目录
输入和输出集成概述
Azure 事件中心输入插件允许 Telegraf 从 Azure 事件中心和 Azure IoT 中心消费数据,从而能够高效地处理数据和监控来自这些云服务的事件流。
Dynatrace 插件允许用户将 Telegraf 收集的指标直接发送到 Dynatrace 进行监控和分析。此集成增强了系统和应用程序的可观测性,为性能和运营健康状况提供了有价值的见解。
集成详情
Azure 事件中心
此插件充当 Azure 事件中心和 Azure IoT 中心的消费者,允许用户高效地从这些平台摄取数据流。Azure 事件中心是一个高度可扩展的数据流平台和事件摄取服务,能够每秒接收和处理数百万个事件,而 Azure IoT 中心支持 IoT 应用程序中安全的设备到云和云到设备通信。事件中心输入插件与这些服务无缝交互,提供可靠的消息消费和流处理能力。主要功能包括消费者组的动态管理、防止数据丢失的消息跟踪以及用于预取计数、用户代理和元数据处理的可自定义设置。此插件旨在支持各种用例,包括实时遥测数据收集、IoT 数据处理以及与更广泛的 Azure 生态系统中的各种数据分析和监控工具集成。
Dynatrace
Telegraf 的 Dynatrace 插件有助于通过 Dynatrace Metrics API V2 将指标传输到 Dynatrace 平台。此插件可以在两种模式下运行:它可以与 Dynatrace OneAgent 一起运行,后者自动执行身份验证,或者它可以以独立配置运行,这需要手动指定 URL 和 API 令牌,用于没有 OneAgent 的环境。除非明确配置为使用可用的配置选项将某些指标视为增量计数器,否则该插件主要将指标报告为仪表。此功能使用户能够自定义发送到 Dynatrace 的指标的行为,从而利用该平台的强大功能进行全面的性能监控和可观测性。对于用户而言,确保 Dynatrace 和 Telegraf 都符合版本要求至关重要,从而在与 Dynatrace 生态系统集成时优化兼容性和性能。
配置
Azure 事件中心
[[inputs.eventhub_consumer]]
