SpringBoot Advanced Tutorial (70)SkyWalking

There are many popular APM(Application Performance Management tools, such as Cat, Zipkin, Pinpoint, SkyWalking. Other excellent monitoring tools include Zabbix, Prometheus, Arthas, and Grafana. SkyWalking is an excellent domestic APM tool that includes distributed tracking, performance metrics analysis, application and service dependency analysis, etc.

Skywalking is an application performance monitoring tool for distributed systems, designed for microservices, cloud native architectures, and container-based (Docker, K8s, Mesos) architectures. SkyWalking is an observational analytics platform and application performance management system. Provides integrated solutions for distributed tracking, service grid telemetry analysis, measurement aggregation and visualization. Supports Java,.NET Core, PHP, NodeJS, Golang, LUA probes and Service Mesh built by Envoy + Istio.

V is introduced

1.1 SkyWalking is logically divided into four parts: probe, platform back end, storage, and user interface. Its architecture diagram is as follows:

Pictures from the network, deleted.

Probes: The probes may be different depending on the source, but all they do is collect data and format it into a format suitable for SkyWalking. In Java, for example, bytecode implantation, non-invasive collection, and sending data to the back end of the platform via HTTP or GRPC.

Platform backend: A backend that supports cluster mode for data aggregation, data analysis, and processes that drive data flow from probes to user interfaces. The platform back end also provides pluggable capabilities such as formatting data from different sources (such as Zipkin), different storage systems, and cluster management. You can even use observational analysis language to do custom aggregation analysis.

Storage: Is open, you can choose an existing storage system such as ElasticSearch, H2 or MySQL cluster (managed by Sharding-Sphere), or you can choose to implement your own storage system.

User Interface: SkyWalking’s visual interface, the UI is cool and powerful, but also customizable to match your existing backend.

1.2 The concepts of services, service instances, and endpoints also exist in SkyWalking because SkyWalking provides the ability to observe these concepts:

Service: Represents a series or set of workloads that provide the same behavior for requests. When using an agent or SDK, you can define the name of the service. If not, SkyWalking will use the name you define on the platform, such as Istio.

Service Instance: Each workload in the set above is called an Instance. Just like the Pods in Kubernetes, a service instance is not necessarily a process on the operating system. But when you use an agent, a service instance is actually a real process on the operating system.

Endpoint: The request path received by a particular service, such as the HTTP URI path and the class name + method signature of the gRPC service

1.3 Advantages of SkyWalking are as follows:

1. Multiple monitoring means, language probe and Service Mesh

2. Modularization: UI, storage, and cluster management are optional

3. Supports alarms (alarms can be pushed to nails)

4. Excellent visualization scheme

V Environment Preparation

2.1 Pulling a Mirror

Docker Pull :7.5.1 Docker pull Apache/Skywalking - OAP-server: 8.3.0-ES7 Docker pull Apache/skywalking - UI: 8.3.0Copy the code

2.2 Creating and Starting ElasticSearch

Docker run -d --name=es7 \ -p 9200:9200 \ -e "discovery. Type =single-node" ElasticSearch :7.5.1Copy the code

Note: To create an ES persistent directory, follow the command below.

mkdir -p /data/elasticsearch docker cp es7:/usr/share/elasticsearch/data /data/elasticsearch/ docker cp es7:/usr/share/elasticsearch/logs /data/elasticsearch/ docker rm -f es7 docker run -d --name=es7 \ --restart=always \ -p  9200:9200 -p 9300:9300 \ -e "discovery.type=single-node" \ -v /data/elasticsearch/data:/usr/share/elasticsearch/data \ - v/data/elasticsearch/logs: / usr/share/elasticsearch/logs \ elasticsearch: 7.5.1Copy the code

2.3 Creating and Starting the OAP

docker run --name oap --restart always -d \ --restart=always \ -e TZ=Asia/Shanghai \ -p 12800:12800 \ -p 11800:11800 \ --link es7:es7 \ -e SW_STORAGE=elasticsearch7 \ -e SW_STORAGE_ES_CLUSTER_NODES=es7:9200 \ Apache/skywalking - oap - server: 8.3.0 - es7Copy the code

SW_STORAGE: elasticSearch7 is selected as the storage component

SW_STORAGE_ES_CLUSTER_NODES: Specifies elasticSearch nodes. Multiple nodes are separated by commas (,)

All the above parameters are in the application.yml file.

