目录
输入和输出集成概述
NSQ Telegraf 插件从 NSQD 消息传递系统读取指标,从而实现实时数据处理和监控。
AWS Timestream Telegraf 插件使用户能够直接将指标发送到 Amazon 的 Timestream 服务,该服务专为时序数据管理而设计。此插件为身份验证、数据组织和保留设置提供了多种配置选项。
集成详情
NSQ
NSQ 插件与实时消息传递平台 NSQ 接口,从而能够从 NSQD 读取消息。此插件被归类为服务插件,这意味着它主动监听指标和事件,而不是定期轮询它们。该插件注重可靠性,通过跟踪未传递的消息直到输出确认,从而防止数据丢失。该插件允许进行配置,例如指定 NSQLookupd 端点、主题和通道,并且它支持多种数据格式,以实现数据处理的灵活性。
AWS Timestream
此插件旨在高效地将指标写入 Amazon 的 Timestream 服务,Timestream 服务是专为 IoT 和运营应用程序优化的时序数据库。借助此插件,Telegraf 可以发送从各种来源收集的数据,并支持灵活的配置,用于身份验证、数据组织和保留管理。它利用凭证链进行身份验证,允许各种方法,例如 Web 身份、承担角色和共享配置文件。用户可以定义指标在 Timestream 中的组织方式——是使用单个表还是多个表,以及控制磁存储和内存存储的保留期限等方面。一个关键特性是它能够处理多指标记录,从而实现高效的数据摄取并帮助减少多次写入的开销。在错误处理方面,该插件包含用于解决与数据写入期间 AWS 错误相关的常见问题的机制,例如用于限制的重试逻辑以及根据需要创建表的能力。
配置
NSQ
# Read metrics from NSQD topic(s)
[[inputs.nsq_consumer]]
## Server option still works but is deprecated, we just prepend it to the nsqd array.
# server = "localhost:4150"
## An array representing the NSQD TCP HTTP Endpoints
nsqd = ["localhost:4150"]
## An array representing the NSQLookupd HTTP Endpoints
nsqlookupd = ["localhost:4161"]
topic = "telegraf"
channel = "consumer"
max_in_flight = 100
## Max undelivered messages
## This plugin uses tracking metrics, which ensure messages are read to
## outputs before acknowledging them to the original broker to ensure data
## is not lost. This option sets the maximum messages to read from the
## broker that have not been written by an output.
##
## This value needs to be picked with awareness of the agent's
## metric_batch_size value as well. Setting max undelivered messages too high
## can result in a constant stream of data batches to the output. While
## setting it too low may never flush the broker's messages.
# max_undelivered_messages = 1000
## Data format to consume.
## Each data format has its own unique set of configuration options, read
## more about them here:
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
data_format = "influx"
AWS Timestream
[[outputs.timestream]]
## Amazon Region
region = "us-east-1"
## Amazon Credentials
## Credentials are loaded in the following order:
## 1) Web identity provider credentials via STS if role_arn and web_identity_token_file are specified
## 2) Assumed credentials via STS if role_arn is specified
## 3) explicit credentials from 'access_key' and 'secret_key'
## 4) shared profile from 'profile'
## 5) environment variables
## 6) shared credentials file
## 7) EC2 Instance Profile
#access_key = ""
#secret_key = ""
#token = ""
#role_arn = ""
#web_identity_token_file = ""
#role_session_name = ""
#profile = ""
#shared_credential_file = ""
## Endpoint to make request against, the correct endpoint is automatically
## determined and this option should only be set if you wish to override the
## default.
## ex: endpoint_url = "http://localhost:8000"
# endpoint_url = ""
## Timestream database where the metrics will be inserted.
## The database must exist prior to starting Telegraf.
database_name = "yourDatabaseNameHere"
