目录
输入和输出集成概述
此插件从 RabbitMQ 服务器读取指标,提供对消息传递系统的性能和状态的基本洞察。
Telegraf SQL 插件允许您将来自 Telegraf 的指标直接存储到 MySQL 数据库中,从而更轻松地分析和可视化收集的指标。
集成详情
RabbitMQ
Telegraf 的 RabbitMQ 插件允许用户通过 RabbitMQ 管理插件从 RabbitMQ 服务器收集指标。此功能对于监控 RabbitMQ 实例的性能和健康状况至关重要,RabbitMQ 实例广泛用于各种应用程序中的消息队列和处理。该插件提供对关键 RabbitMQ 指标的全面洞察,包括消息速率、队列深度和节点健康统计信息,从而使运营商能够维护其消息传递基础设施的最佳性能和稳健性。此外,它还支持用于安全管理敏感凭据的密钥存储,从而使与现有系统的集成更加顺畅。配置选项允许灵活指定要监控的节点、队列和交换机,为各种部署场景提供有价值的适应性。
MySQL
Telegraf 的 SQL 输出插件旨在通过基于传入指标动态创建表和列,将指标数据无缝写入 SQL 数据库。当配置为 MySQL 时,该插件利用 go-sql-driver/mysql,这需要启用 ANSI_QUOTES SQL 模式以确保正确处理带引号的标识符。这种动态模式创建方法确保每个指标都存储在其自己的表中,其结构源自其字段和标签,从而提供系统性能的详细、带时间戳的记录。该插件的灵活性使其能够处理高吞吐量环境,使其成为需要强大、精细的指标日志记录和历史数据分析的场景的理想选择。
配置
RabbitMQ
[[inputs.rabbitmq]]
## Management Plugin url. (default: http://localhost:15672)
# url = "http://localhost:15672"
## Tag added to rabbitmq_overview series; deprecated: use tags
# name = "rmq-server-1"
## Credentials
# username = "guest"
# password = "guest"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Optional request timeouts
## ResponseHeaderTimeout, if non-zero, specifies the amount of time to wait
## for a server's response headers after fully writing the request.
# header_timeout = "3s"
##
## client_timeout specifies a time limit for requests made by this client.
## Includes connection time, any redirects, and reading the response body.
# client_timeout = "4s"
## A list of nodes to gather as the rabbitmq_node measurement. If not
## specified, metrics for all nodes are gathered.
# nodes = ["rabbit@node1", "rabbit@node2"]
## A list of queues to gather as the rabbitmq_queue measurement. If not
## specified, metrics for all queues are gathered.
## Deprecated in 1.6: Use queue_name_include instead.
# queues = ["telegraf"]
## A list of exchanges to gather as the rabbitmq_exchange measurement. If not
## specified, metrics for all exchanges are gathered.
# exchanges = ["telegraf"]
## Metrics to include and exclude. Globs accepted.
## Note that an empty array for both will include all metrics
## Currently the following metrics are supported: "exchange", "federation", "node", "overview", "queue"
# metric_include = []
# metric_exclude = []
## Queues to include and exclude. Globs accepted.
## Note that an empty array for both will include all queues
# queue_name_include = []
# queue_name_exclude = []
## Federation upstreams to include and exclude specified as an array of glob
## pattern strings. Federation links can also be limited by the queue and
## exchange filters.
# federation_upstream_include = []
# federation_upstream_exclude = []
MySQL
[[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})"
## 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
RabbitMQ
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监控队列性能指标:使用 RabbitMQ 插件来跟踪队列性能随时间的变化。这包括设置监控仪表板,以可视化关键队列指标,例如消息速率、消费者数量和消息传递速率。借助此信息,团队可以通过分析趋势并根据数据做出关于扩展或优化其 RabbitMQ 配置的明智决策,从而主动解决任何瓶颈或性能问题。
-
系统健康状况告警:将 RabbitMQ 插件与告警系统集成,以通知运营团队 RabbitMQ 实例中潜在的问题。例如,如果未确认消息的数量达到临界阈值,或者队列变得不堪重负,则可以触发告警,从而可以立即进行调查并迅速采取补救措施以维持消息流的健康状况。
-
分析消息处理指标:使用该插件收集有关消息处理性能的详细指标,例如已发布、已确认和已重新传递的消息的速率。通过分析这些指标,团队可以评估其消息消费者应用程序的效率,并在必要时调整配置或代码,从而提高整体系统吞吐量和弹性。
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跨系统数据集成:利用 RabbitMQ 插件收集的指标来集成 RabbitMQ 与其他系统或服务之间的数据流。例如,使用收集的指标来驱动自动化工作流程或分析管道,这些管道利用在 RabbitMQ 中处理的消息,使组织能够优化工作流程并提高其生态系统中的数据敏捷性。
MySQL
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实时 Web 分析存储:利用该插件捕获网站性能指标并将它们存储在 MySQL 中。此设置使团队能够监控用户交互、分析流量模式并根据实时数据洞察动态调整站点功能。
-
物联网设备监控:利用该插件从物联网传感器网络收集指标并将它们记录到 MySQL 数据库中。此用例支持对设备健康状况和性能进行持续监控,从而实现预测性维护和对异常的即时响应。
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金融交易日志记录:记录具有精确时间戳的高频金融交易数据。这种方法支持强大的审计跟踪、实时欺诈检测以及用于合规性和报告的全面历史分析。
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应用程序性能基准测试:将该插件与应用程序性能监控系统集成,以将指标记录到 MySQL 中。这有助于进行详细的基准测试和随时间推移的趋势分析,使组织能够有效地识别性能瓶颈并优化资源分配。
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