Application. Yml details are as follows:

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
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# limitations under the License.

cluster:
  selector: ${SW_CLUSTER:standalone}
  standalone:
  # Please check your ZooKeeper is 3.5+, However, it is also compatible with ZooKeeper 3.4.x. Replace the ZooKeeper 3.5+
  # library the oap-libs folder with your ZooKeeper 3.4.x library.
  zookeeper:
    nameSpace: ${SW_NAMESPACE:""}
    hostPort: ${SW_CLUSTER_ZK_HOST_PORT:localhost:2181}
    # Retry Policy
    baseSleepTimeMs: ${SW_CLUSTER_ZK_SLEEP_TIME:1000} # initial amount of time to wait between retries
    maxRetries: ${SW_CLUSTER_ZK_MAX_RETRIES:3} # max number of times to retry
    # Enable ACL
    enableACL: ${SW_ZK_ENABLE_ACL:false} # disable ACL in default
    schema: ${SW_ZK_SCHEMA:digest} # only support digest schema
    expression: ${SW_ZK_EXPRESSION:skywalking:skywalking}
  kubernetes:
    namespace: ${SW_CLUSTER_K8S_NAMESPACE:default}
    labelSelector: ${SW_CLUSTER_K8S_LABEL:app=collector,release=skywalking}
    uidEnvName: ${SW_CLUSTER_K8S_UID:SKYWALKING_COLLECTOR_UID}
  consul:
    serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}
    # Consul cluster nodes, example: 10.0.0.1:8500,10.0.0.2:8500,10.0.0.3:8500
    hostPort: ${SW_CLUSTER_CONSUL_HOST_PORT:localhost:8500}
    aclToken: ${SW_CLUSTER_CONSUL_ACLTOKEN:""}
  etcd:
    serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}
    # etcd cluster nodes, example: 10.0.0.1:2379,10.0.0.2:2379,10.0.0.3:2379
    hostPort: ${SW_CLUSTER_ETCD_HOST_PORT:localhost:2379}
  nacos:
    serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}
    hostPort: ${SW_CLUSTER_NACOS_HOST_PORT:localhost:8848}
    # Nacos Configuration namespace
    namespace: ${SW_CLUSTER_NACOS_NAMESPACE:"public"}
    # Nacos auth username
    username: ${SW_CLUSTER_NACOS_USERNAME:""}
    password: ${SW_CLUSTER_NACOS_PASSWORD:""}
    # Nacos auth accessKey
    accessKey: ${SW_CLUSTER_NACOS_ACCESSKEY:""}
    secretKey: ${SW_CLUSTER_NACOS_SECRETKEY:""}
core:
  selector: ${SW_CORE:default}
  default:
    # Mixed: Receive agent data, Level 1 aggregate, Level 2 aggregate
    # Receiver: Receive agent data, Level 1 aggregate
    # Aggregator: Level 2 aggregate
    role: ${SW_CORE_ROLE:Mixed} # Mixed/Receiver/Aggregator
    restHost: ${SW_CORE_REST_HOST:0.0.0.0}
    restPort: ${SW_CORE_REST_PORT:12800}
    restContextPath: ${SW_CORE_REST_CONTEXT_PATH:/}
    restMinThreads: ${SW_CORE_REST_JETTY_MIN_THREADS:1}
    restMaxThreads: ${SW_CORE_REST_JETTY_MAX_THREADS:200}
    restIdleTimeOut: ${SW_CORE_REST_JETTY_IDLE_TIMEOUT:30000}
    restAcceptorPriorityDelta: ${SW_CORE_REST_JETTY_DELTA:0}
    restAcceptQueueSize: ${SW_CORE_REST_JETTY_QUEUE_SIZE:0}
    gRPCHost: ${SW_CORE_GRPC_HOST:0.0.0.0}
    gRPCPort: ${SW_CORE_GRPC_PORT:11800}
    maxConcurrentCallsPerConnection: ${SW_CORE_GRPC_MAX_CONCURRENT_CALL:0}
    maxMessageSize: ${SW_CORE_GRPC_MAX_MESSAGE_SIZE:0}
    gRPCThreadPoolQueueSize: ${SW_CORE_GRPC_POOL_QUEUE_SIZE:-1}
    gRPCThreadPoolSize: ${SW_CORE_GRPC_THREAD_POOL_SIZE:-1}
    gRPCSslEnabled: ${SW_CORE_GRPC_SSL_ENABLED:false}
    gRPCSslKeyPath: ${SW_CORE_GRPC_SSL_KEY_PATH:""}
    gRPCSslCertChainPath: ${SW_CORE_GRPC_SSL_CERT_CHAIN_PATH:""}
    gRPCSslTrustedCAPath: ${SW_CORE_GRPC_SSL_TRUSTED_CA_PATH:""}
    downsampling:
      - Hour
      - Day
    # Set a timeout on metrics data. After the timeout has expired, the metrics data will automatically be deleted.
    enableDataKeeperExecutor: ${SW_CORE_ENABLE_DATA_KEEPER_EXECUTOR:true} # Turn it off then automatically metrics data delete will be close.
    dataKeeperExecutePeriod: ${SW_CORE_DATA_KEEPER_EXECUTE_PERIOD:5} # How often the data keeper executor runs periodically, unit is minute
    recordDataTTL: ${SW_CORE_RECORD_DATA_TTL:3} # Unit is day
    metricsDataTTL: ${SW_CORE_METRICS_DATA_TTL:7} # Unit is day
    # Cache metrics data for 1 minute to reduce database queries, and if the OAP cluster changes within that minute,
    # the metrics may not be accurate within that minute.
    enableDatabaseSession: ${SW_CORE_ENABLE_DATABASE_SESSION:true}
    topNReportPeriod: ${SW_CORE_TOPN_REPORT_PERIOD:10} # top_n record worker report cycle, unit is minute
    # Extra model column are the column defined by in the codes, These columns of model are not required logically in aggregation or further query,
    # and it will cause more load for memory, network of OAP and storage.
    # But, being activated, user could see the name in the storage entities, which make users easier to use 3rd party tool, such as Kibana->ES, to query the data by themselves.
    activeExtraModelColumns: ${SW_CORE_ACTIVE_EXTRA_MODEL_COLUMNS:false}
    # The max length of service + instance names should be less than 200
    serviceNameMaxLength: ${SW_SERVICE_NAME_MAX_LENGTH:70}
    instanceNameMaxLength: ${SW_INSTANCE_NAME_MAX_LENGTH:70}
    # The max length of service + endpoint names should be less than 240
    endpointNameMaxLength: ${SW_ENDPOINT_NAME_MAX_LENGTH:150}
    # Define the set of span tag keys, which should be searchable through the GraphQL.
    searchableTracesTags: ${SW_SEARCHABLE_TAG_KEYS:http.method,status_code,db.type,db.instance,mq.queue,mq.topic,mq.broker}
storage:
  selector: ${SW_STORAGE:h2}
  elasticsearch:
    nameSpace: ${SW_NAMESPACE:""}
    clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
    protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
    user: ${SW_ES_USER:""}
    password: ${SW_ES_PASSWORD:""}
    trustStorePath: ${SW_STORAGE_ES_SSL_JKS_PATH:""}
    trustStorePass: ${SW_STORAGE_ES_SSL_JKS_PASS:""}
    secretsManagementFile: ${SW_ES_SECRETS_MANAGEMENT_FILE:""} # Secrets management file in the properties format includes the username, password, which are managed by 3rd party tool.
    dayStep: ${SW_STORAGE_DAY_STEP:1} # Represent the number of days in the one minute/hour/day index.
    indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # Shard number of new indexes
    indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes
