configuration.
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wal:
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path: /data/tempo/wal # Directory to store the the WAL locally.
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# Local configuration for filesystem storage.
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local:
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path: /data/tempo/blocks # Directory to store the TSDB blocks.
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# Pool used for finding trace IDs.
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pool:
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max_workers: 100 # Worker pool determines the number of parallel requests to the object store backend.
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queue_depth: 10000 # Maximum depth for the querier queue jobs. A job is required for each block searched.
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# Configures the metrics generator component of Tempo.
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metrics_generator:
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# Specifies which processors to use.
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processor:
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# Span metrics create metrics based on span type, duration, name and service.
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span_metrics:
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# Configure extra dimensions to add as metric labels.
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dimensions:
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- http.method
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- http.target
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- http.status_code
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- service.version
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# Service graph metrics create node and edge metrics for determinng service interactions.
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service_graphs:
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# Configure extra dimensions to add as metric labels.
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dimensions:
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- http.method
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- http.target
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- http.status_code
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- service.version
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# The registry configuration determines how to process metrics.
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registry:
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collection_interval: 5s # Create new metrics every 5s.
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# Configure extra labels to be added to metrics.
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external_labels:
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source: tempo # Add a `{source="tempo"}` label.
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group: 'mythical' # Add a `{group="mythical"}` label.
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# Configures where the store for metrics is located.
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storage:
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# WAL for metrics generation.
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path: /data/tempo/generator/wal
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traces_storage:
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path: /data/tempo/generator/traces
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# Global override configuration.
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overrides:
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metrics_generator_processors: ['service-graphs', 'span-metrics','local-blocks'] # The types of metrics generation to enable for each tenant.
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```
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loki配置文件：
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```yml
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# For more information on this configuration, see the complete reference guide at
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# https://grafana.com/docs/loki/latest/configure/
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auth_enabled: false
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server:
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http_listen_port: 3100
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grpc_listen_port: 9096
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common:
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instance_addr: 127.0.0.1
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path_prefix: /data/loki
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storage:
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filesystem:
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chunks_directory: /data/loki/chunks
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rules_directory: /data/loki/rules
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replication_factor: 1
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ring:
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kvstore:
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store: inmemory
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query_range:
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results_cache:
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cache:
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embedded_cache:
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enabled: true
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max_size_mb: 100
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schema_config:
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configs:
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- from: 2020-10-24
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store: tsdb
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object_store: filesystem
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schema: v12
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index:
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prefix: index_
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period: 24h
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ruler:
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alertmanager_url: http://localhost:9093
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```
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prometheus配置文件：
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```yml
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# For more information on this configuration, see the complete reference guide at
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# https://prometheus.io/docs/prometheus/latest/configuration/configuration/
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global:
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scrape_interval: 15s
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scrape_configs:
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- job_name: aggregated-trace-metrics
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static_configs:
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- targets: ['otel:8889']
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```
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opentelemetry collector配置文件：
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```yml
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# For more information on this configuration, see the complete reference guide at
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# https://opentelemetry.io/docs/collector/configuration/
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receivers:
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otlp:
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protocols:
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grpc:
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processors:
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batch:
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connectors:
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spanmetrics:
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dimensions:
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- name: http.method # extract http.method attribute from span to Prometheus label http_method
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- name: http.status_code # extract http.status_code attribute from span to Prometheus label http_status_code
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- name: http.route # extract http.route attribute from span to Prometheus label http_route
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exporters:
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debug:
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otlp/tempo:
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endpoint: tempo:4317
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tls:
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insecure: true
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loki:
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endpoint: http://loki:3100/loki/api/v1/push
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prometheusremotewrite:
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endpoint: http://prometheus:9090/api/v1/write
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prometheus:
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endpoint: "0.0.0.0:8889"
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service:
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pipelines:
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traces:
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receivers: [otlp]
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processors: [batch]
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exporters: [debug, spanmetrics, otlp/tempo]
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logs:
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receivers: [otlp]
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processors: [batch]
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exporters: [debug, loki]
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metrics:
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receivers: [otlp]
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processors: [batch]
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exporters: [debug, prometheus]
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metrics/spanmetrics:
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receivers: [spanmetrics]
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exporters: [debug, prometheus]
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```
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# **后端服务收集遥测数据**
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分别下载 [opentelemetry-javaagent.jar](https://github.com/open-telemetry/opentelemetry-java-instrumentation/releases/latest/download/opentelemetry-javaagent.jar) 和 [ot-java-agent-extension-1.28.0.jar](https://github.com/alibabacloud-observability/opentelemetry-best-practice/raw/main/opentelemetry-javaagent-extension/ot-java-agent-extension-1.28.0.jar) 放在 /opt/agent 目录。然后用以下命令启动应用：
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```shell
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# For more information on this configuration, see the complete reference guide at
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# https://github.com/open-telemetry/opentelemetry-java/tree/main/sdk-extensions/autoconfigure
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java -javaagent:/opt/agent/opentelemetry-javaagent.jar \
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-Dotel.javaagent.extensions=/opt/agent/ot-java-agent-extension-1.28.0.jar \
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-Dotel.exporter.otlp.endpoint=http://otel:4317 \
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-Dotel.service.name=xxx \
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-Dotel.logs.exporter=otlp \
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-jar xxx.jar
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```
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opentelemetry-javaagent 会对一些库自动记录 Span，如果想要追加一些 Span 以便更精细地追踪，则需要通过注解来控制：
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```xml
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<dependencies>
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<dependency>
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<groupId>io.opentelemetry.instrumentation</groupId>
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<artifactId>opentelemetry-instrumentation-annotations</artifactId>
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<version>1.32.0</version>
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</dependency>
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</dependencies>
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```
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```java
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import io.opentelemetry.instrumentation.annotations.WithSpan;
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/**
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* @see <a href="https://opentelemetry.io/docs/instrumentation/java/automatic/annotations/">Annotations | OpenTelemetry</a>
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*/
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public class MyClass {
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@WithSpan
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public void myMethod() {
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<...>
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}
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}
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```
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# 可视化遥测数据
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访问https://www.rzdata.net/grafana/。添加数据源：
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## 查看踪迹
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## 查看日志
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## 查看指标
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指标的配置比较复杂，可以在 [Grafana Dashboard Market](https://grafana.com/grafana/dashboards/) 找到现成的 Dashboard 来使用。这里可以尝试 [OpenTelemetry APM](https://grafana.com/grafana/dashboards/19419-opentelemetry-apm/)。
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<!--stackedit_data:
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eyJoaXN0b3J5IjpbLTc0ODQzNzgyOF19
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-->
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