Azure Storage Queue 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 Azure Storage Queue 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 gathers sizes of Azure Storage Queues, providing users with metrics that enhance observability and management of their storage resources.

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

Integration details

Azure Storage Queue

The Azure Storage Queue plugin allows users to gather various metrics concerning the size and message age of Azure Storage Queues. This plugin connects to Azure Storage, requiring specific credentials and offers configurable options to enhance performance. By collecting metrics, users gain valuable insights into the performance of their storage queues, enabling them to monitor usage patterns, peak loads, and optimize storage management effectively. The integration with Azure’s storage infrastructure provides a straightforward way to monitor queue metrics, ensuring that users can react to changes promptly, maintaining the efficiency and reliability of their applications.

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

Azure Storage Queue

[[inputs.azure_storage_queue]]
  ## Required Azure Storage Account name
  account_name = "mystorageaccount"

  ## Required Azure Storage Account access key
  account_key = "storageaccountaccesskey"

  ## Set to false to disable peeking age of oldest message (executes faster)
  # peek_oldest_message_age = true

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

Azure Storage Queue

  1. Monitoring Queue Performance in Real-time: Use the Azure Storage Queue plugin to continuously track the size and age of messages in queues, providing operators with real-time insights. This information can help teams understand throughput and delays, enabling them to adjust processing rates or troubleshoot bottlenecks.

  2. Dynamic Alerting Based on Queue Metrics: Integrate metrics from the Azure Storage Queue plugin into an alerting system. By defining thresholds for message age and queue size, organizations can automate notifications, ensuring they promptly address situations where queues become too long or messages are delayed, maintaining a healthy and responsive system environment.

  3. Optimizing Cost Management: Leverage the insights from the Azure Storage Queue metrics to identify periods of inactivity and implement cost-saving measures by adjusting storage scales. By analyzing queue size trends, organizations can make informed decisions about resource allocation, effectively balancing performance needs with cost efficiency.

  4. Enhancing Application Fault Tolerance: Use the age metrics of the oldest message to design smarter retry strategies within applications. In scenarios where message processing fails, understanding how long messages sit in the queue allows developers to fine-tune their error handling logic, enhancing the resilience and reliability of their applications.

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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