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,它都更有价值。借助 InfluxDB,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
此插件侦听通过 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。
OpenSearch 输出插件允许用户使用 HTTP 将指标直接发送到 OpenSearch 实例,从而促进 OpenSearch 生态系统内有效的数据管理和分析。
集成详情
AWS Data Firehose
AWS Data Firehose Telegraf 插件旨在通过 HTTP 接收来自 AWS Data Firehose 的指标。此插件侦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。与按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侦听器,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。
OpenSearch
OpenSearch Telegraf 插件通过 HTTP 与 OpenSearch 数据库集成,从而实现指标的简化收集和存储。作为一个专为 OpenSearch 2.x 版本设计的强大工具,该插件在提供强大功能的同时,还通过原始 Elasticsearch 插件提供与 1.x 版本的兼容性。此插件有助于在 OpenSearch 中创建和管理索引,自动管理模板并确保数据结构化以实现高效分析。该插件支持各种配置选项,例如索引名称、身份验证、运行状况检查和值处理,使其可以根据不同的操作要求进行定制。其功能使其对于希望利用 OpenSearch 的强大功能进行指标存储和查询的组织至关重要。
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"
OpenSearch
[[outputs.opensearch]]
## URLs
## The full HTTP endpoint URL for your OpenSearch instance. Multiple URLs can
## be specified as part of the same cluster, but only one URLs is used to
## write during each interval.
urls = ["http://node1.os.example.com:9200"]
## Index Name
## Target index name for metrics (OpenSearch will create if it not exists).
## This is a Golang template (see https://pkg.go.dev/text/template)
## You can also specify
## metric name (`{{.Name}}`), tag value (`{{.Tag "tag_name"}}`), field value (`{{.Field "field_name"}}`)
## If the tag does not exist, the default tag value will be empty string "".
## the timestamp (`{{.Time.Format "xxxxxxxxx"}}`).
## For example: "telegraf-{{.Time.Format \"2006-01-02\"}}-{{.Tag \"host\"}}" would set it to telegraf-2023-07-27-HostName
index_name = ""
## Timeout
## OpenSearch client timeout
# timeout = "5s"
## Sniffer
## Set to true to ask OpenSearch a list of all cluster nodes,
## thus it is not necessary to list all nodes in the urls config option
# enable_sniffer = false
## GZIP Compression
## Set to true to enable gzip compression
# enable_gzip = false
## Health Check Interval
## Set the interval to check if the OpenSearch nodes are available
## Setting to "0s" will disable the health check (not recommended in production)
# health_check_interval = "10s"
## Set the timeout for periodic health checks.
# health_check_timeout = "1s"
## HTTP basic authentication details.
# username = ""
# password = ""
## HTTP bearer token authentication details
# auth_bearer_token = ""
## Optional TLS Config
## Set to true/false to enforce TLS being enabled/disabled. If not set,
## enable TLS only if any of the other options are specified.
# tls_enable =
## Trusted root certificates for server
# tls_ca = "/path/to/cafile"
## Used for TLS client certificate authentication
# tls_cert = "/path/to/certfile"
## Used for TLS client certificate authentication
# tls_key = "/path/to/keyfile"
## Send the specified TLS server name via SNI
# tls_server_name = "kubernetes.example.com"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Template Config
## Manage templates
## Set to true if you want telegraf to manage its index template.
## If enabled it will create a recommended index template for telegraf indexes
# manage_template = true
## Template Name
## The template name used for telegraf indexes
# template_name = "telegraf"
## Overwrite Templates
## Set to true if you want telegraf to overwrite an existing template
# overwrite_template = false
## Document ID
## If set to true a unique ID hash will be sent as
## sha256(concat(timestamp,measurement,series-hash)) string. It will enable
## data resend and update metric points avoiding duplicated metrics with
## different id's
# force_document_id = false
## Value Handling
## Specifies the handling of NaN and Inf values.
## This option can have the following values:
## none -- do not modify field-values (default); will produce an error
## if NaNs or infs are encountered
## drop -- drop fields containing NaNs or infs
## replace -- replace with the value in "float_replacement_value" (default: 0.0)
## NaNs and inf will be replaced with the given number, -inf with the negative of that number
# float_handling = "none"
# float_replacement_value = 0.0
## Pipeline Config
## To use a ingest pipeline, set this to the name of the pipeline you want to use.
# use_pipeline = "my_pipeline"
## Pipeline Name
## Additionally, you can specify a tag name using the notation (`{{.Tag "tag_name"}}`)
## which will be used as the pipeline name (e.g. "{{.Tag \"os_pipeline\"}}").
## If the tag does not exist, the default pipeline will be used as the pipeline.
## If no default pipeline is set, no pipeline is used for the metric.
# default_pipeline = ""
输入和输出集成示例
AWS Data Firehose
-
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)的实时数据流式传输到分析平台中。这使数据团队能够分析传入数据,从而根据最新的指标实现快速洞察和运营调整。
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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,企业可以深入了解用户行为。这可以推动内容个性化策略或优化服务器架构,从而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,使团队能够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,以防止问题升级。
OpenSearch
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时间序列数据的动态索引:利用 OpenSearch Telegraf 插件为时间序列指标动态创建索引,确保数据以有组织的方式存储,从而有助于基于时间的查询。通过使用 Go 模板定义索引模式,用户可以利用该插件创建每日或每月索引,这可以大大简化数据管理和长期检索,从而提高分析性能。
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多租户应用程序的集中式日志记录:在多租户应用程序中实施 OpenSearch 插件,其中每个租户的日志都发送到单独的索引。这使得能够针对每个租户进行有针对性的分析和监控,同时保持数据隔离。通过利用索引名称模板功能,用户可以自动创建特定于租户的索引,这不仅简化了流程,还增强了租户数据的安全性和可访问性。
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与机器学习集成以进行异常检测:将 OpenSearch 插件与机器学习工具结合使用,以自动检测指标数据中的异常。通过配置插件以将实时指标发送到 OpenSearch,用户可以在传入的数据流上应用机器学习模型,以识别异常值或异常模式,从而促进主动监控和快速补救措施。
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使用 OpenSearch 增强监控仪表板:使用从 OpenSearch 收集的指标创建实时仪表板,以深入了解系统性能。通过将指标馈送到 OpenSearch,组织可以利用 OpenSearch Dashboards 可视化关键绩效指标,使运营团队能够快速评估运行状况和性能,并做出数据驱动的决策。
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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,它都更有价值。借助 InfluxDB,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