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并监控来自这些云服务的事件流。
Telegraf 的 SQL 插件允许在 SQL 数据库中无缝存储指标。当配置为 Snowflake 时,它采用专门的 DSN 格式和动态表创建,将指标映射到相应的模式。
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,允许用户有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。
Snowflake
Telegraf 的 SQL 插件旨在通过根据传入数据创建表和列,动态地将指标写入 SQL 数据库。当配置为 Snowflake 时,它采用 gosnowflake 驱动程序,该驱动程序使用 DSN,DSN 以紧凑的格式封装凭据、帐户详细信息和数据库配置。这种设置允许自动生成表,其中每个指标都记录有精确的时间戳,从而确保详细的历史跟踪。尽管此集成被认为是实验性的,但它利用了 Snowflake 强大的数据仓库功能,使其适用于可扩展的、基于云的分析和报告解决方案。
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"
Snowflake
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "snowflake"
## Data source name
## For Snowflake, the DSN format typically includes the username, password, account identifier, and optional warehouse, database, and schema.
## Example DSN: "username:password@account/warehouse/db/schema"
data_source_name = "username:password@account/warehouse/db/schema"
## Timestamp column name
timestamp_column = "timestamp"
## Table creation template
## Available template variables:
## {TABLE} - table name as a quoted identifier
## {TABLELITERAL} - table name as a quoted string literal
## {COLUMNS} - column definitions (list of quoted identifiers and types)
table_template = "CREATE TABLE {TABLE} ({COLUMNS})"
## Table existence check template
## Available template variables:
## {TABLE} - table name as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL (optional)
init_sql = ""
## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time.
connection_max_idle_time = "0s"
## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age.
connection_max_lifetime = "0s"
## Maximum number of connections in the idle connection pool. 0 means unlimited.
connection_max_idle = 2
## Maximum number of open connections to the database. 0 means unlimited.
connection_max_open = 0
## Metric type to SQL type conversion
## Defaults to ANSI/ISO SQL types unless overridden. Adjust if needed for Snowflake compatibility.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
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。这种设置允许对设备进行主动管理,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,使企业能够更有效地自动化其工作流。这种集成增强了响应能力并简化了跨系统的操作。
-
与分析平台集成:实施此插件以将事件数据输送到 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交互式可视化,从而为决策提供信息。
-
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保持一致且最新的信息,从而实现有凝聚力的数据策略。
Snowflake
-
基于云的数据湖集成:利用此插件将来自各种来源的实时指标流式传输到 Snowflake 中,从而创建集中式数据湖。这种集成支持云数据上的复杂分析和机器学习工作流。
-
动态商业智能仪表板:利用此插件从传入指标自动生成表,并将它们馈送到 BI 工具中。这使企业能够创建动态仪表板,可视化性能趋势和运营洞察,而无需手动模式管理。
-
可扩展的 IoT 分析:部署此插件以捕获来自 IoT 设备的高频数据到 Snowflake 中。此用例有助于传感器数据的聚合和分析,从而实现大规模的预测性维护和实时监控。
-
用于合规性的历史趋势分析:使用此插件在 Snowflake 中记录和存档详细的指标数据,然后可以查询这些数据以进行长期趋势分析和合规性报告。这种设置确保组织可以维护强大的审计跟踪并在需要时执行取证分析。
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