gNMI 和 Snowflake 集成

通过 Telegraf(由 InfluxData 构建的开源数据连接器)提供支持,实现强大的性能和简单的集成。

info

对于大规模实时查询,这不是推荐的配置。 为了实现查询和压缩优化、高速摄取和高可用性,您可能需要考虑gNMI 和 InfluxDB

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时间序列数据库
来源:DB Engines

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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,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

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,用于安全身份验证和数据传输。

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

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 方法使用遥测数据,从而可以实时监控网络设备。

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。 这种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

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"

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

gNMI

  1. 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。

  2. 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。

  3. 安全数据采集:配置具有 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。

  4. 灵活的数据处理:使用订阅选项自定义您想要根据特定需求或要求收集的遥测数据。

  5. 错误处理:该插件包括故障排除选项,用于处理常见问题,例如缺少指标名称或 TLS 握手失败。

Snowflake

  1. 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,从而创建集中的数据湖。 这种集成支持云数据上的复杂分析和机器学习工作流程。

  2. 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。 这使企业能够创建动态仪表板,可视化性能趋势和运营洞察,而无需手动模式管理。

  3. 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。

  4. 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。 这种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。

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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,第一的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

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