目录
输入和输出集成概述
gNMI (gRPC 网络管理接口) 输入插件使用 gNMI Subscribe 方法从网络设备收集遥测数据。它支持 TLS 以实现安全身份验证和数据传输。
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。此插件提供各种配置选项,用于身份验证、数据组织和保留设置。
集成详情
gNMI
此输入插件与供应商无关,可以与任何支持 gNMI 规范的平台一起使用。它基于 gNMI Subscribe 方法消耗遥测数据,从而可以实时监控网络设备。
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,并支持灵活的配置,用于身份验证、数据组织和保留管理。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与数据写入期间 AWS 错误相关的常见问题的机制,例如用于节流的重试逻辑以及根据需要创建表的能力。
配置
gNMI
[[inputs.gnmi]]
## Address and port of the gNMI GRPC server
addresses = ["10.49.234.114:57777"]
## define credentials
username = "cisco"
password = "cisco"
## gNMI encoding requested (one of: "proto", "json", "json_ietf", "bytes")
# encoding = "proto"
## redial in case of failures after
# redial = "10s"
## gRPC Keepalive settings
## See https://pkg.go.dev/google.golang.org/grpc/keepalive
## The client will ping the server to see if the transport is still alive if it has
## not see any activity for the given time.
## If not set, none of the keep-alive setting (including those below) will be applied.
## If set and set below 10 seconds, the gRPC library will apply a minimum value of 10s will be used instead.
# keepalive_time = ""
## Timeout for seeing any activity after the keep-alive probe was
## sent. If no activity is seen the connection is closed.
# keepalive_timeout = ""
## gRPC Maximum Message Size
# max_msg_size = "4MB"
## Enable to get the canonical path as field-name
# canonical_field_names = false
## Remove leading slashes and dots in field-name
# trim_field_names = false
## Guess the path-tag if an update does not contain a prefix-path
## Supported values are
## none -- do not add a 'path' tag
## common path -- use the common path elements of all fields in an update
## subscription -- use the subscription path
# path_guessing_strategy = "none"
## Prefix tags from path keys with the path element
# prefix_tag_key_with_path = false
## Optional client-side TLS to authenticate the device
## Set to true/false to enforce TLS being enabled/disabled. If not set,
## enable TLS only if any of the other options are specified.
# tls_enable =
## Trusted root certificates for server
# tls_ca = "/path/to/cafile"
## Used for TLS client certificate authentication
# tls_cert = "/path/to/certfile"
## Used for TLS client certificate authentication
# tls_key = "/path/to/keyfile"
## Password for the key file if it is encrypted
# tls_key_pwd = ""
## Send the specified TLS server name via SNI
# tls_server_name = "kubernetes.example.com"
## Minimal TLS version to accept by the client
# tls_min_version = "TLS12"
## List of ciphers to accept, by default all secure ciphers will be accepted
## See https://pkg.go.dev/crypto/tls#pkg-constants for supported values.
## Use "all", "secure" and "insecure" to add all support ciphers, secure
## suites or insecure suites respectively.
# tls_cipher_suites = ["secure"]
## Renegotiation method, "never", "once" or "freely"
# tls_renegotiation_method = "never"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## gNMI subscription prefix (optional, can usually be left empty)
## See: https://github.com/openconfig/reference/blob/master/rpc/gnmi/gnmi-specification.md#222-paths
# origin = ""
# prefix = ""
# target = ""
## Vendor specific options
## This defines what vendor specific options to load.
## * Juniper Header Extension (juniper_header): some sensors are directly managed by
## Linecard, which adds the Juniper GNMI Header Extension. Enabling this
## allows the decoding of the Extension header if present. Currently this knob
## adds component, component_id & sub_component_id as additional tags
# vendor_specific = []
## YANG model paths for decoding IETF JSON payloads
## Model files are loaded recursively from the given directories. Disabled if
## no models are specified.
# yang_model_paths = []
## Define additional aliases to map encoding paths to measurement names
# [inputs.gnmi.aliases]
# ifcounters = "openconfig:/interfaces/interface/state/counters"
[[inputs.gnmi.subscription]]
## Name of the measurement that will be emitted
name = "ifcounters"
## Origin and path of the subscription
## See: https://github.com/openconfig/reference/blob/master/rpc/gnmi/gnmi-specification.md#222-paths
##
## origin usually refers to a (YANG) data model implemented by the device
## and path to a specific substructure inside it that should be subscribed
## to (similar to an XPath). YANG models can be found e.g. here:
## https://github.com/YangModels/yang/tree/master/vendor/cisco/xr
origin = "openconfig-interfaces"
path = "/interfaces/interface/state/counters"
## Subscription mode ("target_defined", "sample", "on_change") and interval
subscription_mode = "sample"
sample_interval = "10s"
## Suppress redundant transmissions when measured values are unchanged
# suppress_redundant = false
## If suppression is enabled, send updates at least every X seconds anyway
# heartbeat_interval = "60s"
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
gNMI
-
监控 Cisco 设备:使用 gNMI 插件从 Cisco IOS XR、NX-OS 或 IOS XE 设备收集遥测数据以进行性能监控。
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实时网络洞察:借助 gNMI 插件,网络管理员可以深入了解实时指标,例如接口统计信息和 CPU 使用率。
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安全数据采集:配置带有 TLS 设置的 gNMI 插件,以确保在从设备收集敏感遥测数据时进行安全通信。
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灵活的数据处理:使用订阅选项自定义您要根据特定需求或要求收集的遥测数据。
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错误处理:该插件包含故障排除选项,用于处理常见问题,例如缺少指标名称或 TLS 握手失败。
AWS Timestream
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物联网数据指标:使用 Timestream 插件将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:利用 Timestream 和应用程序监控工具,可以随时间推移发送有关服务性能的指标。此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,并根据随时间推移查看的使用模式优化资源分配。
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自动化数据存档:配置 Timestream 插件以将数据写入 Timestream,同时管理保留期。此设置可以自动化存档策略,确保根据预定义的标准保存旧数据。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。通过创建性能指标的统一数据库,组织可以获得跨各种服务的整体洞察力,从而提高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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