## Specifies if the plugin should describe the Timestream database upon starting
## to validate if it has access necessary permissions, connection, etc., as a safety check.
## If the describe operation fails, the plugin will not start
## and therefore the Telegraf agent will not start.
describe_database_on_start = false
## Specifies how the data is organized in Timestream.
## Valid values are: single-table, multi-table.
## When mapping_mode is set to single-table, all of the data is stored in a single table.
## When mapping_mode is set to multi-table, the data is organized and stored in multiple tables.
## The default is multi-table.
mapping_mode = "multi-table"
## Specifies if the plugin should create the table, if the table does not exist.
create_table_if_not_exists = true
## Specifies the Timestream table magnetic store retention period in days.
## Check Timestream documentation for more details.
## NOTE: This property is valid when create_table_if_not_exists = true.
create_table_magnetic_store_retention_period_in_days = 365
## Specifies the Timestream table memory store retention period in hours.
## Check Timestream documentation for more details.
## NOTE: This property is valid when create_table_if_not_exists = true.
create_table_memory_store_retention_period_in_hours = 24
## Specifies how the data is written into Timestream.
## Valid values are: true, false
## When use_multi_measure_records is set to true, all of the tags and fields are stored
## as a single row in a Timestream table.
## When use_multi_measure_record is set to false, Timestream stores each field in a
## separate table row, thereby storing the tags multiple times (once for each field).
## The recommended setting is true.
## The default is false.
use_multi_measure_records = "false"
## Specifies the measure_name to use when sending multi-measure records.
## NOTE: This property is valid when use_multi_measure_records=true and mapping_mode=multi-table
measure_name_for_multi_measure_records = "telegraf_measure"
## Specifies the name of the table to write data into
## NOTE: This property is valid when mapping_mode=single-table.
# single_table_name = ""
## Specifies the name of dimension when all of the data is being stored in a single table
## and the measurement name is transformed into the dimension value
## (see Mapping data from Influx to Timestream for details)
## NOTE: This property is valid when mapping_mode=single-table.
# single_table_dimension_name_for_telegraf_measurement_name = "namespace"
## Only valid and optional if create_table_if_not_exists = true
## Specifies the Timestream table tags.
## Check Timestream documentation for more details
# create_table_tags = { "foo" = "bar", "environment" = "dev"}
## Specify the maximum number of parallel go routines to ingest/write data
## If not specified, defaulted to 1 go routines
max_write_go_routines = 25
## Please see README.md to know how line protocol data is mapped to Timestream
##
输入和输出集成示例
NSQ
-
实时分析仪表板:将此插件与可视化工具集成,以创建仪表板,显示来自 NSQ 中各种主题的实时指标。通过订阅特定主题,用户可以动态监控系统健康状况和应用程序性能,从而立即获得洞察力并及时响应任何异常。
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事件驱动的自动化:将 NSQ 与无服务器架构相结合,以基于传入消息触发自动化工作流程。此用例可能涉及处理机器学习模型的数据或响应应用程序中的用户操作,从而通过快速处理来简化操作并增强用户体验。
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多服务通信中心:在分布式架构中,使用 NSQ 插件充当不同微服务之间的集中式消息传递中心。通过使服务能够通过 NSQ 进行通信,开发人员可以确保可靠的消息传递,同时保持解耦的服务交互,从而显着提高可扩展性和弹性。
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指标聚合以增强监控:实施 NSQ 插件以聚合来自多个来源的指标,然后再将它们发送到分析工具。此设置使企业能够整合来自各种应用程序和服务的数据,从而创建统一的视图,以实现更好的决策和战略规划。
AWS Timestream
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IoT 数据指标:使用 Timestream 插件将来自 IoT 设备的实时指标发送到 Timestream,从而可以快速分析和可视化传感器数据。通过将设备读数组织成时序格式,用户可以跟踪趋势、识别异常并根据设备性能简化运营决策。
-
应用程序性能监控:将 Timestream 与应用程序监控工具结合使用,以发送有关服务性能随时间变化的指标。这种集成使工程师能够对应用程序性能进行历史分析,将其与业务指标相关联,并根据随时间查看的使用模式优化资源分配。
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自动化数据归档:配置 Timestream 插件以将数据写入 Timestream,同时管理保留期限。此设置可以自动化归档策略,确保根据预定义标准保存较旧的数据。这对于合规性和历史分析尤其有用,使企业能够以最少的人工干预来维护其数据生命周期。
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多应用程序指标聚合:利用 Timestream 插件将来自多个应用程序的指标聚合到 Timestream 中。通过创建性能指标的统一数据库,组织可以获得跨各种服务的整体洞察力,从而提高对系统范围性能的可见性并促进跨应用程序故障排除。
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