目录
输入和输出集成概述
此插件通过 gRPC 接收来自 OpenTelemetry 客户端和代理的跟踪、指标和日志,从而实现对应用程序的全面可观察性。
Telegraf 的 SQL 插件有助于将指标存储在 SQL 数据库中。当配置为 Microsoft SQL Server 时,它支持特定的 DSN 格式和模式要求,从而实现与 SQL Server 的无缝集成。
集成详情
OpenTelemetry
OpenTelemetry 插件旨在接收遥测数据,例如来自客户端和代理的跟踪、指标和日志,这些客户端和代理通过 gRPC 实现 OpenTelemetry。此插件启动一个 gRPC 服务来侦听传入的遥测数据,这使其与按定义的时间间隔收集指标的标准插件不同。OpenTelemetry 生态系统通过提供一种供应商中立的方式来检测、生成、收集和导出遥测数据,帮助开发人员观察和理解其应用程序的性能。此插件的主要功能包括可自定义的连接超时、传入数据的可调整最大消息大小,以及用于指定跨度、日志和配置文件维度以标记传入指标的选项。凭借这种灵活性,组织可以定制其遥测数据收集,以满足精确的可观察性要求,并确保将数据无缝集成到 InfluxDB 等系统中。
Microsoft SQL Server
Telegraf 的 Microsoft SQL Server SQL 输出插件旨在通过动态创建与传入数据结构匹配的表和列来捕获和存储指标数据。此集成利用 go-mssqldb 驱动程序,该驱动程序通过包含服务器、端口和数据库详细信息的 DSN 遵循 SQL Server 连接协议。尽管由于单元测试有限,该驱动程序被认为是实验性的,但它为动态模式生成和数据插入提供了强大的支持,从而可以详细记录系统性能的时间戳记录。这种灵活性使其成为需要可靠且精细的指标日志记录环境的宝贵工具,尽管其状态为实验性。
配置
OpenTelemetry
[[inputs.opentelemetry]]
  ## Override the default (0.0.0.0:4317) destination OpenTelemetry gRPC service
  ## address:port
  # service_address = "0.0.0.0:4317"
  ## Override the default (5s) new connection timeout
  # timeout = "5s"
  ## gRPC Maximum Message Size
  # max_msg_size = "4MB"
  ## Override the default span attributes to be used as line protocol tags.
  ## These are always included as tags:
  ## - trace ID
  ## - span ID
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  # span_dimensions = ["service.name", "span.name"]
  ## Override the default log record attributes to be used as line protocol tags.
  ## These are always included as tags, if available:
  ## - trace ID
  ## - span ID
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  ## When using InfluxDB for both logs and traces, be certain that log_record_dimensions
  ## matches the span_dimensions value.
  # log_record_dimensions = ["service.name"]
  ## Override the default profile attributes to be used as line protocol tags.
  ## These are always included as tags, if available:
  ## - profile_id
  ## - address
  ## - sample
  ## - sample_name
  ## - sample_unit
  ## - sample_type
  ## - sample_type_unit
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  # profile_dimensions = []
  ## Override the default (prometheus-v1) metrics schema.
  ## Supports: "prometheus-v1", "prometheus-v2"
  ## For more information about the alternatives, read the Prometheus input
  ## plugin notes.
  # metrics_schema = "prometheus-v1"
  ## Optional TLS Config.
  ## For advanced options: https://github.com/influxdata/telegraf/blob/v1.18.3/docs/TLS.md
  ##
  ## Set one or more allowed client CA certificate file names to
  ## enable mutually authenticated TLS connections.
  # tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
  ## Add service certificate and key.
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
Microsoft SQL Server
[[outputs.sql]]
  ## Database driver
  ## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
  ## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
  driver = "mssql"
