目录
输入和输出集成概述
AMQP Consumer 输入插件允许您从兼容 AMQP 0-9-1 的消息代理(如 RabbitMQ)摄取数据,从而为监控和分析目的实现无缝数据收集。
Datadog Telegraf 插件支持向 Datadog Metrics API 提交指标,通过可靠的指标摄取流程促进高效的监控和数据分析。
集成详情
AMQP
此插件为 AMQP 0-9-1 提供了一个消费者,RabbitMQ 是其重要的实现之一。 AMQP,即高级消息队列协议,最初是为了在网络中各种不同的系统之间实现可靠、可互操作的消息传递而开发的。 该插件使用配置的队列和绑定键从主题交换中读取指标,从而提供了一种灵活高效的方式,用于从兼容 AMQP 的消息传递系统中收集数据。 这使用户能够利用现有的 RabbitMQ 实现来有效地监控其应用程序,方法是捕获详细的指标以进行分析和警报。
Datadog
此插件写入 Datadog Metrics API,使用户能够发送指标以进行监控和性能分析。 通过使用 Datadog API 密钥,用户可以配置插件以建立与 Datadog v1 API 的连接。 该插件支持各种配置选项,包括连接超时、HTTP 代理设置和数据压缩方法,确保适应不同的部署环境。 将计数指标转换为速率的能力增强了 Telegraf 与 Datadog 代理的集成,这对于依赖实时性能指标的应用程序尤其有益。
配置
AMQP
[[inputs.amqp_consumer]]
## Brokers to consume from. If multiple brokers are specified a random broker
## will be selected anytime a connection is established. This can be
## helpful for load balancing when not using a dedicated load balancer.
brokers = ["amqp://localhost:5672/influxdb"]
## Authentication credentials for the PLAIN auth_method.
# username = ""
# password = ""
## Name of the exchange to declare. If unset, no exchange will be declared.
exchange = "telegraf"
## Exchange type; common types are "direct", "fanout", "topic", "header", "x-consistent-hash".
# exchange_type = "topic"
## If true, exchange will be passively declared.
# exchange_passive = false
## Exchange durability can be either "transient" or "durable".
# exchange_durability = "durable"
## Additional exchange arguments.
# exchange_arguments = { }
# exchange_arguments = {"hash_property" = "timestamp"}
## AMQP queue name.
queue = "telegraf"
## AMQP queue durability can be "transient" or "durable".
queue_durability = "durable"
## If true, queue will be passively declared.
# queue_passive = false
## Additional arguments when consuming from Queue
# queue_consume_arguments = { }
# queue_consume_arguments = {"x-stream-offset" = "first"}
## A binding between the exchange and queue using this binding key is
## created. If unset, no binding is created.
binding_key = "#"
## Maximum number of messages server should give to the worker.
# prefetch_count = 50
## 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
## Timeout for establishing the connection to a broker
# timeout = "30s"
## Auth method. PLAIN and EXTERNAL are supported
## Using EXTERNAL requires enabling the rabbitmq_auth_mechanism_ssl plugin as
## described here: https://rabbitmq.cn/plugins.html
# auth_method = "PLAIN"
## 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
## Content encoding for message payloads, can be set to
## "gzip", "identity" or "auto"
## - Use "gzip" to decode gzip
## - Use "identity" to apply no encoding
## - Use "auto" determine the encoding using the ContentEncoding header
# content_encoding = "identity"
## Maximum size of decoded message.
## Acceptable units are B, KiB, KB, MiB, MB...
## Without quotes and units, interpreted as size in bytes.
# max_decompression_size = "500MB"
## 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"
Datadog
[[outputs.datadog]]
## Datadog API key
apikey = "my-secret-key"
## Connection timeout.
# timeout = "5s"
## Write URL override; useful for debugging.
## This plugin only supports the v1 API currently due to the authentication
## method used.
# url = "https://app.datadoghq.com/api/v1/series"
## Set http_proxy
# use_system_proxy = false
# http_proxy_url = "http://localhost:8888"
## Override the default (none) compression used to send data.
## Supports: "zlib", "none"
# compression = "none"
## When non-zero, converts count metrics submitted by inputs.statsd
## into rate, while dividing the metric value by this number.
## Note that in order for metrics to be submitted simultaenously alongside
## a Datadog agent, rate_interval has to match the interval used by the
## agent - which defaults to 10s
# rate_interval = 0s
输入和输出集成示例
AMQP
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将应用程序指标与 AMQP 集成:使用 AMQP Consumer 插件收集发布到 RabbitMQ 交换机的应用程序指标。 通过配置插件以侦听特定队列,团队可以实时了解应用程序性能,跟踪请求率、错误计数和延迟指标。 这种设置不仅有助于异常检测,而且还为容量规划和系统优化提供了有价值的数据。
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事件驱动的监控:配置 AMQP Consumer 以在应用程序内满足某些条件时触发特定的监控事件。 例如,如果收到指示高错误率的消息,则插件可以将此数据馈送到监控工具中,从而生成警报或扩展事件。 这种集成可以提高对问题的响应速度并自动化部分操作工作流程。
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跨平台数据聚合:利用 AMQP Consumer 插件整合来自分布在不同平台上的各种应用程序的指标。 通过使用 RabbitMQ 作为集中式消息代理,组织可以统一其监控数据,从而可以通过 Telegraf 进行全面的分析和仪表板显示,从而在异构环境中保持可见性。
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实时日志处理:扩展 AMQP Consumer 的使用,以捕获发送到 RabbitMQ 交换机的日志数据,实时处理日志以进行监控和警报。 此应用程序通过分析日志模式、趋势和异常情况(在发生时),确保及时检测和解决操作问题。
Datadog
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实时基础设施监控:使用 Datadog 插件实时监控服务器指标,方法是将 CPU 使用率和内存统计信息直接发送到 Datadog。 这种集成允许 IT 团队在集中式仪表板中可视化和分析系统性能指标,从而能够主动响应任何新出现的问题,例如资源瓶颈或服务器过载。
-
应用程序性能跟踪:利用此插件向 Datadog 提交特定于应用程序的指标,例如请求计数和错误率。 通过与应用程序监控工具集成,团队可以将基础设施指标与应用程序性能相关联,从而提供洞察力,使其能够优化代码性能并改善用户体验。
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指标中的异常检测:配置 Datadog 插件以发送指标,这些指标可以根据 Datadog 机器学习功能检测到的异常模式触发警报和通知。 这种主动监控有助于团队在客户受到影响之前迅速对潜在的中断或性能下降做出反应。
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与云服务集成:通过利用 Datadog 插件从云资源发送指标,IT 团队可以了解云应用程序的性能。 监控延迟和错误率等指标有助于确保满足服务级别协议 (SLA),并有助于优化跨云环境的资源分配。
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