目录
输入和输出集成概述
使用 Azure Monitor API 从 Azure 资源收集指标。
Telegraf SQL 插件允许您将指标从 Telegraf 直接存储到 MySQL 数据库中,从而更轻松地分析和可视化收集的指标。
集成详情
Azure Monitor
Azure Monitor Telegraf 插件专门用于使用 Azure Monitor API 从各种 Azure 资源收集指标。用户必须提供特定的凭据,例如 client_id
、client_secret
、tenant_id
和 subscription_id
,以进行身份验证并获得对其 Azure 资源的访问权限。此外,该插件还支持从单个资源以及资源组或订阅收集指标的功能,从而可以根据用户需求灵活且可扩展地收集指标。此插件非常适合利用 Azure 云基础设施的组织,可以深入了解资源性能和随时间推移的利用率,从而促进云资源的积极管理和优化。
MySQL
Telegraf 的 SQL 输出插件旨在通过基于传入指标动态创建表和列,将指标数据无缝写入 SQL 数据库。当配置为 MySQL 时,该插件利用 go-sql-driver/mysql,这需要启用 ANSI_QUOTES SQL 模式,以确保正确处理带引号的标识符。这种动态模式创建方法确保每个指标都存储在自己的表中,其结构源自其字段和标签,从而提供系统性能的详细、带时间戳的记录。该插件的灵活性使其能够处理高吞吐量环境,非常适合需要强大、精细的指标日志记录和历史数据分析的场景。
配置
Azure Monitor
# Gather Azure resources metrics from Azure Monitor API
[[inputs.azure_monitor]]
# can be found under Overview->Essentials in the Azure portal for your application/service
subscription_id = "<>"
# can be obtained by registering an application under Azure Active Directory
client_id = "<>"
# can be obtained by registering an application under Azure Active Directory.
# If not specified Default Azure Credentials chain will be attempted:
# - Environment credentials (AZURE_*)
# - Workload Identity in Kubernetes cluster
# - Managed Identity
# - Azure CLI auth
# - Developer Azure CLI auth
client_secret = "<>"
# can be found under Azure Active Directory->Properties
tenant_id = "<>"
# Define the optional Azure cloud option e.g. AzureChina, AzureGovernment or AzurePublic. The default is AzurePublic.
# cloud_option = "AzurePublic"
# resource target #1 to collect metrics from
[[inputs.azure_monitor.resource_target]]
# can be found under Overview->Essentials->JSON View in the Azure portal for your application/service
# must start with 'resourceGroups/...' ('/subscriptions/xxxxxxxx-xxxx-xxxx-xxx-xxxxxxxxxxxx'
# must be removed from the beginning of Resource ID property value)
resource_id = "<>"
# the metric names to collect
# leave the array empty to use all metrics available to this resource
metrics = [ "<>", "<>" ]
# metrics aggregation type value to collect
# can be 'Total', 'Count', 'Average', 'Minimum', 'Maximum'
# leave the array empty to collect all aggregation types values for each metric
aggregations = [ "<>", "<>" ]
# resource target #2 to collect metrics from
[[inputs.azure_monitor.resource_target]]
resource_id = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# resource group target #1 to collect metrics from resources under it with resource type
[[inputs.azure_monitor.resource_group_target]]
# the resource group name
resource_group = "<>"
# defines the resources to collect metrics from
[[inputs.azure_monitor.resource_group_target.resource]]
# the resource type
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# defines the resources to collect metrics from
[[inputs.azure_monitor.resource_group_target.resource]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# resource group target #2 to collect metrics from resources under it with resource type
[[inputs.azure_monitor.resource_group_target]]
resource_group = "<>"
[[inputs.azure_monitor.resource_group_target.resource]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# subscription target #1 to collect metrics from resources under it with resource type
[[inputs.azure_monitor.subscription_target]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# subscription target #2 to collect metrics from resources under it with resource type
[[inputs.azure_monitor.subscription_target]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
</code></pre>
MySQL
[[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})"
## 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
Azure Monitor
-
动态资源监控:使用 Azure Monitor 插件根据特定条件(如标签或资源类型)动态收集 Azure 资源的指标。组织可以自动化加载和卸载资源指标的过程,从而根据资源利用率模式更好地跟踪和优化性能。
-
多云监控集成:将从 Azure Monitor 收集的指标与其他云提供商集成,使用集中式监控解决方案。这使组织能够查看和分析跨多个云部署的性能数据,从而全面了解资源性能和成本,并简化运营。
-
异常检测和警报:结合机器学习算法,利用通过 Azure Monitor 插件收集的指标来检测资源利用率的异常情况。通过建立基准性能指标并自动警报偏差,组织可以在风险升级之前缓解风险并解决性能问题。
-
历史性能分析:通过将数据馈送到数据仓库解决方案中,使用收集的 Azure 指标进行历史分析。这使组织能够跟踪随时间推移的趋势,从而根据历史性能数据进行详细的报告和决策。
MySQL
-
实时 Web 分析存储:利用该插件捕获网站性能指标并将其存储在 MySQL 中。此设置使团队能够监控用户交互、分析流量模式,并根据实时数据洞察动态调整站点功能。
-
物联网设备监控:利用该插件从物联网传感器网络收集指标,并将它们记录到 MySQL 数据库中。此用例支持对设备健康状况和性能的持续监控,从而实现预测性维护和对异常情况的即时响应。
-
金融交易日志记录:记录具有精确时间戳的高频金融交易数据。这种方法支持强大的审计跟踪、实时欺诈检测以及全面的历史分析,以用于合规性和报告目的。
-
应用程序性能基准测试:将该插件与应用程序性能监控系统集成,以将指标记录到 MySQL 中。这有助于随时间推移进行详细的基准测试和趋势分析,使组织能够有效地识别性能瓶颈并优化资源分配。
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