    # Super data set has been defined in the codes, such as trace segments.The following 3 config would be improve es performance when storage super size data in es.
    superDatasetDayStep: ${SW_SUPERDATASET_STORAGE_DAY_STEP:-1} # Represent the number of days in the super size dataset record index, the default value is the same as dayStep when the value is less than 0
    superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} #  This factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jaeger traces.
    superDatasetIndexReplicasNumber: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_REPLICAS_NUMBER:0} # Represent the replicas number in the super size dataset record index, the default value is 0.
    bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:1000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requests
    syncBulkActions: ${SW_STORAGE_ES_SYNC_BULK_ACTIONS:50000} # Execute the sync bulk metrics data every ${SW_STORAGE_ES_SYNC_BULK_ACTIONS} requests
    flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:10} # flush the bulk every 10 seconds whatever the number of requests
    concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
    resultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}
    metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:5000}
    segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}
    profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}
    advanced: ${SW_STORAGE_ES_ADVANCED:""}
  elasticsearch7:
    nameSpace: ${SW_NAMESPACE:""}
    clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
    protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
    trustStorePath: ${SW_STORAGE_ES_SSL_JKS_PATH:""}
    trustStorePass: ${SW_STORAGE_ES_SSL_JKS_PASS:""}
    dayStep: ${SW_STORAGE_DAY_STEP:1} # Represent the number of days in the one minute/hour/day index.
    indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # Shard number of new indexes
    indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes
    # Super data set has been defined in the codes, such as trace segments.The following 3 config would be improve es performance when storage super size data in es.
    superDatasetDayStep: ${SW_SUPERDATASET_STORAGE_DAY_STEP:-1} # Represent the number of days in the super size dataset record index, the default value is the same as dayStep when the value is less than 0
    superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} #  This factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jaeger traces.
    superDatasetIndexReplicasNumber: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_REPLICAS_NUMBER:0} # Represent the replicas number in the super size dataset record index, the default value is 0.
    user: ${SW_ES_USER:""}
    password: ${SW_ES_PASSWORD:""}
    secretsManagementFile: ${SW_ES_SECRETS_MANAGEMENT_FILE:""} # Secrets management file in the properties format includes the username, password, which are managed by 3rd party tool.
    bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:1000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requests
    syncBulkActions: ${SW_STORAGE_ES_SYNC_BULK_ACTIONS:50000} # Execute the sync bulk metrics data every ${SW_STORAGE_ES_SYNC_BULK_ACTIONS} requests
    flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:10} # flush the bulk every 10 seconds whatever the number of requests
    concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
    resultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}
    metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:5000}
    segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}
    profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}
    advanced: ${SW_STORAGE_ES_ADVANCED:""}
  h2:
    driver: ${SW_STORAGE_H2_DRIVER:org.h2.jdbcx.JdbcDataSource}
    url: ${SW_STORAGE_H2_URL:jdbc:h2:mem:skywalking-oap-db}
    user: ${SW_STORAGE_H2_USER:sa}
    metadataQueryMaxSize: ${SW_STORAGE_H2_QUERY_MAX_SIZE:5000}
    maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
    numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
  mysql:
    properties:
      jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://localhost:3306/swtest"}
      dataSource.user: ${SW_DATA_SOURCE_USER:root}
      dataSource.password: ${SW_DATA_SOURCE_PASSWORD:root@1234}
      dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
      dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
      dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
      dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
    metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
    maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
    numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
  tidb:
    properties:
      jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://localhost:4000/tidbswtest"}
      dataSource.user: ${SW_DATA_SOURCE_USER:root}
      dataSource.password: ${SW_DATA_SOURCE_PASSWORD:""}
      dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
      dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
      dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
      dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
      dataSource.useAffectedRows: ${SW_DATA_SOURCE_USE_AFFECTED_ROWS:true}
    metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
    maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
    numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
  influxdb:
    # InfluxDB configuration
    url: ${SW_STORAGE_INFLUXDB_URL:http://localhost:8086}
    user: ${SW_STORAGE_INFLUXDB_USER:root}
    password: ${SW_STORAGE_INFLUXDB_PASSWORD:}
    database: ${SW_STORAGE_INFLUXDB_DATABASE:skywalking}
    actions: ${SW_STORAGE_INFLUXDB_ACTIONS:1000} # the number of actions to collect
    duration: ${SW_STORAGE_INFLUXDB_DURATION:1000} # the time to wait at most (milliseconds)
    batchEnabled: ${SW_STORAGE_INFLUXDB_BATCH_ENABLED:true}
    fetchTaskLogMaxSize: ${SW_STORAGE_INFLUXDB_FETCH_TASK_LOG_MAX_SIZE:5000} # the max number of fetch task log in a request

