目录
输入和输出集成概述
Jenkins 插件通过其 API 从 Jenkins 实例收集有关作业和节点的关键信息,从而促进全面的监控和分析。
AWS Timestream Telegraf 插件使用户能够将指标直接发送到 Amazon 的 Timestream 服务,该服务专为时序数据管理而设计。此插件为身份验证、数据组织和保留设置提供了各种配置选项。
集成详情
Jenkins
Jenkins Telegraf 插件允许用户从 Jenkins 实例收集指标,而无需在 Jenkins 本身安装任何额外的插件。通过利用 Jenkins API,该插件检索有关 Jenkins 环境中运行的节点和作业的信息。此集成提供了 Jenkins 基础设施的全面概览,包括可用于监控和分析的实时指标。主要功能包括用于作业和节点选择的可配置过滤器、可选的 TLS 安全设置以及有效管理请求超时和连接限制的能力。这使其成为依赖 Jenkins 进行持续集成和交付的团队必不可少的工具,确保他们拥有维护最佳性能和可靠性所需的洞察力。
AWS Timestream
此插件旨在有效地将指标写入 Amazon 的 Timestream 服务,这是一种针对物联网和运营应用程序优化的时序数据库。借助此插件,Telegraf 可以发送从各种来源收集的数据,并支持身份验证、数据组织和保留管理的灵活配置。它利用凭证链进行身份验证,允许各种方法,例如 Web 身份、承担角色和共享配置文件。用户可以定义指标在 Timestream 中的组织方式——是使用单个表还是多个表,以及控制磁存储和内存存储的保留期等方面。一个关键特性是它能够处理多度量记录,从而实现高效的数据摄取并帮助减少多次写入的开销。在错误处理方面,该插件包含用于解决数据写入期间与 AWS 错误相关的常见问题的机制,例如用于限制的重试逻辑以及根据需要创建表的能力。
配置
Jenkins
[[inputs.jenkins]]
## The Jenkins URL in the format "schema://host:port"
url = "http://my-jenkins-instance:8080"
# username = "admin"
# password = "admin"
## Set response_timeout
response_timeout = "5s"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use SSL but skip chain & host verification
# insecure_skip_verify = false
## Optional Max Job Build Age filter
## Default 1 hour, ignore builds older than max_build_age
# max_build_age = "1h"
## Optional Sub Job Depth filter
## Jenkins can have unlimited layer of sub jobs
## This config will limit the layers of pulling, default value 0 means
## unlimited pulling until no more sub jobs
# max_subjob_depth = 0
## Optional Sub Job Per Layer
## In workflow-multibranch-plugin, each branch will be created as a sub job.
## This config will limit to call only the lasted branches in each layer,
## empty will use default value 10
# max_subjob_per_layer = 10
## Jobs to include or exclude from gathering
## When using both lists, job_exclude has priority.
## Wildcards are supported: [ "jobA/*", "jobB/subjob1/*"]
# job_include = [ "*" ]
# job_exclude = [ ]
## Nodes to include or exclude from gathering
## When using both lists, node_exclude has priority.
# node_include = [ "*" ]
# node_exclude = [ ]
## Worker pool for jenkins plugin only
## Empty this field will use default value 5
# max_connections = 5
## When set to true will add node labels as a comma-separated tag. If none,
## are found, then a tag with the value of 'none' is used. Finally, if a
## label contains a comma it is replaced with an underscore.
# node_labels_as_tag = false
AWS Timestream
[[outputs.timestream]]
## Amazon Region
region = "us-east-1"
## Amazon Credentials
## Credentials are loaded in the following order:
## 1) Web identity provider credentials via STS if role_arn and web_identity_token_file are specified
## 2) Assumed credentials via STS if role_arn is specified
## 3) explicit credentials from 'access_key' and 'secret_key'
## 4) shared profile from 'profile'
## 5) environment variables
## 6) shared credentials file
## 7) EC2 Instance Profile
#access_key = ""
#secret_key = ""
#token = ""
#role_arn = ""
#web_identity_token_file = ""
#role_session_name = ""
#profile = ""
#shared_credential_file = ""
## Endpoint to make request against, the correct endpoint is automatically
## determined and this option should only be set if you wish to override the
## default.
## ex: endpoint_url = "http://localhost:8000"
# endpoint_url = ""
## Timestream database where the metrics will be inserted.
## The database must exist prior to starting Telegraf.
database_name = "yourDatabaseNameHere"
