ctrlX Data Layer and Sensu Integration
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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 ctrlX plugin is designed to gather data seamlessly from the ctrlX Data Layer middleware, widely used in industrial automation.
This plugin writes metrics events to Sensu via its HTTP events API, enabling seamless integration with the Sensu monitoring platform.
Integration details
ctrlX Data Layer
The ctrlX Telegraf plugin provides a means to gather data from the ctrlX Data Layer, a communication middleware designed for professional automation applications. This plugin allows users to connect to ctrlX CORE devices, enabling the collection and monitoring of various metrics related to industrial and building automation, robotics, and IoT. The configuration options allow for detailed specifications of connection settings, subscription properties, and sampling rates, facilitating effective integration with the ctrlX Data Layer to meet customized monitoring needs, while leveraging the unique capabilities of the ctrlX platform.
Sensu
This plugin writes metrics events to Sensu via its HTTP events API. Sensu is a monitoring system that enables users to collect, analyze, and manage metrics from various components in their infrastructure. The plugin facilitates the integration of Telegraf, a server agent for collecting and reporting metrics, with the Sensu monitoring platform. Users can configure settings such as backend and agent API URLs, API keys for authentication, and optional TLS settings. The plugin’s core functionality is centered around sending metric events, including check and entity specifications, to Sensu, allowing for comprehensive monitoring and alerting. The API reference provides extensive details about the events and metrics structure, ensuring users can efficiently leverage Sensu’s capabilities for observability and incident response.
Configuration
ctrlX Data Layer
[[inputs.ctrlx_datalayer]]
## Hostname or IP address of the ctrlX CORE Data Layer server
## example: server = "localhost" # Telegraf is running directly on the device
## server = "192.168.1.1" # Connect to ctrlX CORE remote via IP
## server = "host.example.com" # Connect to ctrlX CORE remote via hostname
## server = "10.0.2.2:8443" # Connect to ctrlX CORE Virtual from development environment
server = "localhost"
## Authentication credentials
username = "boschrexroth"
password = "boschrexroth"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Timeout for HTTP requests. (default: "10s")
# timeout = "10s"
## Create a ctrlX Data Layer subscription.
## It is possible to define multiple subscriptions per host. Each subscription can have its own
## sampling properties and a list of nodes to subscribe to.
## All subscriptions share the same credentials.
[[inputs.ctrlx_datalayer.subscription]]
## The name of the measurement. (default: "ctrlx")
measurement = "memory"
## Configure the ctrlX Data Layer nodes which should be subscribed.
## address - node address in ctrlX Data Layer (mandatory)
## name - field name to use in the output (optional, default: base name of address)
## tags - extra node tags to be added to the output metric (optional)
## Note:
## Use either the inline notation or the bracketed notation, not both.
## The tags property is only supported in bracketed notation due to toml parser restrictions
## Examples:
## Inline notation
nodes=[
{name="available", address="framework/metrics/system/memavailable-mb"},
{name="used", address="framework/metrics/system/memused-mb"},
]