agent-analyzer:
  selector: ${SW_AGENT_ANALYZER:default}
  default:
    sampleRate: ${SW_TRACE_SAMPLE_RATE:10000} # The sample rate precision is 1/10000. 10000 means 100% sample in default.
    slowDBAccessThreshold: ${SW_SLOW_DB_THRESHOLD:default:200,mongodb:100} # The slow database access thresholds. Unit ms.
    forceSampleErrorSegment: ${SW_FORCE_SAMPLE_ERROR_SEGMENT:true} # When sampling mechanism active, this config can open(true) force save some error segment. true is default.
    segmentStatusAnalysisStrategy: ${SW_SEGMENT_STATUS_ANALYSIS_STRATEGY:FROM_SPAN_STATUS} # Determine the final segment status from the status of spans. Available values are `FROM_SPAN_STATUS` , `FROM_ENTRY_SPAN` and `FROM_FIRST_SPAN`. `FROM_SPAN_STATUS` represents the segment status would be error if any span is in error status. `FROM_ENTRY_SPAN` means the segment status would be determined by the status of entry spans only. `FROM_FIRST_SPAN` means the segment status would be determined by the status of the first span only.
    # Nginx and Envoy agents can't get the real remote address.
    # Exit spans with the component in the list would not generate the client-side instance relation metrics.
    noUpstreamRealAddressAgents: ${SW_NO_UPSTREAM_REAL_ADDRESS:6000,9000}
    slowTraceSegmentThreshold: ${SW_SLOW_TRACE_SEGMENT_THRESHOLD:-1} # Setting this threshold about the latency would make the slow trace segments sampled if they cost more time, even the sampling mechanism activated. The default value is `-1`, which means would not sample slow traces. Unit, millisecond.
    meterAnalyzerActiveFiles: ${SW_METER_ANALYZER_ACTIVE_FILES:} # Which files could be meter analyzed, files split by ","

