gNMI and OpenSearch 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.

See Ways to Get Started

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 OpenSearch Output Plugin allows users to send metrics directly to an OpenSearch instance using HTTP, thus facilitating effective data management and analytics within the OpenSearch ecosystem.

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.

OpenSearch

The OpenSearch Telegraf Plugin integrates with the OpenSearch database via HTTP, allowing for the streamlined collection and storage of metrics. As a powerful tool designed specifically for OpenSearch releases from 2.x, the plugin provides robust features while offering compatibility with 1.x through the original Elasticsearch plugin. This plugin facilitates the creation and management of indexes in OpenSearch, automatically managing templates and ensuring that data is structured efficiently for analysis. The plugin supports various configuration options such as index names, authentication, health checks, and value handling, allowing it to be tailored to diverse operational requirements. Its capabilities make it essential for organizations looking to harness the power of OpenSearch for metrics storage and querying.

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"

OpenSearch

[[outputs.opensearch]]
  ## URLs
  ## The full HTTP endpoint URL for your OpenSearch instance. Multiple URLs can
  ## be specified as part of the same cluster, but only one URLs is used to
  ## write during each interval.
  urls = ["http://node1.os.example.com:9200"]

  ## Index Name
  ## Target index name for metrics (OpenSearch will create if it not exists).
  ## This is a Golang template (see https://pkg.go.dev/text/template)
  ## You can also specify
  ## metric name (`{{.Name}}`), tag value (`{{.Tag "tag_name"}}`), field value (`{{.Field "field_name"}}`)
  ## If the tag does not exist, the default tag value will be empty string "".
  ## the timestamp (`{{.Time.Format "xxxxxxxxx"}}`).
  ## For example: "telegraf-{{.Time.Format \"2006-01-02\"}}-{{.Tag \"host\"}}" would set it to telegraf-2023-07-27-HostName
  index_name = ""

  ## Timeout
  ## OpenSearch client timeout
  # timeout = "5s"

  ## Sniffer
  ## Set to true to ask OpenSearch a list of all cluster nodes,
  ## thus it is not necessary to list all nodes in the urls config option
  # enable_sniffer = false

  ## GZIP Compression
  ## Set to true to enable gzip compression
  # enable_gzip = false

  ## Health Check Interval
  ## Set the interval to check if the OpenSearch nodes are available
  ## Setting to "0s" will disable the health check (not recommended in production)
  # health_check_interval = "10s"

  ## Set the timeout for periodic health checks.
  # health_check_timeout = "1s"
  ## HTTP basic authentication details.
  # username = ""
  # password = ""
  ## HTTP bearer token authentication details
  # auth_bearer_token = ""

  ## Optional TLS Config
  ## 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"
  ## Send the specified TLS server name via SNI
  # tls_server_name = "kubernetes.example.com"
  ## Use TLS but skip chain & host verification
  # insecure_skip_verify = false

  ## Template Config
  ## Manage templates
  ## Set to true if you want telegraf to manage its index template.
  ## If enabled it will create a recommended index template for telegraf indexes
  # manage_template = true

  ## Template Name
  ## The template name used for telegraf indexes
  # template_name = "telegraf"

  ## Overwrite Templates
  ## Set to true if you want telegraf to overwrite an existing template
  # overwrite_template = false

  ## Document ID
  ## If set to true a unique ID hash will be sent as
  ## sha256(concat(timestamp,measurement,series-hash)) string. It will enable
  ## data resend and update metric points avoiding duplicated metrics with
  ## different id's
  # force_document_id = false

  ## Value Handling
  ## Specifies the handling of NaN and Inf values.
  ## This option can have the following values:
  ##    none    -- do not modify field-values (default); will produce an error
  ##               if NaNs or infs are encountered
  ##    drop    -- drop fields containing NaNs or infs
  ##    replace -- replace with the value in "float_replacement_value" (default: 0.0)
  ##               NaNs and inf will be replaced with the given number, -inf with the negative of that number
  # float_handling = "none"
  # float_replacement_value = 0.0

  ## Pipeline Config
  ## To use a ingest pipeline, set this to the name of the pipeline you want to use.
  # use_pipeline = "my_pipeline"

  ## Pipeline Name
  ## Additionally, you can specify a tag name using the notation (`{{.Tag "tag_name"}}`)
  ## which will be used as the pipeline name (e.g. "{{.Tag \"os_pipeline\"}}").
  ## If the tag does not exist, the default pipeline will be used as the pipeline.
  ## If no default pipeline is set, no pipeline is used for the metric.
  # default_pipeline = ""

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.

OpenSearch

  1. Dynamic Indexing for Time-Series Data: Utilize the OpenSearch Telegraf plugin to dynamically create indexes for time-series metrics, ensuring that data is stored in an organized manner conducive to time-based queries. By defining index patterns using Go templates, users can leverage the plugin to create daily or monthly indexes, which can greatly simplify data management and retrieval over time, thus enhancing analytical performance.

  2. Centralized Logging for Multi-Tenant Applications: Implement the OpenSearch plugin in a multi-tenant application where each tenant’s logs are sent to separate indexes. This enables targeted analysis and monitoring for each tenant while maintaining data isolation. By utilizing the index name templating feature, users can automatically create tenant-specific indexes, which not only streamlines the process but also enhances security and accessibility for tenant data.

  3. Integration with Machine Learning for Anomaly Detection: Leverage the OpenSearch plugin alongside machine learning tools to automatically detect anomalies in metrics data. By configuring the plugin to send real-time metrics to OpenSearch, users can apply machine learning models on the incoming data streams to identify outliers or unusual patterns, facilitating proactive monitoring and swift remedial actions.

  4. Enhanced Monitoring Dashboards with OpenSearch: Use the metrics collected from OpenSearch to create real-time dashboards that provide insights into system performance. By feeding metrics into OpenSearch, organizations can utilize OpenSearch Dashboards to visualize key performance indicators, allowing operations teams to quickly assess health and performance, and making data-driven decisions.

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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