目录
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,提供实时数据摄取能力。
Telegraf Elasticsearch 插件无缝地将指标发送到 Elasticsearch 服务器。 该插件处理模板创建和动态索引管理,并支持各种 Elasticsearch 特有功能,以确保数据格式正确,以便存储和检索。
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 AWS 官方文档中概述的请求-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侦听器,等待传入的指标。 这允许从 AWS Data Firehose 实时数据摄取,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 连接以进行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,增强了其在涉及数据流和处理的各种用例中的灵活性。
Elasticsearch
此插件将指标写入 Elasticsearch,这是一个分布式、RESTful 的搜索和分析引擎,能够近乎实时地存储大量数据。 它旨在处理 Elasticsearch 5.x 到 7.x 版本,并利用其动态模板功能来正确管理数据类型映射。 该插件支持高级功能,例如模板管理、动态索引命名以及与 OpenSearch 的集成。 它还允许配置 Elasticsearch 节点的身份验证和运行状况监控。
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"
Elasticsearch
[[outputs.elasticsearch]]
## The full HTTP endpoint URL for your Elasticsearch instance
## Multiple urls can be specified as part of the same cluster,
## this means that only ONE of the urls will be written to each interval
urls = [ "http://node1.es.example.com:9200" ] # required.
## Elasticsearch client timeout, defaults to "5s" if not set.
timeout = "5s"
## Set to true to ask Elasticsearch a list of all cluster nodes,
## thus it is not necessary to list all nodes in the urls config option
enable_sniffer = false
## Set to true to enable gzip compression
enable_gzip = false
## Set the interval to check if the Elasticsearch 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.
## HTTP basic authentication details
# username = "telegraf"
# password = "mypassword"
## HTTP bearer token authentication details
# auth_bearer_token = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9"
## Index Config
## The target index for metrics (Elasticsearch will create if it not exists).
## You can use the date specifiers below to create indexes per time frame.
## The metric timestamp will be used to decide the destination index name
# %Y - year (2016)
# %y - last two digits of year (00..99)
# %m - month (01..12)
# %d - day of month (e.g., 01)
# %H - hour (00..23)
# %V - week of the year (ISO week) (01..53)
## Additionally, you can specify a tag name using the notation {{tag_name}}
## which will be used as part of the index name. If the tag does not exist,
## the default tag value will be used.
# index_name = "telegraf-{{host}}-%Y.%m.%d"
# default_tag_value = "none"
index_name = "telegraf-%Y.%m.%d" # required.
## Optional Index Config
## Set to true if Telegraf should use the "create" OpType while indexing
# use_optype_create = false
## 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
## Template Config
## 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
## The template name used for telegraf indexes
template_name = "telegraf"
## Set to true if you want telegraf to overwrite an existing template
overwrite_template = false
## 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
## 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"
## Additionally, you can specify a tag name using the notation {{tag_name}}
## which will be used as part of the pipeline name. 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.
# use_pipeline = "{{es_pipeline}}"
# default_pipeline = "my_pipeline"
#
# Custom HTTP headers
# To pass custom HTTP headers please define it in a given below section
# [outputs.elasticsearch.headers]
# "X-Custom-Header" = "custom-value"
## Template Index Settings
## Overrides the template settings.index section with any provided options.
## Defaults provided here in the config
# template_index_settings = {
# refresh_interval = "10s",
# mapping.total_fields.limit = 5000,
# auto_expand_replicas = "0-1",
# codec = "best_compression"
# }
输入和输出集成示例
AWS Data Firehose
-
实时数据分析: 使用 AWS Data Firehose 插件,组织可以从各种来源(例如应用程序日志或物联网设备)实时将数据流式传输到分析平台。 这使数据团队能够在生成传入数据时对其进行分析,从而根据最新的指标快速获得见解和进行运营调整。
-
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,以根据流量模式获得更好的性能。
-
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。
Elasticsearch
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基于时间的索引: 使用此插件将指标存储在 Elasticsearch 中,以根据收集的时间对每个指标进行索引。 例如,CPU 指标可以存储在名为
telegraf-2023.01.01
的每日索引中,从而可以轻松进行基于时间的查询和保留策略。 -
动态模板管理: 利用模板管理功能自动创建为您的指标量身定制的自定义模板。 这使您可以定义如何索引和分析不同的字段,而无需手动配置 Elasticsearch,从而确保用于查询的最佳数据结构。
-
OpenSearch 兼容性: 如果您正在使用 AWS OpenSearch,则可以通过激活兼容模式来配置此插件以实现无缝工作,从而确保您现有的 Elasticsearch 客户端保持功能,并与较新的集群设置兼容。
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