receiver-sharing-server:
  selector: ${SW_RECEIVER_SHARING_SERVER:default}
  default:
    # For Jetty server
    restHost: ${SW_RECEIVER_SHARING_REST_HOST:0.0.0.0}
    restPort: ${SW_RECEIVER_SHARING_REST_PORT:0}
    contextPath: ${SW_RECEIVER_SHARING_REST_CONTEXT_PATH:/}
    restMinThreads: ${SW_RECEIVER_SHARING_JETTY_MIN_THREADS:1}
    restMaxThreads: ${SW_RECEIVER_SHARING_JETTY_MAX_THREADS:200}
    restIdleTimeOut: ${SW_RECEIVER_SHARING_JETTY_IDLE_TIMEOUT:30000}
    restAcceptorPriorityDelta: ${SW_RECEIVER_SHARING_JETTY_DELTA:0}
    restAcceptQueueSize: ${SW_RECEIVER_SHARING_JETTY_QUEUE_SIZE:0}
    # For gRPC server
    gRPCHost: ${SW_RECEIVER_GRPC_HOST:0.0.0.0}
    gRPCPort: ${SW_RECEIVER_GRPC_PORT:0}
    maxConcurrentCallsPerConnection: ${SW_RECEIVER_GRPC_MAX_CONCURRENT_CALL:0}
    maxMessageSize: ${SW_RECEIVER_GRPC_MAX_MESSAGE_SIZE:0}
    gRPCThreadPoolQueueSize: ${SW_RECEIVER_GRPC_POOL_QUEUE_SIZE:0}
    gRPCThreadPoolSize: ${SW_RECEIVER_GRPC_THREAD_POOL_SIZE:0}
    gRPCSslEnabled: ${SW_RECEIVER_GRPC_SSL_ENABLED:false}
    gRPCSslKeyPath: ${SW_RECEIVER_GRPC_SSL_KEY_PATH:""}
    gRPCSslCertChainPath: ${SW_RECEIVER_GRPC_SSL_CERT_CHAIN_PATH:""}
    authentication: ${SW_AUTHENTICATION:""}
receiver-register:
  selector: ${SW_RECEIVER_REGISTER:default}
  default:

