gNMI and Librato Integration

Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider gNMI and InfluxDB.

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Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

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Input and output integration overview

The gNMI (gRPC Network Management Interface) Input Plugin collects telemetry data from network devices using the gNMI Subscribe method. It supports TLS for secure authentication and data transmission.

The Librato plugin for Telegraf is designed to facilitate seamless integration with the Librato Metrics API, allowing for efficient metric reporting and monitoring.

Integration details

gNMI

This input plugin is vendor-agnostic and can be used with any platform that supports the gNMI specification. It consumes telemetry data based on the gNMI Subscribe method, allowing for real-time monitoring of network devices.

Librato

The Librato plugin enables Telegraf to send metrics to the Librato Metrics API. To authenticate, users must provide an api_user and api_token, which can be acquired from the Librato account settings. This integration allows for efficient monitoring and reporting of custom metrics within the Librato platform. The plugin also utilizes a source_tag option that can enrich the metrics with contextual information from Point Tags; however, it does not currently support sending associated Point Tags. It is essential to note that any point value sent that cannot be converted to a float64 type will be skipped, ensuring that only valid metrics are processed and sent to Librato. The plugin also supports secret-store options for managing sensitive authentication credentials securely, facilitating best practices in credential management.

Configuration

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"

Librato

[[outputs.librato]]
  ## Librato API Docs
  ## http://dev.librato.com/v1/metrics-authentication
  ## Librato API user
  api_user = "[email protected]" # required.
  ## Librato API token
  api_token = "my-secret-token" # required.
  ## Debug
  # debug = false
  ## Connection timeout.
  # timeout = "5s"
  ## Output source Template (same as graphite buckets)
  ## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md#graphite
  ## This template is used in librato's source (not metric's name)
  template = "host"

Input and output integration examples

gNMI

  1. Monitoring Cisco Devices: Use the gNMI plugin to collect telemetry data from Cisco IOS XR, NX-OS, or IOS XE devices for performance monitoring.

  2. Real-time Network Insights: With the gNMI plugin, network administrators can gain insights into real-time metrics such as interface statistics and CPU usage.

  3. Secure Data Collection: Configure the gNMI plugin with TLS settings to ensure secure communication while collecting sensitive telemetry data from devices.

  4. Flexible Data Handling: Use the subscription options to customize which telemetry data you want to collect based on specific needs or requirements.

  5. Error Handling: The plugin includes troubleshooting options to handle common issues like missing metric names or TLS handshake failures.

Librato

  1. Real-time Application Monitoring: Utilize Librato to collect performance metrics from a web application in real-time. This setup involves sending response times, error rates, and user interactions to Librato, allowing developers to monitor the application’s health and performance metrics closely. By analyzing these metrics, teams can quickly identify and address performance bottlenecks or application failures before they impact end users.

  2. Infrastructure Metrics Aggregation: Leverage this plugin to gather and send metrics from various infrastructure components, such as servers or containers, to Librato for centralized monitoring. Configuring the plugin to send CPU, memory usage, and disk I/O metrics enables system administrators to have a comprehensive view of infrastructure performance, assisting in capacity planning and resource optimization strategies.

  3. Custom Metrics for Business Operations: Feed business-specific metrics, such as sales transactions or user sign-ups, to the Librato service using this plugin. By tracking these custom metrics, businesses can gain insights into their operational performance and make data-driven decisions to enhance their strategies, marketing efforts, or product development initiatives.

  4. Anomaly Detection in Metrics: Implement monitoring tools that utilize machine learning for anomaly detection. By continuously sending real-time metrics to Librato, teams can analyze trends and automatically flag unusual behavior, such as sudden spikes in latency or unusual traffic patterns, enabling timely intervention and troubleshooting.

Feedback

Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.

Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

See Ways to Get Started

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