对于大规模实时查询，这不是推荐的配置。为了优化查询和压缩、实现高速摄取和高可用性，您可能需要考虑 StatsD 和 InfluxDB。
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输入和输出集成概述
StatsD 输入插件通过在后台运行侦听器服务，从 StatsD 服务器捕获指标，从而实现全面的性能监控和指标聚合。
Sumo Logic 插件旨在方便从 Telegraf 向 Sumo Logic 的 HTTP 源发送指标。通过使用此插件，用户可以在 Sumo Logic 平台上分析其指标数据，并利用各种输出数据格式。
集成详细信息
StatsD
StatsD 输入插件旨在通过在 Telegraf 处于活动状态时运行后台 StatsD 侦听器服务，从 StatsD 服务器收集指标。此插件利用原始 Etsy 实现建立的 StatsD 消息格式，该格式允许各种类型的指标，包括仪表、计数器、集合、计时、直方图和分布图。StatsD 插件的功能扩展到解析标签，并使用适应 InfluxDB 标签系统的功能扩展标准协议。它可以处理通过不同协议（UDP 或 TCP）发送的消息，有效管理多个指标，并为优化指标处理提供高级配置，例如百分位数计算和数据转换模板。这种灵活性使户能够全面跟踪应用程序性能，使其成为强大监控设置的重要工具。
Sumo Logic
此插件有助于将指标传输到 Sumo Logic 的 HTTP 源，并为 HTTP 消息采用指定的数据格式。Telegraf 必须是 1.16.0 或更高版本，可以发送以多种格式编码的指标，包括 graphite、carbon2 和 prometheus。这些格式对应于 Sumo Logic 识别的不同内容类型，确保指标得到正确解释以进行分析。与 Sumo Logic 集成使用户能够利用全面的分析平台，从而可以从其指标数据中获得丰富的可视化效果和见解。该插件提供配置选项，例如设置 HTTP 指标源的 URL、选择数据格式以及指定其他参数（如超时和请求大小），从而增强数据监控工作流程的灵活性和控制力。
配置
StatsD
[[inputs.statsd]]
## Protocol, must be "tcp", "udp4", "udp6" or "udp" (default=udp)
protocol = "udp"
## MaxTCPConnection - applicable when protocol is set to tcp (default=250)
max_tcp_connections = 250
## Enable TCP keep alive probes (default=false)
tcp_keep_alive = false
## Specifies the keep-alive period for an active network connection.
## Only applies to TCP sockets and will be ignored if tcp_keep_alive is false.
## Defaults to the OS configuration.
# tcp_keep_alive_period = "2h"
## Address and port to host UDP listener on
service_address = ":8125"
## The following configuration options control when telegraf clears it's cache
## of previous values. If set to false, then telegraf will only clear it's
## cache when the daemon is restarted.
## Reset gauges every interval (default=true)
delete_gauges = true
## Reset counters every interval (default=true)
delete_counters = true
## Reset sets every interval (default=true)
delete_sets = true
## Reset timings & histograms every interval (default=true)
delete_timings = true
## Enable aggregation temporality adds temporality=delta or temporality=commulative tag, and
## start_time field, which adds the start time of the metric accumulation.
## You should use this when using OpenTelemetry output.
# enable_aggregation_temporality = false
## Percentiles to calculate for timing & histogram stats.
percentiles = [50.0, 90.0, 99.0, 99.9, 99.95, 100.0]
## separator to use between elements of a statsd metric
metric_separator = "_"