receiver-trace:
  selector: ${SW_RECEIVER_TRACE:default}
  default:

receiver-jvm:
  selector: ${SW_RECEIVER_JVM:default}
  default:

receiver-clr:
  selector: ${SW_RECEIVER_CLR:default}
  default:

receiver-profile:
  selector: ${SW_RECEIVER_PROFILE:default}
  default:

service-mesh:
  selector: ${SW_SERVICE_MESH:default}
  default:

envoy-metric:
  selector: ${SW_ENVOY_METRIC:default}
  default:
    acceptMetricsService: ${SW_ENVOY_METRIC_SERVICE:true}
    alsHTTPAnalysis: ${SW_ENVOY_METRIC_ALS_HTTP_ANALYSIS:""}
    # `k8sServiceNameRule` allows you to customize the service name in ALS via Kubernetes metadata,
    # the available variables are `pod`, `service`, f.e., you can use `${service.metadata.name}-${pod.metadata.labels.version}`
    # to append the version number to the service name.
    # Be careful, when using environment variables to pass this configuration, use single quotes(`''`) to avoid it being evaluated by the shell.
    k8sServiceNameRule: ${K8S_SERVICE_NAME_RULE:"${service.metadata.name}"}

prometheus-fetcher:
  selector: ${SW_PROMETHEUS_FETCHER:-}
  default:
    enabledRules: ${SW_PROMETHEUS_FETCHER_ENABLED_RULES:"self"}

kafka-fetcher:
  selector: ${SW_KAFKA_FETCHER:-}
  default:
    bootstrapServers: ${SW_KAFKA_FETCHER_SERVERS:localhost:9092}
    partitions: ${SW_KAFKA_FETCHER_PARTITIONS:3}
    replicationFactor: ${SW_KAFKA_FETCHER_PARTITIONS_FACTOR:2}
    enableMeterSystem: ${SW_KAFKA_FETCHER_ENABLE_METER_SYSTEM:false}
    isSharding: ${SW_KAFKA_FETCHER_IS_SHARDING:false}
    consumePartitions: ${SW_KAFKA_FETCHER_CONSUME_PARTITIONS:""}
    kafkaHandlerThreadPoolSize: ${SW_KAFKA_HANDLER_THREAD_POOL_SIZE:-1}
    kafkaHandlerThreadPoolQueueSize: ${SW_KAFKA_HANDLER_THREAD_POOL_QUEUE_SIZE:-1}

receiver-meter:
  selector: ${SW_RECEIVER_METER:default}
  default:

receiver-otel:
  selector: ${SW_OTEL_RECEIVER:-}
  default:
    enabledHandlers: ${SW_OTEL_RECEIVER_ENABLED_HANDLERS:"oc"}
    enabledOcRules: ${SW_OTEL_RECEIVER_ENABLED_OC_RULES:"istio-controlplane"}

receiver_zipkin:
  selector: ${SW_RECEIVER_ZIPKIN:-}
  default:
    host: ${SW_RECEIVER_ZIPKIN_HOST:0.0.0.0}
    port: ${SW_RECEIVER_ZIPKIN_PORT:9411}
    contextPath: ${SW_RECEIVER_ZIPKIN_CONTEXT_PATH:/}
    jettyMinThreads: ${SW_RECEIVER_ZIPKIN_JETTY_MIN_THREADS:1}
    jettyMaxThreads: ${SW_RECEIVER_ZIPKIN_JETTY_MAX_THREADS:200}
    jettyIdleTimeOut: ${SW_RECEIVER_ZIPKIN_JETTY_IDLE_TIMEOUT:30000}
    jettyAcceptorPriorityDelta: ${SW_RECEIVER_ZIPKIN_JETTY_DELTA:0}
    jettyAcceptQueueSize: ${SW_RECEIVER_ZIPKIN_QUEUE_SIZE:0}

