OpenStack and GroundWork 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 OpenStack 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

This plugin collects metrics from essential OpenStack services, facilitating the monitoring and management of cloud infrastructures.

This plugin writes to a GroundWork Monitor instance, allowing for effective metrics management and monitoring in a centralized manner.

Integration details

OpenStack

The OpenStack plugin allows users to collect performance metrics from various OpenStack services such as CINDER, GLANCE, HEAT, KEYSTONE, NEUTRON, and NOVA. It supports multiple OpenStack APIs to fetch critical metrics related to these services, enabling comprehensive monitoring and management of cloud resources. As organizations increasingly adopt OpenStack for their cloud infrastructure, this plugin plays a vital role in providing insights into resource usage, availability, and performance across the cloud environment. Configuration options allow for customized polling intervals and filtering unwanted tags to optimize performance and cardinals.

GroundWork

The GroundWork plugin enables Telegraf to send metrics to a GroundWork Monitor instance, specifically supporting GW8 and newer versions. This integration allows users to leverage the robust monitoring capabilities of GroundWork, enabling comprehensive oversight of metrics collected from diverse sources. Users can specify various parameters such as the GroundWork instance URL, agent IDs, and authentication credentials, allowing for a tailored fit within their existing monitoring setups. It also supports secret-store secrets to enhance security for sensitive fields like username and password. Tags used within the plugin provide fine-grained control over how metrics are categorized and displayed within the GroundWork interface, allowing for custom configurations that adapt to different monitoring needs. However, users should be aware that string metrics are currently not supported by GroundWork, impacting how they manage their data.

Configuration

OpenStack

[[inputs.openstack]]
  ## The recommended interval to poll is '30m'

  ## The identity endpoint to authenticate against and get the service catalog from.
  authentication_endpoint = "https://my.openstack.cloud:5000"

  ## The domain to authenticate against when using a V3 identity endpoint.
  # domain = "default"

  ## The project to authenticate as.
  # project = "admin"

  ## User authentication credentials. Must have admin rights.
  username = "admin"
  password = "password"

  ## Available services are:
  ## "agents", "aggregates", "cinder_services", "flavors", "hypervisors",
  ## "networks", "nova_services", "ports", "projects", "servers",
  ## "serverdiagnostics", "services", "stacks", "storage_pools", "subnets",
  ## "volumes"
  # enabled_services = ["services", "projects", "hypervisors", "flavors", "networks", "volumes"]

  ## Query all instances of all tenants for the volumes and server services
  ## NOTE: Usually this is only permitted for administrators!
  # query_all_tenants = true

  ## output secrets (such as adminPass(for server) and UserID(for volume)).
  # output_secrets = false

  ## Amount of time allowed to complete the HTTP(s) request.
  # timeout = "5s"

  ## HTTP Proxy support
  # http_proxy_url = ""

  ## Optional TLS Config
  # tls_ca = /path/to/cafile
  # tls_cert = /path/to/certfile
  # tls_key = /path/to/keyfile
  ## Use TLS but skip chain & host verification
  # insecure_skip_verify = false

  ## Options for tags received from Openstack
  # tag_prefix = "openstack_tag_"
  # tag_value = "true"

  ## Timestamp format for timestamp data received from Openstack.
  ## If false format is unix nanoseconds.
  # human_readable_timestamps = false

  ## Measure Openstack call duration
  # measure_openstack_requests = false

GroundWork

[[outputs.groundwork]]
  ## URL of your groundwork instance.
  url = "https://groundwork.example.com"

  ## Agent uuid for GroundWork API Server.
  agent_id = ""

  ## Username and password to access GroundWork API.
  username = ""
  password = ""

  ## Default application type to use in GroundWork client
  # default_app_type = "TELEGRAF"

  ## Default display name for the host with services(metrics).
  # default_host = "telegraf"

  ## Default service state.
  # default_service_state = "SERVICE_OK"

  ## The name of the tag that contains the hostname.
  # resource_tag = "host"

  ## The name of the tag that contains the host group name.
  # group_tag = "group"

Input and output integration examples

OpenStack

  1. Cross-Cloud Management: Leverage the OpenStack plugin to monitor and manage multiple OpenStack clouds from a single Telegraf instance. By aggregating metrics across different clouds, organizations can gain insights into resource utilization and optimize their cloud architecture for cost and performance.

  2. Automated Scaling Based on Metrics: Integrate the metrics gathered from OpenStack into an automated scaling solution. For example, if the plugin detects that a specific service’s performance is degraded, it can trigger auto-scaling rules to launch additional instances, ensuring that system performance remains optimal under varying workloads.

  3. Performance Monitoring Dashboard: Use data collected by the OpenStack Telegraf plugin to power real-time monitoring dashboards. This setup provides visualizations of key metrics from OpenStack services, enabling stakeholders to quickly identify trends, pinpoint issues, and make data-driven decisions in managing their cloud infrastructure.

  4. Reporting and Analysis of Service Availability: By utilizing the metrics collected from various OpenStack services, teams can generate detailed reports on service availability and performance over time. This information can help identify recurring issues, improve service delivery, and make informed decisions regarding changes in infrastructure or service configuration.

GroundWork

  1. Centralized Monitoring Dashboard: Use the GroundWork plugin to aggregate metrics from multiple Telegraf instances into a single GroundWork Monitor dashboard. This configuration offers complete visibility into system health across various components, enabling swift identification of performance bottlenecks and improved incident response times.

  2. Service Health Monitoring with Alerts: Configure this plugin to send critical service metrics to GroundWork, establishing a robust alerting system. Metrics such as CPU usage and service statuses can trigger alerts based on threshold values, informing administrators of potential issues before they escalate, thereby enhancing system reliability.

  3. Historical Data Analysis: Leverage the historical metric capabilities of GroundWork using this plugin to conduct trend analysis over time. This application allows organizations to make data-driven decisions based on comprehensive historical performance metrics, which can assist in capacity planning and optimize resource allocation.

  4. Custom Service Tags for Enhanced Monitoring: Extend the functionality of this plugin by utilizing custom tags for different services and hosts. By customizing these tags, users can filter and categorize metrics more effectively within their monitoring framework, leading to tailored monitoring experiences that align specifically with business objectives.

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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