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间序列数据时,它会更有价值。借助 InfluxDB,这个排名第一的时间序列平台旨在与 Telegraf 一起扩展。
查看入门方法
输入和输出集成概述
此插件监听通过 HTTP 从 AWS Data Firehose 以支持的数据格式发送的指标,提供实时数据摄取功能。
AWS Timestream Telegraf 插件使用户能够将指标直接发送到亚马逊的 Timestream 服务,该服务专为时间序列数据管理而设计。此插件为身份验证、数据组织和保留设置提供了各种配置选项。
集成详情
AWS Data Firehose
AWS Data Firehose Telegraf 插件旨在通过 HTTP 从 AWS Data Firehose 接收指标。此插件监听各种格式的传入数据,并根据官方 AWS 文档中概述的请求-响应模式对其进行处理。与以固定间隔运行的标准输入插件不同,此服务插件初始化一个保持活动状态的监听器,等待传入的指标。这允许从 AWS Data Firehose 实时摄取数据,使其适用于需要立即进行数据处理的场景。主要功能包括指定服务地址、路径以及支持 TLS 连接以实现安全数据传输的能力。此外,该插件还支持可选的身份验证密钥和自定义标签,从而增强了其在涉及数据流和处理的各种用例中的灵活性。
AWS Timestream
此插件旨在高效地将指标写入亚马逊的 Timestream 服务,Timestream 服务是一个针对物联网和运营应用程序优化的时间序列数据库。借助此插件,Telegraf 可以发送从各种来源收集的数据,并支持身份验证、数据组织和保留管理方面的灵活配置。它利用凭证链进行身份验证,从而允许各种方法,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,并有助于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数据写入期间与 AWS 错误相关的常见问题的机制,例如节流的重试逻辑以及根据需要创建表的能力。
配置
AWS Data Firehose
[[inputs.firehose]]
## Address and port to host HTTP listener on
service_address = ":8080"
## Paths to listen to.
# paths = ["/telegraf"]
## maximum duration before timing out read of the request
# read_timeout = "5s"
## maximum duration before timing out write of the response
# write_timeout = "5s"
## 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"
## Minimal TLS version accepted by the server
# tls_min_version = "TLS12"
## Optional access key to accept for authentication.
## AWS Data Firehose uses "x-amz-firehose-access-key" header to set the access key.
## If no access_key is provided (default), authentication is completely disabled and
## this plugin will accept all request ignoring the provided access-key in the request!
# access_key = "foobar"
## Optional setting to add parameters as tags
## If the http header "x-amz-firehose-common-attributes" is not present on the
## request, no corresponding tag will be added. The header value should be a
## json and should follow the schema as describe in the official documentation:
## https://docs.aws.amazon.com/firehose/latest/dev/httpdeliveryrequestresponse.html#requestformat
# parameter_tags = ["env"]
## 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
AWS Data Firehose
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实时数据分析:通过使用 AWS Data Firehose 插件,组织可以将来自各种来源(例如应用程序日志或物联网设备)的实时数据直接流式传输到分析平台。这使数据团队能够分析传入数据,从而根据最新的指标快速获得见解并进行运营调整。
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分析访问模式以进行优化:通过收集有关客户端如何通过 AWS Data Firehose 与应用程序交互的数据,企业可以获得有关用户行为的宝贵见解。这可以推动内容个性化策略或优化服务器架构,以根据流量模式获得更好的性能。
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自动化警报机制:通过此插件将 AWS Data Firehose 与警报系统集成,团队可以根据收集的特定指标设置自动化警报。例如,如果在输入数据中达到特定阈值,则警报可以触发运营团队调查潜在问题,以防问题升级。
AWS Timestream
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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间序列格式,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 和应用程序监控工具,随时间推移发送有关服务性能的指标。这种集成使工程师能够执行应用程序性能的历史分析,将其与业务指标相关联,并根据随时间推移查看的使用模式优化资源分配。
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自动化数据存档:配置 Timestream 插件以将数据写入 Timestream,同时管理保留期。此设置可以自动化存档策略,确保根据预定义的标准保留旧数据。这对于合规性和历史分析特别有用,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。通过创建统一的性能指标数据库,组织可以获得跨各种服务的整体见解,从而提高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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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间序列数据时,它会更有价值。借助 InfluxDB,这个排名第一的时间序列平台旨在与 Telegraf 一起扩展。
查看入门方法