## Parses tags in the datadog statsd format
## http://docs.datadoghq.com/guides/dogstatsd/
## deprecated in 1.10; use datadog_extensions option instead
parse_data_dog_tags = false
## Parses extensions to statsd in the datadog statsd format
## currently supports metrics and datadog tags.
## http://docs.datadoghq.com/guides/dogstatsd/
datadog_extensions = false
## Parses distributions metric as specified in the datadog statsd format
## https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition
datadog_distributions = false
## Keep or drop the container id as tag. Included as optional field
## in DogStatsD protocol v1.2 if source is running in Kubernetes
## https://docs.datadoghq.com/developers/dogstatsd/datagram_shell/?tab=metrics#dogstatsd-protocol-v12
datadog_keep_container_tag = false
## Statsd data translation templates, more info can be read here:
## https://github.com/influxdata/telegraf/blob/master/docs/TEMPLATE_PATTERN.md
# templates = [
# "cpu.* measurement*"
# ]
## Number of UDP messages allowed to queue up, once filled,
## the statsd server will start dropping packets
allowed_pending_messages = 10000
## Number of worker threads used to parse the incoming messages.
# number_workers_threads = 5
## Number of timing/histogram values to track per-measurement in the
## calculation of percentiles. Raising this limit increases the accuracy
## of percentiles but also increases the memory usage and cpu time.
percentile_limit = 1000
## Maximum socket buffer size in bytes, once the buffer fills up, metrics
## will start dropping. Defaults to the OS default.
# read_buffer_size = 65535
## Max duration (TTL) for each metric to stay cached/reported without being updated.
# max_ttl = "10h"
## Sanitize name method
## By default, telegraf will pass names directly as they are received.
## However, upstream statsd now does sanitization of names which can be
## enabled by using the "upstream" method option. This option will a) replace
## white space with '_', replace '/' with '-', and remove characters not
## matching 'a-zA-Z_\-0-9\.;='.
#sanitize_name_method = ""
## Replace dots (.) with underscore (_) and dashes (-) with
## double underscore (__) in metric names.
# convert_names = false
## Convert all numeric counters to float
## Enabling this would ensure that both counters and guages are both emitted
## as floats.
# float_counters = false
Sumo Logic
[[outputs.sumologic]]
## Unique URL generated for your HTTP Metrics Source.
## This is the address to send metrics to.
# url = "https://events.sumologic.net/receiver/v1/http/"
## Data format to be used for sending metrics.
## This will set the "Content-Type" header accordingly.
## Currently supported formats:
## * graphite - for Content-Type of application/vnd.sumologic.graphite
## * carbon2 - for Content-Type of application/vnd.sumologic.carbon2
## * prometheus - for Content-Type of application/vnd.sumologic.prometheus
##
## More information can be found at:
## https://help.sumologic.com/03Send-Data/Sources/02Sources-for-Hosted-Collectors/HTTP-Source/Upload-Metrics-to-an-HTTP-Source#content-type-headers-for-metrics
##
## NOTE:
## When unset, telegraf will by default use the influx serializer which is currently unsupported
## in HTTP Source.
data_format = "carbon2"
## Timeout used for HTTP request
# timeout = "5s"
## Max HTTP request body size in bytes before compression (if applied).
## By default 1MB is recommended.
## NOTE:
## Bear in mind that in some serializer a metric even though serialized to multiple
## lines cannot be split any further so setting this very low might not work
## as expected.
# max_request_body_size = 1000000
## Additional, Sumo specific options.
## Full list can be found here:
## https://help.sumologic.com/03Send-Data/Sources/02Sources-for-Hosted-Collectors/HTTP-Source/Upload-Metrics-to-an-HTTP-Source#supported-http-headers
## Desired source name.
## Useful if you want to override the source name configured for the source.
# source_name = ""
## Desired host name.
## Useful if you want to override the source host configured for the source.
# source_host = ""
## Desired source category.
## Useful if you want to override the source category configured for the source.
# source_category = ""
## Comma-separated key=value list of dimensions to apply to every metric.
## Custom dimensions will allow you to query your metrics at a more granular level.
# dimensions = ""
</code></pre>
输入和输出集成示例
StatsD
-
实时应用程序性能监控：利用 StatsD 输入插件实时监控应用程序性能指标。通过配置您的应用程序向 StatsD 服务器发送各种指标，团队可以利用此插件动态分析性能瓶颈、跟踪用户活动并确保资源优化。历史指标和实时指标的结合允许主动排除故障并增强问题解决流程的响应能力。
-
跟踪 Web 应用程序中的用户互动指标：使用 StatsD 插件收集用户互动统计信息，例如页面浏览量、点击事件和互动时间。通过将这些指标发送到 StatsD 服务器，企业可以深入了解用户行为，从而能够根据量化反馈做出数据驱动的决策，以改善用户体验和界面设计。这可以显着提高营销策略和产品开发工作的有效性。
-
基础设施运行状况监控：部署 StatsD 插件，通过跟踪资源利用率、服务器响应时间和网络性能等指标来监控服务器基础设施的运行状况。通过此设置，DevOps 团队可以详细了解系统性能，从而有效地在问题升级之前预测到问题。这有助于采用主动式基础设施管理方法，最大限度地减少停机时间并确保最佳服务交付。
-
创建全面的服务仪表板：将 StatsD 与可视化工具集成，以创建全面的仪表板，从而反映整个架构中服务的状态和运行状况。例如，组合来自通过 StatsD 记录的多个服务的数据可以将原始指标转换为可操作的见解，从而随时间推移展示系统性能趋势。此功能使利益干系人能够保持监督并根据可视化数据集推动决策，从而提高整体运营透明度。
Sumo Logic
-
实时系统监控仪表板：利用 Sumo Logic 插件将服务器的性能指标持续馈送到 Sumo Logic 仪表板中。此设置允许技术团队实时可视化系统运行状况和负载，从而可以通过详细的图表和指标更快地识别任何性能瓶颈或系统故障。
-
自动化警报系统：配置插件以发送在 Sumo Logic 中触发警报的指标，用于特定阈值，例如 CPU 使用率或内存消耗。通过设置自动化警报，团队可以在问题升级为严重故障之前主动解决问题，从而显着提高响应时间和整体系统可靠性。
-
跨系统指标聚合：跨不同环境（开发、测试、生产）集成多个 Telegraf 实例，并使用此插件将所有指标汇集到中央 Sumo Logic 实例。此聚合支持跨环境的全面分析，从而有助于在整个软件开发生命周期中实现更好的监控和知情决策。
-
具有维度跟踪的自定义指标：使用 Sumo Logic 插件发送自定义指标，其中包括标识基础设施各个方面的维度（例如，环境、服务类型）。这种精细的跟踪允许进行更具针对性的分析，使您的团队能够剖析跨不同应用程序层或业务功能的性能。
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