receiver_jaeger:
  selector: ${SW_RECEIVER_JAEGER:-}
  default:
    gRPCHost: ${SW_RECEIVER_JAEGER_HOST:0.0.0.0}
    gRPCPort: ${SW_RECEIVER_JAEGER_PORT:14250}

receiver-browser:
  selector: ${SW_RECEIVER_BROWSER:default}
  default:
    # The sample rate precision is 1/10000. 10000 means 100% sample in default.
    sampleRate: ${SW_RECEIVER_BROWSER_SAMPLE_RATE:10000}

query:
  selector: ${SW_QUERY:graphql}
  graphql:
    path: ${SW_QUERY_GRAPHQL_PATH:/graphql}

alarm:
  selector: ${SW_ALARM:default}
  default:

telemetry:
  selector: ${SW_TELEMETRY:none}
  none:
  prometheus:
    host: ${SW_TELEMETRY_PROMETHEUS_HOST:0.0.0.0}
    port: ${SW_TELEMETRY_PROMETHEUS_PORT:1234}
    sslEnabled: ${SW_TELEMETRY_PROMETHEUS_SSL_ENABLED:false}
    sslKeyPath: ${SW_TELEMETRY_PROMETHEUS_SSL_KEY_PATH:""}
    sslCertChainPath: ${SW_TELEMETRY_PROMETHEUS_SSL_CERT_CHAIN_PATH:""}

configuration:
  selector: ${SW_CONFIGURATION:none}
  none:
  grpc:
    host: ${SW_DCS_SERVER_HOST:""}
    port: ${SW_DCS_SERVER_PORT:80}
    clusterName: ${SW_DCS_CLUSTER_NAME:SkyWalking}
    period: ${SW_DCS_PERIOD:20}
  apollo:
    apolloMeta: ${SW_CONFIG_APOLLO:http://localhost:8080}
    apolloCluster: ${SW_CONFIG_APOLLO_CLUSTER:default}
    apolloEnv: ${SW_CONFIG_APOLLO_ENV:""}
    appId: ${SW_CONFIG_APOLLO_APP_ID:skywalking}
    period: ${SW_CONFIG_APOLLO_PERIOD:5}
  zookeeper:
    period: ${SW_CONFIG_ZK_PERIOD:60} # Unit seconds, sync period. Default fetch every 60 seconds.
    nameSpace: ${SW_CONFIG_ZK_NAMESPACE:/default}
    hostPort: ${SW_CONFIG_ZK_HOST_PORT:localhost:2181}
    # Retry Policy
    baseSleepTimeMs: ${SW_CONFIG_ZK_BASE_SLEEP_TIME_MS:1000} # initial amount of time to wait between retries
    maxRetries: ${SW_CONFIG_ZK_MAX_RETRIES:3} # max number of times to retry
  etcd:
    period: ${SW_CONFIG_ETCD_PERIOD:60} # Unit seconds, sync period. Default fetch every 60 seconds.
    group: ${SW_CONFIG_ETCD_GROUP:skywalking}
    serverAddr: ${SW_CONFIG_ETCD_SERVER_ADDR:localhost:2379}
    clusterName: ${SW_CONFIG_ETCD_CLUSTER_NAME:default}
  consul:
    # Consul host and ports, separated by comma, e.g. 1.2.3.4:8500,2.3.4.5:8500
    hostAndPorts: ${SW_CONFIG_CONSUL_HOST_AND_PORTS:1.2.3.4:8500}
    # Sync period in seconds. Defaults to 60 seconds.
    period: ${SW_CONFIG_CONSUL_PERIOD:60}
    # Consul aclToken
    aclToken: ${SW_CONFIG_CONSUL_ACL_TOKEN:""}
  k8s-configmap:
    period: ${SW_CONFIG_CONFIGMAP_PERIOD:60}
    namespace: ${SW_CLUSTER_K8S_NAMESPACE:default}
    labelSelector: ${SW_CLUSTER_K8S_LABEL:app=collector,release=skywalking}
  nacos:
    # Nacos Server Host
    serverAddr: ${SW_CONFIG_NACOS_SERVER_ADDR:127.0.0.1}
    # Nacos Server Port
    port: ${SW_CONFIG_NACOS_SERVER_PORT:8848}
    # Nacos Configuration Group
    group: ${SW_CONFIG_NACOS_SERVER_GROUP:skywalking}
    # Nacos Configuration namespace
    namespace: ${SW_CONFIG_NACOS_SERVER_NAMESPACE:}
    # Unit seconds, sync period. Default fetch every 60 seconds.
    period: ${SW_CONFIG_NACOS_PERIOD:60}
    # Nacos auth username
    username: ${SW_CONFIG_NACOS_USERNAME:""}
    password: ${SW_CONFIG_NACOS_PASSWORD:""}
    # Nacos auth accessKey
    accessKey: ${SW_CONFIG_NACOS_ACCESSKEY:""}
    secretKey: ${SW_CONFIG_NACOS_SECRETKEY:""}

