目录
强大的性能,无限的扩展能力
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,它会更有价值。 借助 InfluxDB,这是排名第一的时间序列平台,旨在与 Telegraf 一起扩展。
查看入门方法
输入和输出集成概述
Tail Telegraf 插件通过追踪指定的日志文件来收集指标,实时捕获新的日志条目以进行进一步分析。
Telegraf 的 SQL 插件允许在 SQL 数据库中无缝存储指标。 当配置为 Snowflake 时,它采用专门的 DSN 格式和动态表创建,以将指标映射到适当的模式。
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用于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。
Snowflake
Telegraf 的 SQL 插件旨在通过基于传入数据创建表和列,将指标动态写入 SQL 数据库。 当配置为 Snowflake 时,它采用 gosnowflake 驱动程序,该驱动程序使用 DSN,该 DSN 以紧凑的格式封装凭据、帐户详细信息和数据库配置。 此设置允许自动生成表,其中每个指标都以精确的时间戳记录,从而确保详细的历史跟踪。 尽管该集成被认为是实验性的,但它利用了 Snowflake 强大的数据仓库功能,使其适用于可扩展的基于云的分析和报告解决方案。
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
Snowflake
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "snowflake"
## Data source name
## For Snowflake, the DSN format typically includes the username, password, account identifier, and optional warehouse, database, and schema.
## Example DSN: "username:password@account/warehouse/db/schema"
data_source_name = "username:password@account/warehouse/db/schema"
## 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} - table name as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL (optional)
init_sql = ""
## 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
## Metric type to SQL type conversion
## Defaults to ANSI/ISO SQL types unless overridden. Adjust if needed for Snowflake compatibility.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
输入和输出集成示例
Tail
-
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并响应流量或错误的峰值,从而提高系统可靠性和用户体验。
-
集中式日志管理:利用 Tail 插件聚合分布式系统中来自多个来源的日志。 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可以从单个界面访问所有相关数据,从而简化故障排除流程。
-
安全事件检测:使用此插件监控身份验证日志中是否存在未经授权的访问尝试或可疑活动。 通过在某些日志消息上设置警报,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,从而降低漏洞风险并提高整体系统完整性。
-
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,这些仪表板显示基于日志数据的应用程序性能指标。 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。
Snowflake
-
基于云的数据湖集成:利用该插件将来自各种来源的实时指标流式传输到 Snowflake 中,从而创建集中式数据湖。 此集成支持云数据上的复杂分析和机器学习工作流程。
-
动态商业智能仪表板:利用该插件自动从传入指标生成表,并将它们馈送到 BI 工具中。 这使企业可以创建动态仪表板,以可视化性能趋势和运营洞察,而无需手动模式管理。
-
可扩展的物联网分析:部署该插件以捕获来自物联网设备的高频数据到 Snowflake 中。 此用例有助于传感器数据的聚合和分析,从而实现大规模的预测性维护和实时监控。
-
用于合规性的历史趋势分析:使用该插件在 Snowflake 中记录和存档详细的指标数据,然后可以查询这些数据以进行长期趋势分析和合规性报告。 此设置确保组织可以维护强大的审计跟踪并在需要时执行取证分析。
反馈
感谢您成为我们社区的一份子! 如果您有任何一般性反馈或在这些页面上发现任何错误,我们欢迎并鼓励您提供意见。 请在 InfluxDB 社区 Slack 中提交您的反馈。
强大的性能,无限的扩展能力
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,它会更有价值。 借助 InfluxDB,这是排名第一的时间序列平台,旨在与 Telegraf 一起扩展。
查看入门方法