## Bracketed notation
# [[inputs.ctrlx_datalayer.subscription.nodes]]
# name ="available"
# address="framework/metrics/system/memavailable-mb"
# ## Define extra tags related to node to be added to the output metric (optional)
# [inputs.ctrlx_datalayer.subscription.nodes.tags]
# node_tag1="node_tag1"
# node_tag2="node_tag2"
# [[inputs.ctrlx_datalayer.subscription.nodes]]
# name ="used"
# address="framework/metrics/system/memused-mb"
## The switch "output_json_string" enables output of the measurement as json.
## That way it can be used in in a subsequent processor plugin, e.g. "Starlark Processor Plugin".
# output_json_string = false
## Define extra tags related to subscription to be added to the output metric (optional)
# [inputs.ctrlx_datalayer.subscription.tags]
# subscription_tag1 = "subscription_tag1"
# subscription_tag2 = "subscription_tag2"
## The interval in which messages shall be sent by the ctrlX Data Layer to this plugin. (default: 1s)
## Higher values reduce load on network by queuing samples on server side and sending as a single TCP packet.
# publish_interval = "1s"
## The interval a "keepalive" message is sent if no change of data occurs. (default: 60s)
## Only used internally to detect broken network connections.
# keep_alive_interval = "60s"
## The interval an "error" message is sent if an error was received from a node. (default: 10s)
## Higher values reduce load on output target and network in case of errors by limiting frequency of error messages.
# error_interval = "10s"
## The interval that defines the fastest rate at which the node values should be sampled and values captured. (default: 1s)
## The sampling frequency should be adjusted to the dynamics of the signal to be sampled.
## Higher sampling frequencies increases load on ctrlX Data Layer.
## The sampling frequency can be higher, than the publish interval. Captured samples are put in a queue and sent in publish interval.
## Note: The minimum sampling interval can be overruled by a global setting in the ctrlX Data Layer configuration ('datalayer/subscriptions/settings').
# sampling_interval = "1s"
## The requested size of the node value queue. (default: 10)
## Relevant if more values are captured than can be sent.
# queue_size = 10
## The behaviour of the queue if it is full. (default: "DiscardOldest")
## Possible values:
## - "DiscardOldest"
## The oldest value gets deleted from the queue when it is full.
## - "DiscardNewest"
## The newest value gets deleted from the queue when it is full.
# queue_behaviour = "DiscardOldest"
## The filter when a new value will be sampled. (default: 0.0)
## Calculation rule: If (abs(lastCapturedValue - newValue) > dead_band_value) capture(newValue).
# dead_band_value = 0.0
## The conditions on which a sample should be captured and thus will be sent as a message. (default: "StatusValue")
## Possible values:
## - "Status"
## Capture the value only, when the state of the node changes from or to error state. Value changes are ignored.
## - "StatusValue"
## Capture when the value changes or the node changes from or to error state.
## See also 'dead_band_value' for what is considered as a value change.
## - "StatusValueTimestamp":
## Capture even if the value is the same, but the timestamp of the value is newer.
## Note: This might lead to high load on the network because every sample will be sent as a message
## even if the value of the node did not change.
# value_change = "StatusValue"
Sensu
[[outputs.sensu]]
## BACKEND API URL is the Sensu Backend API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the corresponding backend API path
## /api/core/v2/namespaces/:entity_namespace/events/:entity_name/:check_name).
##
## Backend Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## AGENT API URL is the Sensu Agent API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the correspeonding agent API path (/events).
##
## Agent API Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## NOTE: if backend_api_url and agent_api_url and api_key are set, the output
