InfiniBand 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 InfiniBand and InfluxDB.

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Time series database
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Table of Contents

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 InfiniBand Telegraf plugin collects performance metrics from all InfiniBand devices installed on a Linux system, providing essential insights for monitoring network performance and reliability.

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

InfiniBand

This plugin gathers statistics for all InfiniBand devices and ports on the system. InfiniBand is a high-speed networking technology commonly used in high-performance computing and enterprise data centers. The plugin retrieves various performance counters from the system’s InfiniBand devices located in /sys/class/infiniband/<dev>/port/<port>/counters/. The metrics depend on the specific InfiniBand hardware and include various packet and error statistics that are essential for monitoring network health and performance. By utilizing this plugin, users can gain insights into the operational status of their InfiniBand networks, helping to identify potential issues and optimize performance.

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

InfiniBand

# Gets counters from all InfiniBand cards and ports installed
# This plugin ONLY supports Linux
[[inputs.infiniband]]
  # no configuration

  ## Collect RDMA counters
  # gather_rdma = false

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

InfiniBand

  1. Performance Monitoring in High-Performance Computing (HPC): Monitor the performance metrics of InfiniBand interconnects in a high-performance computing cluster. By analyzing metrics such as packet errors and throughput, system administrators can ensure optimal operation and quickly identify any performance degradation. This setup enhances the reliability of computational tasks by allowing timely interventions based on accurate monitoring data.

  2. Network Health Audits: Perform routine health checks of InfiniBand networks. The detailed metrics gathered, such as excessive buffer overruns and link integrity errors, provide valuable insights for network audits. By establishing baseline performance and watching for anomalies, IT professionals can ensure the stability and performance of critical infrastructures.

  3. Integration with Alerting Systems: Set up the InfiniBand plugin to work in conjunction with alerting systems to trigger notifications based on performance thresholds. For instance, if the number of link errors exceeds a predefined limit, an alert can be sent to the network operations team. This proactive approach ensures that potential issues are addressed before they impact business operations.

  4. Data Visualization Dashboards: Feed InfiniBand metrics to a visualization tool to create dashboards that display the real-time performance of the network. This can help stakeholders visualize critical data such as packet transmission rates and errors, facilitating better decision-making regarding network management and capacity planning.

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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