exporter:
  selector: ${SW_EXPORTER:-}
  grpc:
    targetHost: ${SW_EXPORTER_GRPC_HOST:127.0.0.1}
    targetPort: ${SW_EXPORTER_GRPC_PORT:9870}

health-checker:
  selector: ${SW_HEALTH_CHECKER:-}
  default:
    checkIntervalSeconds: ${SW_HEALTH_CHECKER_INTERVAL_SECONDS:5}
Copy the code

View Code

2.4 Create & Start UI

docker run -d --name skywalking-ui \ --restart=always \ -e TZ=Asia/Shanghai \ -p 8101:8080 \ --link oap:oap \ -e SW_OAP_ADDRESS = oap: 12800 \ apache/skywalking - UI: 8.3.0Copy the code

2.5 Downloading the Source Code Package

Wget HTTP: / / https://mirrors.tuna.tsinghua.edu.cn/apache/skywalking/8.3.0/apache-skywalking-apm-8.3.0.tar.gzCopy the code

The source package on the official website was slow to download, so WE changed it to TUNA. After downloading it, unpack it in /opt directory and leave it alone for the time being. Agent will be used for this later.

V SkyWalking is deployed and connected

3.1 Generating the Springboot JAR Package

If you have any doubts about generating springbootJAR packages, check out this article. CentOS Deployment SpringBoot project from 0 to 1

3.2 Starting the JAR Package

nohup java -javaagent:/opt/apache-skywalking-apm-bin/agent/skywalking-agent.jar - Dskywalking. Agent. The service_name = toutou_blog - Dskywalking. Collector. Backend_service = 127.0.0.1:11800 - jar / data/package/learn - web - 0.0.1 - the SNAPSHOT. The jar - d - server port = 8100 &Copy the code

– javaAgent: specifies the probe path. Specify the agent package location. In the preceding steps, apache-Skywalking -apm-8.3.0.tar.gz has been decompressed to /opt. Therefore, the directory is /opt/ apache-Skywalking -apm-bin/agent/ Skywalking -agent.jar

– Dskywalking. Agent. Service_name: used to override the agent/config/agent. The config service name in the configuration file

– Dskywalking. Collector. Backend_service: used to override the agent/config/agent. The config service address in the configuration file

3.3 to access the UI

When accessing for the first time, you need to call the interface in SpringBoot, and then the Corresponding information will be loaded in the SkyWalking UI. The effect is shown in the following figure.

Topology/Topology:

Track/trace:

For more information about SkyWalking’s UI, check out the official introduction.

Other reference/learning materials:

• Apache SkyWalking official documentation
• SkyWalking Chinese blog
• Chinese version of SkyWalking Documentation (provided by community)

V Source code address

Github.com/toutouge/ja…

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