目录
强大性能,无限扩展
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,它都会变得更有价值。InfluxDB 是排名第一的时间序列平台,旨在通过 Telegraf 进行扩展。
查看入门方法
输入和输出集成概述
使用 Azure Monitor API 从 Azure 资源收集指标。
Graphite 插件使用户能够通过 TCP 将 Telegraf 收集的指标发送到 Graphite。此集成允许使用 Graphite 的强大功能高效地存储和可视化时序数据。
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,从而可以灵活且可扩展地收集根据用户需求定制的指标。此插件非常适合利用 Azure 云基础设施的组织,可提供对资源性能和随时间推移的利用率的关键见解,从而促进云资源的积极管理和优化。
Graphite
此插件通过原始 TCP 将指标写入 Graphite,从而将 Telegraf 收集的指标无缝集成到 Graphite 生态系统中。借助此插件,用户可以配置多个 TCP 端点以进行负载均衡,从而确保指标传输的高可用性和可靠性。使用前缀自定义指标命名以及使用各种模板选项的能力增强了数据在 Graphite 中表示方式的灵活性。此外,对 Graphite 标签的支持以及对指标名称进行严格清理的选项允许进行强大的数据管理,以满足用户的不同需求。此功能对于希望利用 Graphite 强大的指标存储和可视化功能,同时保持对数据表示方式的控制的组织至关重要。
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>
Graphite
# Configuration for Graphite server to send metrics to
[[outputs.graphite]]
## TCP endpoint for your graphite instance.
## If multiple endpoints are configured, the output will be load balanced.
## Only one of the endpoints will be written to with each iteration.
servers = ["localhost:2003"]
## Local address to bind when connecting to the server
## If empty or not set, the local address is automatically chosen.
# local_address = ""
## Prefix metrics name
prefix = ""
## Graphite output template
## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
template = "host.tags.measurement.field"
## Strict sanitization regex
## This is the default sanitization regex that is used on data passed to the
## graphite serializer. Users can add additional characters here if required.
## Be aware that the characters, '/' '@' '*' are always replaced with '_',
## '..' is replaced with '.', and '\' is removed even if added to the
## following regex.
# graphite_strict_sanitize_regex = '[^a-zA-Z0-9-:._=\p{L}]'
## Enable Graphite tags support
# graphite_tag_support = false
## Applied sanitization mode when graphite tag support is enabled.
## * strict - uses the regex specified above
## * compatible - allows for greater number of characters
# graphite_tag_sanitize_mode = "strict"
## Character for separating metric name and field for Graphite tags
# graphite_separator = "."
## Graphite templates patterns
## 1. Template for cpu
## 2. Template for disk*
## 3. Default template
# templates = [
# "cpu tags.measurement.host.field",
# "disk* measurement.field",
# "host.measurement.tags.field"
#]
## timeout in seconds for the write connection to graphite
# timeout = "2s"
## 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
输入和输出集成示例
Azure Monitor
-
动态资源监控:使用 Azure Monitor 插件根据特定标准(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:使用集中式监控解决方案集成从 Azure Monitor 和其他云提供商处收集的指标。这使组织可以查看和分析跨多个云部署的性能数据,从而提供资源性能和成本的整体概览,并简化运营。
-
异常检测和警报:利用通过 Azure Monitor 插件收集的指标,结合机器学习算法来检测资源利用率的异常情况。通过建立基线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:通过将收集的 Azure 指标数据输入到数据仓库解决方案中,使用这些数据进行历史分析。这使组织能够跟踪随时间推移的趋势,从而可以根据历史性能数据进行详细的报告和决策。
Graphite
-
动态指标可视化:Graphite 插件可用于将来自各种来源(例如应用程序性能数据或服务器运行状况指标)的实时指标馈送到 Graphite 中。这种动态集成使团队能够创建交互式仪表板,可视化关键绩效指标,跟踪随时间推移的趋势,并做出数据驱动的决策以增强系统性能。
-
负载均衡指标收集:通过在插件中配置多个 TCP 端点,组织可以为指标传输实施负载均衡。此用例确保指标交付既有弹性又高效,从而降低高流量期间数据丢失的风险,并保持到 Graphite 的可靠信息流。
-
自定义指标标记:借助对 Graphite 标签的支持,用户可以使用 Graphite 插件来增强其指标的粒度。使用相关信息(例如应用程序环境或服务类型)标记指标可以进行更精细的查询和分析,从而使团队能够深入研究特定感兴趣的领域,以获得更好的运营见解。
-
增强的数据清理:利用插件的严格清理选项,用户可以确保其指标名称符合 Graphite 的要求。这种积极的措施消除了指标名称中无效字符可能引起的问题,从而实现更清洁的数据管理和更准确的可视化。
反馈
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强大性能,无限扩展
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,它都会变得更有价值。InfluxDB 是排名第一的时间序列平台,旨在通过 Telegraf 进行扩展。
查看入门方法