## plugin will use backend_api_url. If backend_api_url and agent_api_url are
## not provided, the output plugin will default to use an agent_api_url of
## http://127.0.0.1:3031
##
# backend_api_url = "http://127.0.0.1:8080"
# agent_api_url = "http://127.0.0.1:3031"
## API KEY is the Sensu Backend API token
## Generate a new API token via:
##
## $ sensuctl cluster-role create telegraf --verb create --resource events,entities
## $ sensuctl cluster-role-binding create telegraf --cluster-role telegraf --group telegraf
## $ sensuctl user create telegraf --group telegraf --password REDACTED
## $ sensuctl api-key grant telegraf
##
## For more information on Sensu RBAC profiles & API tokens, please visit:
## - https://docs.sensu.io/sensu-go/latest/reference/rbac/
## - https://docs.sensu.io/sensu-go/latest/reference/apikeys/
##
# api_key = "${SENSU_API_KEY}"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Timeout for HTTP message
# timeout = "5s"
## HTTP Content-Encoding for write request body, can be set to "gzip" to
## compress body or "identity" to apply no encoding.
# content_encoding = "identity"
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of
## the table
## Sensu Event details
##
## Below are the event details to be sent to Sensu. The main portions of the
## event are the check, entity, and metrics specifications. For more information
## on Sensu events and its components, please visit:
## - Events - https://docs.sensu.io/sensu-go/latest/reference/events
## - Checks - https://docs.sensu.io/sensu-go/latest/reference/checks
## - Entities - https://docs.sensu.io/sensu-go/latest/reference/entities
## - Metrics - https://docs.sensu.io/sensu-go/latest/reference/events#metrics
##
## Check specification
## The check name is the name to give the Sensu check associated with the event
## created. This maps to check.metadata.name in the event.
[outputs.sensu.check]
name = "telegraf"
## Entity specification
## Configure the entity name and namespace, if necessary. This will be part of
## the entity.metadata in the event.
##
## NOTE: if the output plugin is configured to send events to a
## backend_api_url and entity_name is not set, the value returned by
## os.Hostname() will be used; if the output plugin is configured to send
## events to an agent_api_url, entity_name and entity_namespace are not used.
# [outputs.sensu.entity]
# name = "server-01"
# namespace = "default"
## Metrics specification
## Configure the tags for the metrics that are sent as part of the Sensu event
# [outputs.sensu.tags]
# source = "telegraf"
## Configure the handler(s) for processing the provided metrics
# [outputs.sensu.metrics]
# handlers = ["influxdb","elasticsearch"]
Input and output integration examples
ctrlX Data Layer
-
Industrial Automation Monitoring: Utilize this plugin to continuously monitor key performance indicators from a manufacturing system controlled by ctrlX CORE devices. By subscribing to specific data nodes that provide real-time metrics such as resource availability or machine uptime, manufacturers can dynamically adjust their operations for increased efficiency and minimal downtime.
-
Energy Consumption Analysis: Collect energy consumption data from IoT-enabled ctrlX CORE platforms in a smart building setup. By analyzing trends and patterns in energy use, facility managers can optimize operating strategies, reduce energy costs, and support sustainability initiatives, making informed decisions about resource allocation and predictive maintenance.
-
Predictive Maintenance for Robotics: Gather telemetry data from robotics applications deployed in warehousing environments. By monitoring vibration, temperature, and operational parameters in real-time, organizations can predict equipment failures before they occur, leading to reduced maintenance costs and enhanced robotic system uptime through timely interventions.
-
Cross-Platform Data Integration: Connect data gathered from ctrlX CORE devices into a centralized Cloud data warehouse using this plugin. By streaming real-time metrics to other systems, organizations can create a unified view of operational performance across various manufacturing and operational systems, enabling data-driven decision-making across diverse platforms.
Sensu
-
Real-Time Infrastructure Monitoring: Utilize the Sensu plugin to send performance metrics from various servers and services directly to Sensu. This real-time data flow enables teams to visualize infrastructure health, track resource usage, and receive immediate alerts for any anomalies detected. By centralizing monitoring through Sensu, organizations can create a holistic view of their systems and respond swiftly to issues.
-
Automated Incident Response Workflows: Leverage the plugin to automatically trigger incident response workflows based on the metrics events sent to Sensu. For example, if CPU usage exceeds a defined threshold, the Sensu system can be configured to alert the operations team, which can then initiate automated remediation processes, reducing downtime and maintaining system reliability. This integration allows for proactive management of system resources.
-
Dynamic Scaling of Resources: Use the Sensu plugin to feed metrics into an auto-scaling system that adjusts resources based on demand. By tracking metrics like request load and resource utilization, organizations can automatically scale their infrastructure up or down, ensuring optimal performance and cost efficiency without manual intervention.
-
Centralized Logging and Monitoring: Combine the Sensu with logging tools to send logs and performance metrics to a centralized monitoring system. This comprehensive approach allows teams to correlate logs with metric events, providing deeper insights into system behavior and performance, which aids in troubleshooting and performance optimization over time.
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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