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。InfluxDB 是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
Kinesis 插件使您能够从 Kinesis 数据流中读取数据,支持各种数据格式和配置。
此插件使用参数化的 SQL INSERT 语句将指标从 Telegraf 直接写入 MariaDB,提供了一种将指标存储在结构化关系表中的灵活方法。
集成详细信息
Kinesis
Kinesis Telegraf 插件旨在从 Amazon Kinesis 数据流中读取数据,使使用者能够实时收集指标。作为服务输入插件,它的运行方式是侦听传入数据,而不是定期轮询。配置指定了各种选项,包括 AWS 区域、流名称、身份验证凭据和数据格式。它支持跟踪未交付的消息以防止数据丢失,使用者可以利用 DynamoDB 来维护上次处理记录的检查点。此插件对于需要可靠且可扩展的流处理以及其他监控需求的应用特别有用。
MariaDB
Telegraf 中的 SQL 输出插件支持通过执行参数化的 SQL 语句将指标直接写入 MariaDB 等 SQL 兼容数据库。该插件支持 MySQL 驱动程序,与 MariaDB 无缝集成,实现可靠的结构化指标存储。此设置非常适合喜欢基于 SQL 的分析或希望将指标与业务数据一起存储以进行统一查询的使用者。MariaDB 是一个社区开发的、企业级的 MySQL 分支,强调性能、安全性和开放性。该插件支持将时间序列指标插入到自定义模式中,从而可以使用 SQL 连接器灵活地进行分析并与 Metabase 或 Grafana 等 BI 工具集成。
配置
Kinesis
# Configuration for the AWS Kinesis input.
[[inputs.kinesis_consumer]]
## Amazon REGION of kinesis endpoint.
region = "ap-southeast-2"
## 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 = ""
## Kinesis StreamName must exist prior to starting telegraf.
streamname = "StreamName"
## Shard iterator type (only 'TRIM_HORIZON' and 'LATEST' currently supported)
# shard_iterator_type = "TRIM_HORIZON"
## 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
## 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"
##
## The content encoding of the data from kinesis
## If you are processing a cloudwatch logs kinesis stream then set this to "gzip"
## as AWS compresses cloudwatch log data before it is sent to kinesis (aws
## also base64 encodes the zip byte data before pushing to the stream. The base64 decoding
## is done automatically by the golang sdk, as data is read from kinesis)
##
# content_encoding = "identity"
## Optional
## Configuration for a dynamodb checkpoint
[inputs.kinesis_consumer.checkpoint_dynamodb]
## unique name for this consumer
app_name = "default"
table_name = "default"
MariaDB
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com) clickhouse (ClickHouse)
driver = "mysql"
## Data source name
## The format of the data source name is different for each database driver.
## See the plugin readme for details.
data_source_name = "username:password@tcp(host:port)/dbname"
## 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})"
## SQL INSERT statement with placeholders. Telegraf will substitute values at runtime.
## table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"
## Table existence check template
## Available template variables:
## {TABLE} - tablename as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL
init_sql = "SET sql_mode='ANSI_QUOTES';"
## 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
## 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
## Metric type to SQL type conversion
## The values on the left are the data types Telegraf has and the values on
## the right are the data types Telegraf will use when sending to a database.
##
## The database values used must be data types the destination database
## understands. It is up to the user to ensure that the selected data type is
## available in the database they are using. Refer to your database
## documentation for what data types are available and supported.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
# ## This setting controls the behavior of the unsigned value. By default the
# ## setting will take the integer value and append the unsigned value to it. The other
# ## option is "literal", which will use the actual value the user provides to
# ## the unsigned option. This is useful for a database like ClickHouse where
# ## the unsigned value should use a value like "uint64".
# # conversion_style = "unsigned_suffix"
输入和输出集成示例
Kinesis
-
使用 Kinesis 进行实时数据处理:此用例涉及将 Kinesis 插件与监控仪表板集成,以实时分析传入的数据指标。例如,应用程序可以从多个服务中使用日志并以可视化方式呈现它们,使运营团队能够快速识别趋势并对异常做出反应。
-
无服务器日志聚合:在无服务器架构中使用此插件,其中 Kinesis 流聚合来自各种微服务的日志。该插件可以创建指标,帮助检测系统中的问题,通过第三方集成自动执行警报流程,使团队能够最大限度地减少停机时间并提高可靠性。
-
基于流指标的动态扩展:实施一种解决方案,其中 Kinesis 插件使用的流指标可用于动态调整资源。例如,如果处理的记录数激增,则可以触发相应的扩展操作以处理增加的负载,从而确保最佳的资源分配和性能。
-
使用检查点检查到 S3 的数据管道:创建一个强大的数据管道,其中 Kinesis 流数据通过 Telegraf Kinesis 插件进行处理,检查点存储在 DynamoDB 中。这种方法可以确保数据一致性和可靠性,因为它管理已处理数据的状态,从而实现与下游数据湖或存储解决方案的无缝集成。
MariaDB
-
商业智能集成:将应用程序性能指标直接存储到 MariaDB 中,并将其连接到 Metabase 或 Apache Superset 等 BI 工具。此设置允许将运营数据与业务 KPI 混合,以实现统一的仪表板,从而提高跨部门的可见性。
-
具有历史指标的合规性报告:使用此插件将指标记录到 MariaDB 中,用于审计和合规性用例。关系模型支持使用时间戳条目精确查询过去的绩效指标,支持法规文档。
-
基于 SQL 逻辑的自定义警报:将指标插入 MariaDB 并使用自定义 SQL 查询来定义警报阈值或条件。与 cron 作业或计划脚本结合使用,这可以实现传统指标平台无法实现的高级警报工作流程。
-
物联网传感器指标存储:通过 Telegraf 收集来自物联网设备的传感器数据,并使用规范化模式将其存储在 MariaDB 中。这种方法具有成本效益,并且与现有的基于 SQL 的系统集成良好,可用于实时或历史分析。
反馈
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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。InfluxDB 是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