## Specifies if the plugin should describe the Timestream database upon starting
## to validate if it has access necessary permissions, connection, etc., as a safety check.
## If the describe operation fails, the plugin will not start
## and therefore the Telegraf agent will not start.
describe_database_on_start = false
## Specifies how the data is organized in Timestream.
## Valid values are: single-table, multi-table.
## When mapping_mode is set to single-table, all of the data is stored in a single table.
## When mapping_mode is set to multi-table, the data is organized and stored in multiple tables.
## The default is multi-table.
mapping_mode = "multi-table"
## Specifies if the plugin should create the table, if the table does not exist.
create_table_if_not_exists = true
## Specifies the Timestream table magnetic store retention period in days.
## Check Timestream documentation for more details.
## NOTE: This property is valid when create_table_if_not_exists = true.
create_table_magnetic_store_retention_period_in_days = 365
## Specifies the Timestream table memory store retention period in hours.
## Check Timestream documentation for more details.
## NOTE: This property is valid when create_table_if_not_exists = true.
create_table_memory_store_retention_period_in_hours = 24
## Specifies how the data is written into Timestream.
## Valid values are: true, false
## When use_multi_measure_records is set to true, all of the tags and fields are stored
## as a single row in a Timestream table.
## When use_multi_measure_record is set to false, Timestream stores each field in a
## separate table row, thereby storing the tags multiple times (once for each field).
## The recommended setting is true.
## The default is false.
use_multi_measure_records = "false"
## Specifies the measure_name to use when sending multi-measure records.
## NOTE: This property is valid when use_multi_measure_records=true and mapping_mode=multi-table
measure_name_for_multi_measure_records = "telegraf_measure"
## Specifies the name of the table to write data into
## NOTE: This property is valid when mapping_mode=single-table.
# single_table_name = ""
## Specifies the name of dimension when all of the data is being stored in a single table
## and the measurement name is transformed into the dimension value
## (see Mapping data from Influx to Timestream for details)
## NOTE: This property is valid when mapping_mode=single-table.
# single_table_dimension_name_for_telegraf_measurement_name = "namespace"
## Only valid and optional if create_table_if_not_exists = true
## Specifies the Timestream table tags.
## Check Timestream documentation for more details
# create_table_tags = { "foo" = "bar", "environment" = "dev"}
## Specify the maximum number of parallel go routines to ingest/write data
## If not specified, defaulted to 1 go routines
max_write_go_routines = 25
## Please see README.md to know how line protocol data is mapped to Timestream
##
输入和输出集成示例
Jenkins
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持续集成监控:使用 Jenkins 插件通过收集作业持续时间和失败率的指标来监控持续集成管道的性能。这可以帮助团队识别管道中的瓶颈并提高整体构建效率。
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资源分配分析:利用 Jenkins 节点指标来评估不同代理之间的资源使用情况。通过了解资源分配方式,团队可以优化其 Jenkins 架构,从而可能重新分配代理或调整作业配置以获得更好的性能。
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作业执行趋势:分析历史作业性能指标以识别作业执行随时间变化的趋势。借助此数据,团队可以主动解决潜在问题,并在问题扩大之前根据需要调整作业或其配置。
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作业失败警报:实施利用 Jenkins 作业指标的警报,以便在作业失败时通知团队成员。这种主动方法可以增强运营意识并加快对失败的响应时间,确保有效监控关键作业。
AWS Timestream
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物联网数据指标:使用 Timestream 插件将来自物联网设备的实时指标发送到 Timestream,从而可以快速分析和可视化传感器数据。通过将设备读数组织成时序格式,用户可以跟踪趋势、识别异常并根据设备性能简化运营决策。
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应用程序性能监控:将 Timestream 与应用程序监控工具结合使用,以发送有关服务性能随时间变化的指标。这种集成使工程师能够对应用程序性能进行历史分析,将其与业务指标相关联,并根据随时间推移的使用模式优化资源分配。
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自动化数据归档:配置 Timestream 插件以将数据写入 Timestream,同时管理保留期。此设置可以自动化归档策略,确保根据预定义的标准保留旧数据。这对于合规性和历史分析尤其有用,使企业能够以最少的人工干预来维护其数据生命周期。
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多应用程序指标聚合:利用 Timestream 插件将来自多个应用程序的指标聚合到 Timestream 中。通过创建统一的性能指标数据库,组织可以获得跨各种服务的整体洞察力,从而提高对系统范围性能的可见性并促进跨应用程序故障排除。
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