目录
输入和输出集成概述
Fluentd 输入插件从 Fluentd 的 in_monitor 插件端点收集指标。 它提供对各种插件指标的洞察,同时允许自定义配置以减少序列基数。
AWS Timestream Telegraf 插件使用户能够将指标直接发送到 Amazon 的 Timestream 服务,该服务专为时序数据管理而设计。 此插件提供各种配置选项,用于身份验证、数据组织和保留设置。
集成详情
Fluentd
此插件从 in_monitor 插件提供的 Fluentd 插件端点收集指标。 它从 /api/plugin.json 资源读取数据,并允许根据插件类型排除特定插件。
AWS Timestream
此插件旨在高效地将指标写入 Amazon 的 Timestream 服务,这是一种为物联网和运营应用程序优化的时序数据库。 通过此插件,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、承担的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——是使用单表还是多表,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度量记录,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的 AWS 错误相关的常见问题的机制,例如用于节流的重试逻辑以及根据需要创建表的能力。
配置
Fluentd
[[inputs.fluentd]]
## This plugin reads information exposed by fluentd (using /api/plugins.json endpoint).
##
## Endpoint:
## - only one URI is allowed
## - https is not supported
endpoint = "http://localhost:24220/api/plugins.json"
## Define which plugins have to be excluded (based on "type" field - e.g. monitor_agent)
exclude = [
"monitor_agent",
"dummy",
]
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
Fluentd
- 基本配置:设置 Fluentd 输入插件以从您的 Fluentd 实例的监控端点收集指标,确保您能够跟踪性能和使用统计信息。
- 排除插件:使用
exclude
选项忽略特定插件的指标,这些指标对于您的监控需求不是必需的,从而简化数据收集并专注于重要事项。 - 自定义插件 ID:在您的 Fluentd 配置中实现 `@id` 参数以保持一致的 `plugin_id`,这有助于避免频繁重启期间出现高序列基数的问题。
AWS Timestream
-
物联网数据指标:使用 Timestream 插件将来自物联网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:利用 Timestream 以及应用程序监控工具来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。
-
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留较旧的数据。 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。
-
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。 通过创建统一的性能指标数据库,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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