Azure Event Hubs 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 Azure Event Hubs Input Plugin allows Telegraf to consume data from Azure Event Hubs and Azure IoT Hub, enabling efficient data processing and monitoring of event streams from these cloud services.
This plugin writes metrics events to Sensu via its HTTP events API, enabling seamless integration with the Sensu monitoring platform.
Integration details
Azure Event Hubs
This plugin serves as a consumer for Azure Event Hubs and Azure IoT Hub, allowing users to ingest data streams from these platforms efficiently. Azure Event Hubs is a highly scalable data streaming platform and event ingestion service capable of receiving and processing millions of events per second, while Azure IoT Hub enables secure device-to-cloud and cloud-to-device communication in IoT applications. The Event Hub Input Plugin interacts seamlessly with these services, providing reliable message consumption and stream processing capabilities. Key features include dynamic management of consumer groups, message tracking to prevent data loss, and customizable settings for prefetch counts, user agents, and metadata handling. This plugin is designed to support a range of use cases, including real-time telemetry data collection, IoT data processing, and integration with various data analysis and monitoring tools within the broader Azure ecosystem.
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
Azure Event Hubs
[[inputs.eventhub_consumer]]
## The default behavior is to create a new Event Hub client from environment variables.
## This requires one of the following sets of environment variables to be set:
##
## 1) Expected Environment Variables:
## - "EVENTHUB_CONNECTION_STRING"
##
## 2) Expected Environment Variables:
## - "EVENTHUB_NAMESPACE"
## - "EVENTHUB_NAME"
## - "EVENTHUB_KEY_NAME"
## - "EVENTHUB_KEY_VALUE"
## 3) Expected Environment Variables:
## - "EVENTHUB_NAMESPACE"
## - "EVENTHUB_NAME"
## - "AZURE_TENANT_ID"
## - "AZURE_CLIENT_ID"
## - "AZURE_CLIENT_SECRET"
## Uncommenting the option below will create an Event Hub client based solely on the connection string.
## This can either be the associated environment variable or hard coded directly.
## If this option is uncommented, environment variables will be ignored.
## Connection string should contain EventHubName (EntityPath)
# connection_string = ""
## Set persistence directory to a valid folder to use a file persister instead of an in-memory persister
# persistence_dir = ""
## Change the default consumer group
# consumer_group = ""
## By default the event hub receives all messages present on the broker, alternative modes can be set below.
## The timestamp should be in https://github.com/toml-lang/toml#offset-date-time format (RFC 3339).
## The 3 options below only apply if no valid persister is read from memory or file (e.g. first run).
# from_timestamp =
# latest = true
## Set a custom prefetch count for the receiver(s)
# prefetch_count = 1000
## Add an epoch to the receiver(s)
# epoch = 0
## Change to set a custom user agent, "telegraf" is used by default
# user_agent = "telegraf"
## To consume from a specific partition, set the partition_ids option.
## An empty array will result in receiving from all partitions.
# partition_ids = ["0","1"]
## Max undelivered messages
## This plugin uses tracking metrics, which ensure messages are read to
## outputs before acknowledging them to the original broker to ensure data
## is not lost. This option sets the maximum messages to read from the
## broker that have not been written by an output.
##
## This value needs to be picked with awareness of the agent's
## metric_batch_size value as well. Setting max undelivered messages too high
## can result in a constant stream of data batches to the output. While
## setting it too low may never flush the broker's messages.
# max_undelivered_messages = 1000
## Set either option below to true to use a system property as timestamp.
## You have the choice between EnqueuedTime and IoTHubEnqueuedTime.
## It is recommended to use this setting when the data itself has no timestamp.
# enqueued_time_as_ts = true
# iot_hub_enqueued_time_as_ts = true
## Tags or fields to create from keys present in the application property bag.
## These could for example be set by message enrichments in Azure IoT Hub.
# application_property_tags = []
# application_property_fields = []
## Tag or field name to use for metadata
## By default all metadata is disabled
# sequence_number_field = "SequenceNumber"
# enqueued_time_field = "EnqueuedTime"
# offset_field = "Offset"
# partition_id_tag = "PartitionID"
# partition_key_tag = "PartitionKey"
# iot_hub_device_connection_id_tag = "IoTHubDeviceConnectionID"
# iot_hub_auth_generation_id_tag = "IoTHubAuthGenerationID"
# iot_hub_connection_auth_method_tag = "IoTHubConnectionAuthMethod"
# iot_hub_connection_module_id_tag = "IoTHubConnectionModuleID"
# iot_hub_enqueued_time_field = "IoTHubEnqueuedTime"
## Data format to consume.
## Each data format has its own unique set of configuration options, read
## more about them here:
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
data_format = "influx"
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
Azure Event Hubs
-
Real-Time IoT Device Monitoring: Use the Azure Event Hubs Plugin to monitor telemetry data from IoT devices like sensors and actuators. By streaming device data into monitoring dashboards, organizations can gain insights into system performances, track usage patterns, and quickly respond to irregularities. This setup allows for proactive management of devices, improving operational efficiency and reducing downtime.
-
Event-Driven Data Processing Workflows: Leverage this plugin to trigger data processing workflows in response to events received from Azure Event Hubs. For instance, when a new event arrives, it can initiate data transformation, aggregation, or storage processes, allowing businesses to automate their workflows more effectively. This integration enhances responsiveness and streamlines operations across systems.
-
Integration with Analytics Platforms: Implement the plugin to funnel event data into analytics platforms like Azure Synapse or Power BI. By integrating real-time streaming data into analytics tools, organizations can perform comprehensive data analysis, drive business intelligence efforts, and create interactive visualizations that inform decision-making.
-
Cross-Platform Data Sync: Utilize the Azure Event Hubs Plugin to synchronize data streams across diverse systems or platforms. By consuming data from Azure Event Hubs and forwarding it to other systems like databases or cloud storage, organizations can maintain consistent and up-to-date information across their entire architecture, enabling cohesive data strategies.
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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