Azure Storage Queue and ServiceNow 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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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.

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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 output plugin streams metrics from Telegraf directly to a ServiceNow MID Server via HTTP, leveraging the nowmetric serializer for efficient integration with ServiceNow’s Operational Intelligence and Event Management.

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.

ServiceNow

Telegraf can be used to send metric data directly to a ServiceNow MID Server REST endpoint. Metrics are formatted either using ServiceNow’s Operational Intelligence (OI) format or JSONv2 format, enabling seamless integration with ServiceNow’s Event Management and Operational Intelligence platforms. The serializer batches metrics efficiently, reducing network overhead by minimizing the number of HTTP POST requests. This integration allows users to quickly leverage metrics in ServiceNow for enhanced observability, proactive incident management, and performance monitoring, with ServiceNow’s operational intelligence capabilities.

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

ServiceNow

[[outputs.http]]
  ## ServiceNow MID Server metrics endpoint
  url = "http://mid-server.example.com:9082/api/mid/sa/metrics"

  ## HTTP request method
  method = "POST"

  ## Basic Authentication credentials
  username = "evt.integration"
  password = "P@$$w0rd!"

  ## Data serialization format for ServiceNow
  data_format = "nowmetric"

  ## Metric format type: "oi" (default) or "jsonv2"
  nowmetric_format = "oi"

  ## HTTP Headers
  [outputs.http.headers]
    Content-Type = "application/json"
    Accept = "application/json"

  ## Optional timeout
  # timeout = "5s"

  ## TLS configuration options
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  # insecure_skip_verify = false

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.

ServiceNow

  1. Proactive Incident Management: Utilize the Telegraf and ServiceNow integration to stream infrastructure and application metrics in real-time to ServiceNow Event Management. Automatically trigger incidents or remediation workflows based on thresholds, significantly reducing incident detection and response times.

  2. End-to-End Application Monitoring: Deploy Telegraf agents across multiple layers of an application stack, sending performance metrics directly into ServiceNow. Leveraging ServiceNow’s Operational Intelligence, teams can correlate metrics across components, quickly identifying performance bottlenecks.

  3. Dynamic CI Performance Tracking: Integrate Telegraf metrics with ServiceNow’s CMDB by using this plugin to push performance data, allowing automatic updates of Configuration Item (CI) health states based on live metrics. This ensures an accurate and current state of infrastructure health in ServiceNow.

  4. Cloud Resource Optimization: Collect metrics from hybrid and multi-cloud infrastructures using Telegraf, streaming directly to ServiceNow. Leverage these metrics for real-time analytics, predictive capacity planning, and resource optimization, enabling proactive management and reduced operational costs.

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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