  ## Data source name
  ## For Microsoft SQL Server, the DSN typically includes the server, port, username, password, and database name.
  ## Example DSN: "sqlserver://username:password@localhost:1433?database=telegraf"
  data_source_name = "sqlserver://username:password@localhost:1433?database=telegraf"
  ## Timestamp column name
  timestamp_column = "timestamp"
  ## Table creation template
  ## Available template variables:
  ##  {TABLE}        - table name as a quoted identifier
  ##  {TABLELITERAL} - table name as a quoted string literal
  ##  {COLUMNS}      - column definitions (list of quoted identifiers and types)
  table_template = "CREATE TABLE {TABLE} ({COLUMNS})"
  ## Table existence check template
  ## Available template variables:
  ##  {TABLE} - table name as a quoted identifier
  table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
  ## Initialization SQL (optional)
  init_sql = ""
  ## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time.
  connection_max_idle_time = "0s"
  ## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age.
  connection_max_lifetime = "0s"
  ## Maximum number of connections in the idle connection pool. 0 means unlimited.
  connection_max_idle = 2
  ## Maximum number of open connections to the database. 0 means unlimited.
  connection_max_open = 0
  ## Metric type to SQL type conversion
  ## You can customize the mapping if needed.
  #[outputs.sql.convert]
  #  integer       = "INT"
  #  real          = "DOUBLE"
  #  text          = "TEXT"
  #  timestamp     = "TIMESTAMP"
  #  defaultvalue  = "TEXT"
  #  unsigned      = "UNSIGNED"
  #  bool          = "BOOL"
输入和输出集成示例
OpenTelemetry
- 
    跨服务的统一监控:使用 OpenTelemetry 插件收集和整合 Kubernetes 环境中各种微服务的遥测数据。通过使用 OpenTelemetry 检测每个服务,您可以利用此插件收集应用程序性能和依赖关系的整体视图,从而更快地进行故障排除并提高复杂系统的可靠性。 
- 
    通过跟踪增强调试:实施此插件以捕获流经多个服务的请求的端到端跟踪。例如,当用户发起触发多个后端服务的事务时,OpenTelemetry 插件可以记录详细的跟踪,突出显示性能瓶颈,从而为开发人员提供调试问题和优化代码所需的见解。 
- 
    动态负载测试和性能监控:在负载测试阶段利用此插件的功能,通过在模拟更高负载下收集实时指标和跟踪。此方法有助于评估应用程序组件的弹性,并主动识别潜在的性能下降,从而确保在生产环境中获得流畅的用户体验。 
- 
    用于实时监控的集成日志记录和指标:将 OpenTelemetry 插件与日志记录框架结合使用,以收集实时日志以及指标数据,从而创建一个强大的可观察性平台。例如,将其集成到 CI/CD 管道中以监控构建和部署,同时收集有助于实时诊断故障或性能问题的日志。 
Microsoft SQL Server
- 
    企业应用监控:利用此插件捕获在 SQL Server 上运行的企业应用程序的详细性能指标。此设置允许 IT 团队分析系统性能、跟踪事务时间并识别跨复杂、多层环境的瓶颈。 
- 
    动态基础设施审计:部署此插件以在 SQL Server 中创建基础设施变更和性能指标的动态审计日志。此用例非常适合需要实时监控和系统性能历史分析以进行合规性和优化的组织。 
- 
    自动化性能基准测试:使用此插件持续记录和分析 SQL Server 数据库的性能指标。这实现了自动化基准测试,其中将历史数据与当前性能进行比较,从而有助于快速识别服务中的异常或降级。 
- 
    集成 DevOps 仪表板:将此插件与 DevOps 监控工具集成,以将 SQL Server 的实时指标馈送到集中式仪表板中。这提供了应用程序运行状况的整体视图,使团队可以将 SQL Server 性能与应用程序级别的事件相关联,从而实现更快的故障排除和主动维护。 
反馈
感谢您成为我们社区的一份子!如果您有任何一般性反馈或在这些页面上发现任何错误,我们欢迎并鼓励您提供意见。请在 InfluxDB 社区 Slack 中提交您的反馈。