目录
强大的性能,无限的扩展能力
收集、组织和处理海量高速数据。当您将任何数据视为时序数据时,它都会更有价值。借助 InfluxDB,这个排名第一的时序平台旨在与 Telegraf 一起扩展。
查看入门方法
输入和输出集成概述
此插件通过 gRPC 从 OpenTelemetry 客户端和代理接收跟踪、指标和日志,从而实现对应用程序的全面可观测性。
此插件使用参数化的 SQL INSERT 语句将指标从 Telegraf 直接写入 MariaDB,从而提供了一种将指标存储在结构化关系表中的灵活方法。
集成详情
OpenTelemetry
OpenTelemetry 插件旨在接收来自客户端和代理的遥测数据,例如跟踪、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,监听传入的遥测数据,这使其与在定义的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,从而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测性要求,并确保数据无缝集成到 InfluxDB 等系统中。
MariaDB
Telegraf 中的 SQL 输出插件允许通过执行参数化的 SQL 语句将指标直接写入 SQL 兼容的数据库(如 MariaDB)。通过对 MySQL 驱动程序的支持,该插件与 MariaDB 无缝集成,以实现可靠的结构化指标存储。此设置非常适合喜欢基于 SQL 的分析或希望将指标与业务数据一起存储以进行统一查询的用户。MariaDB 是一个社区开发的、企业级的 MySQL 分支,强调性能、安全性和开放性。该插件支持将时序指标插入到自定义模式中,从而可以使用 SQL 连接器灵活地进行分析以及与 Metabase 或 Grafana 等 BI 工具集成。
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"
MariaDB
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com) clickhouse (ClickHouse)
driver = "mysql"
## Data source name
## The format of the data source name is different for each database driver.
## See the plugin readme for details.
data_source_name = "username:password@tcp(host:port)/dbname"
## 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})"
## SQL INSERT statement with placeholders. Telegraf will substitute values at runtime.
## table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"
## Table existence check template
## Available template variables:
## {TABLE} - tablename as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL
init_sql = "SET sql_mode='ANSI_QUOTES';"
## 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
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of the
## table
## Metric type to SQL type conversion
## The values on the left are the data types Telegraf has and the values on
## the right are the data types Telegraf will use when sending to a database.
##
## The database values used must be data types the destination database
## understands. It is up to the user to ensure that the selected data type is
## available in the database they are using. Refer to your database
## documentation for what data types are available and supported.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
# ## This setting controls the behavior of the unsigned value. By default the
# ## setting will take the integer value and append the unsigned value to it. The other
# ## option is "literal", which will use the actual value the user provides to
# ## the unsigned option. This is useful for a database like ClickHouse where
# ## the unsigned value should use a value like "uint64".
# # conversion_style = "unsigned_suffix"
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,当用户发起一个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其代码所需的见解。
-
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,收集模拟更高负载下的实时指标和跟踪。这种方法有助于评估应用程序组件的弹性,并抢先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测性平台。例如,将其集成到 CI/CD 管道中以监控构建和部署,同时收集日志以帮助实时诊断故障或性能问题。
MariaDB
-
商业智能集成:将应用程序性能指标直接存储到 MariaDB 中,并将其连接到 Metabase 或 Apache Superset 等 BI 工具。这种设置允许将运营数据与业务 KPI 混合以实现统一的仪表板,从而提高跨部门的可见性。
-
具有历史指标的合规性报告:使用此插件将指标记录到 MariaDB 中以用于审计和合规性用例。关系模型支持使用时间戳条目精确查询过去的性能指标,从而支持法规文档。
-
基于 SQL 逻辑的自定义警报:将指标插入 MariaDB,并使用自定义 SQL 查询来定义警报阈值或条件。与 cron 作业或计划脚本结合使用,可以实现传统指标平台无法实现的高级警报工作流程。
-
物联网传感器指标存储:通过 Telegraf 收集来自物联网设备的传感器数据,并使用规范化模式将其存储在 MariaDB 中。这种方法具有成本效益,并且可以与现有的基于 SQL 的系统良好集成,以进行实时或历史分析。
反馈
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强大的性能,无限的扩展能力
收集、组织和处理海量高速数据。当您将任何数据视为时序数据时,它都会更有价值。借助 InfluxDB,这个排名第一的时序平台旨在与 Telegraf 一起扩展。
查看入门方法