## The default behavior is to create a new Event Hub client from environment variables.
## This requires one of the following sets of environment variables to be set:
##
## 1) Expected Environment Variables:
## - "EVENTHUB_CONNECTION_STRING"
##
## 2) Expected Environment Variables:
## - "EVENTHUB_NAMESPACE"
## - "EVENTHUB_NAME"
## - "EVENTHUB_KEY_NAME"
## - "EVENTHUB_KEY_VALUE"
## 3) Expected Environment Variables:
## - "EVENTHUB_NAMESPACE"
## - "EVENTHUB_NAME"
## - "AZURE_TENANT_ID"
## - "AZURE_CLIENT_ID"
## - "AZURE_CLIENT_SECRET"
## Uncommenting the option below will create an Event Hub client based solely on the connection string.
## This can either be the associated environment variable or hard coded directly.
## If this option is uncommented, environment variables will be ignored.
## Connection string should contain EventHubName (EntityPath)
# connection_string = ""
## Set persistence directory to a valid folder to use a file persister instead of an in-memory persister
# persistence_dir = ""
## Change the default consumer group
# consumer_group = ""
## By default the event hub receives all messages present on the broker, alternative modes can be set below.
## The timestamp should be in https://github.com/toml-lang/toml#offset-date-time format (RFC 3339).
## The 3 options below only apply if no valid persister is read from memory or file (e.g. first run).
# from_timestamp =
# latest = true
## Set a custom prefetch count for the receiver(s)
# prefetch_count = 1000
## Add an epoch to the receiver(s)
# epoch = 0
## Change to set a custom user agent, "telegraf" is used by default
# user_agent = "telegraf"
## To consume from a specific partition, set the partition_ids option.
## An empty array will result in receiving from all partitions.
# partition_ids = ["0","1"]
## 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
## Set either option below to true to use a system property as timestamp.
## You have the choice between EnqueuedTime and IoTHubEnqueuedTime.
## It is recommended to use this setting when the data itself has no timestamp.
# enqueued_time_as_ts = true
# iot_hub_enqueued_time_as_ts = true
## Tags or fields to create from keys present in the application property bag.
## These could for example be set by message enrichments in Azure IoT Hub.
# application_property_tags = []
# application_property_fields = []
## Tag or field name to use for metadata
## By default all metadata is disabled
# sequence_number_field = "SequenceNumber"
# enqueued_time_field = "EnqueuedTime"
# offset_field = "Offset"
# partition_id_tag = "PartitionID"
# partition_key_tag = "PartitionKey"
# iot_hub_device_connection_id_tag = "IoTHubDeviceConnectionID"
# iot_hub_auth_generation_id_tag = "IoTHubAuthGenerationID"
# iot_hub_connection_auth_method_tag = "IoTHubConnectionAuthMethod"
# iot_hub_connection_module_id_tag = "IoTHubConnectionModuleID"
# iot_hub_enqueued_time_field = "IoTHubEnqueuedTime"
## 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"
Dynatrace
[[outputs.dynatrace]]
## For usage with the Dynatrace OneAgent you can omit any configuration,
## the only requirement is that the OneAgent is running on the same host.
## Only setup environment url and token if you want to monitor a Host without the OneAgent present.
##
## Your Dynatrace environment URL.
## For Dynatrace OneAgent you can leave this empty or set it to "http://127.0.0.1:14499/metrics/ingest" (default)
## For Dynatrace SaaS environments the URL scheme is "https://{your-environment-id}.live.dynatrace.com/api/v2/metrics/ingest"
## For Dynatrace Managed environments the URL scheme is "https://{your-domain}/e/{your-environment-id}/api/v2/metrics/ingest"
url = ""
## Your Dynatrace API token.
## Create an API token within your Dynatrace environment, by navigating to Settings > Integration > Dynatrace API
## The API token needs data ingest scope permission. When using OneAgent, no API token is required.
api_token = ""
## Optional prefix for metric names (e.g.: "telegraf")
prefix = "telegraf"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Optional flag for ignoring tls certificate check
# insecure_skip_verify = false
## Connection timeout, defaults to "5s" if not set.
timeout = "5s"
## If you want metrics to be treated and reported as delta counters, add the metric names here
additional_counters = [ ]
## In addition or as an alternative to additional_counters, if you want metrics to be treated and
## reported as delta counters using regular expression pattern matching
additional_counters_patterns = [ ]
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of the
## table
## Optional dimensions to be added to every metric
# [outputs.dynatrace.default_dimensions]
# default_key = "default value"
输入和输出集成示例
Azure 事件中心
-
实时 IoT 设备监控:使用 Azure 事件中心插件监控来自 IoT 设备(如传感器和执行器)的遥测数据。通过将设备数据流式传输到监控仪表板,组织可以深入了解系统性能、跟踪使用模式并快速响应异常情况。此设置允许对设备进行主动管理,从而提高运营效率并减少停机时间。
-
事件驱动的数据处理工作流:利用此插件触发数据处理工作流,以响应从 Azure 事件中心接收的事件。例如,当新事件到达时,它可以启动数据转换、聚合或存储过程,从而使企业能够更有效地自动化其工作流。此集成增强了响应能力并简化了跨系统的运营。
-
与分析平台集成:实施此插件以将事件数据导入到 Azure Synapse 或 Power BI 等分析平台。通过将实时流数据集成到分析工具中,组织可以执行全面的数据分析、推动商业智能工作并创建信息丰富的交互式可视化效果,从而为决策提供依据。
-
跨平台数据同步:利用 Azure 事件中心插件在不同的系统或平台之间同步数据流。通过从 Azure 事件中心消费数据并将其转发到数据库或云存储等其他系统,组织可以在其整个架构中维护一致且最新的信息,从而实现有凝聚力的数据策略。
Dynatrace
-
云基础设施监控:利用 Dynatrace 插件监控云基础设施设置,将来自 Telegraf 的实时指标馈送到 Dynatrace。此集成提供了资源利用率、应用程序性能和系统健康状况的整体视图,从而能够主动响应各种云环境中的性能问题。
-
自定义应用程序性能指标:通过配置 Dynatrace 输出插件以发送来自 Telegraf 的定制指标来实施自定义应用程序特定指标。通过利用附加的计数器和维度选项,开发团队可以获得与其应用程序运营要求精确对齐的见解,从而实现有针对性的优化工作。
-
多环境指标管理:对于运行多个 Dynatrace 环境(例如,生产、暂存和开发)的组织,请使用此插件从单个 Telegraf 实例管理所有环境的指标。通过正确配置端点和 API 令牌,团队可以在整个 SDLC 中保持一致的监控实践,确保在开发过程的早期检测到性能异常。
-
基于指标变化的自动警报:将 Dynatrace 输出插件与警报机制集成,该机制在特定指标超过定义的阈值时触发通知。这种情况涉及配置额外的计数器来监控关键的应用程序性能指标,从而能够快速采取补救措施以维持服务可用性和用户满意度。
反馈
感谢您成为我们社区的一份子!如果您有任何一般性反馈或在这些页面上发现任何错误,我们欢迎并鼓励您提供意见。请在 InfluxDB 社区 Slack 中提交您的反馈。