目录
输入和输出集成概述
Tail Telegraf 插件通过跟踪指定的日志文件来收集指标,实时捕获新的日志条目以供进一步分析。
Redis 插件使用户能够将 Telegraf 收集的指标直接发送到 Redis。此集成非常适合需要强大的时序数据存储和分析的应用程序。
集成详情
Tail
tail 插件旨在持续监控和解析日志文件,使其成为实时日志分析和监控的理想选择。它模仿 Unix tail
命令的功能,允许用户指定文件或模式,并在添加新行时开始读取。主要功能包括跟踪日志轮换文件、从文件末尾开始读取以及支持日志消息的各种解析格式。用户可以通过各种配置选项自定义插件,例如指定文件编码、监视文件更新的方法以及处理日志数据的过滤器设置。在日志数据对于监控应用程序性能和诊断问题至关重要的环境中,此插件尤其有价值。
Redis
Redis Telegraf 插件旨在将指标写入 RedisTimeSeries,这是一个专门用于时序数据的 Redis 数据库模块。此插件促进了 Telegraf 与 RedisTimeSeries 的集成,从而可以高效地存储和检索带时间戳的数据。借助 RedisTimeSeries,用户可以利用增强的功能来管理时序数据,包括聚合视图和范围查询。该插件提供了各种配置选项,以实现安全连接到 Redis 数据库所需的灵活性,包括对身份验证、超时、数据类型转换和 TLS 配置的支持。底层技术利用了 Redis 的效率和可扩展性,使其成为高容量指标环境的绝佳选择,在这些环境中,实时处理至关重要。
配置
Tail
[[inputs.tail]]
## File names or a pattern to tail.
## These accept standard unix glob matching rules, but with the addition of
## ** as a "super asterisk". ie:
## "/var/log/**.log" -> recursively find all .log files in /var/log
## "/var/log/*/*.log" -> find all .log files with a parent dir in /var/log
## "/var/log/apache.log" -> just tail the apache log file
## "/var/log/log[!1-2]* -> tail files without 1-2
## "/var/log/log[^1-2]* -> identical behavior as above
## See https://github.com/gobwas/glob for more examples
##
files = ["/var/mymetrics.out"]
## Read file from beginning.
# from_beginning = false
## Whether file is a named pipe
# pipe = false
## Method used to watch for file updates. Can be either "inotify" or "poll".
## inotify is supported on linux, *bsd, and macOS, while Windows requires
## using poll. Poll checks for changes every 250ms.
# watch_method = "inotify"
## Maximum lines of the file to process that have not yet be written by the
## output. For best throughput set based on the number of metrics on each
## line and the size of the output's metric_batch_size.
# max_undelivered_lines = 1000
## Character encoding to use when interpreting the file contents. Invalid
## characters are replaced using the unicode replacement character. When set
## to the empty string the data is not decoded to text.
## ex: character_encoding = "utf-8"
## character_encoding = "utf-16le"
## character_encoding = "utf-16be"
## character_encoding = ""
# character_encoding = ""
## 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"
## Set the tag that will contain the path of the tailed file. If you don't want this tag, set it to an empty string.
# path_tag = "path"
## Filters to apply to files before generating metrics
## "ansi_color" removes ANSI colors
# filters = []
## multiline parser/codec
## https://elastic.ac.cn/guide/en/logstash/2.4/plugins-filters-multiline.html
#[inputs.tail.multiline]
## The pattern should be a regexp which matches what you believe to be an indicator that the field is part of an event consisting of multiple lines of log data.
#pattern = "^\s"
## The field's value must be previous or next and indicates the relation to the
## multi-line event.
#match_which_line = "previous"
## The invert_match can be true or false (defaults to false).
## If true, a message not matching the pattern will constitute a match of the multiline filter and the what will be applied. (vice-versa is also true)
#invert_match = false
## The handling method for quoted text (defaults to 'ignore').
## The following methods are available:
## ignore -- do not consider quotation (default)
## single-quotes -- consider text quoted by single quotes (')
## double-quotes -- consider text quoted by double quotes (")
## backticks -- consider text quoted by backticks (`)
## When handling quotes, escaped quotes (e.g. \") are handled correctly.
#quotation = "ignore"
## The preserve_newline option can be true or false (defaults to false).
## If true, the newline character is preserved for multiline elements,
## this is useful to preserve message-structure e.g. for logging outputs.
#preserve_newline = false
#After the specified timeout, this plugin sends the multiline event even if no new pattern is found to start a new event. The default is 5s.
#timeout = 5s
Redis
[[outputs.redistimeseries]]
## The address of the RedisTimeSeries server.
address = "127.0.0.1:6379"
## Redis ACL credentials
# username = ""
# password = ""
# database = 0
## Timeout for operations such as ping or sending metrics
# timeout = "10s"
## Enable attempt to convert string fields to numeric values
## If "false" or in case the string value cannot be converted the string
## field will be dropped.
# convert_string_fields = true
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
# insecure_skip_verify = false
输入和输出集成示例
Tail
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实时服务器健康状况监控:实施 Tail 插件以实时解析 Web 服务器访问日志,从而立即了解用户活动、错误率和性能指标。通过可视化此日志数据,运营团队可以快速识别和响应流量或错误峰值,从而提高系统可靠性和用户体验。
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集中式日志管理:利用 Tail 插件来聚合分布式系统中多个来源的日志。通过配置每个服务以通过 Tail 插件将其日志发送到集中位置,团队可以简化日志分析,并确保从单个界面访问所有相关数据,从而简化故障排除流程。
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安全事件检测:使用此插件监控身份验证日志中未经授权的访问尝试或可疑活动。通过对某些日志消息设置警报,团队可以利用此插件来增强安全态势并及时响应潜在的安全威胁,从而降低违规风险并提高整体系统完整性。
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动态应用程序性能洞察:与分析工具集成以创建实时仪表板,这些仪表板根据日志数据展示应用程序性能指标。此设置不仅可以帮助开发人员诊断瓶颈和效率低下问题,还可以实现主动性能调整和资源分配,从而优化应用程序在不同负载下的行为。
Redis
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监控物联网传感器数据:利用 Redis Telegraf 插件实时收集和存储来自物联网传感器的数据。通过将插件连接到 RedisTimeSeries 数据库,用户可以分析温度、湿度或其他环境因素的趋势。有效查询历史传感器数据的能力将有助于预测性维护并帮助进行资源管理。
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金融市场数据聚合:使用此插件跟踪和存储来自各种来源的时间敏感性金融数据。通过将指标发送到 Redis,金融机构可以聚合和分析市场趋势或价格随时间的变化,从而为他们提供从可靠的时序分析中得出的可操作见解。
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应用程序性能监控 (APM):实施 Redis 插件以收集应用程序性能指标,例如响应时间和 CPU 使用率。用户可以使用 RedisTimeSeries 可视化其应用程序随时间的性能,从而使他们能够快速识别瓶颈并优化资源分配。
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能源消耗跟踪:利用此插件来监控建筑物随时间的能源使用情况。通过与智能电表集成并将数据发送到 RedisTimeSeries,市政当局或企业可以分析能源消耗模式,从而帮助实施节能措施和可持续性实践。
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