Azure Storage Queue and Dynatrace Integration

Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.

info

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.

5B+

Telegraf downloads

#1

Time series database
Source: DB Engines

1B+

Downloads of InfluxDB

2,800+

Contributors

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.

See Ways to Get Started

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.

The Dynatrace plugin allows users to send metrics collected by Telegraf directly to Dynatrace for monitoring and analysis. This integration enhances the observability of systems and applications, providing valuable insights into performance and operational health.

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.

Dynatrace

The Dynatrace plugin for Telegraf facilitates the transmission of metrics to the Dynatrace platform via the Dynatrace Metrics API V2. This plugin can function in two modes: it can run alongside the Dynatrace OneAgent, which automates authentication, or it can operate in a standalone configuration that requires manual specification of the URL and API token for environments without a OneAgent. The plugin primarily reports metrics as gauges unless explicitly configured to treat certain metrics as delta counters using the available config options. This feature empowers users to customize the behavior of metrics sent to Dynatrace, harnessing the robust capabilities of the platform for comprehensive performance monitoring and observability. It’s crucial for users to ensure compliance with version requirements for both Dynatrace and Telegraf, thereby optimizing compatibility and performance when integrating with the Dynatrace ecosystem.

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

Dynatrace

[[outputs.dynatrace]]
  ## For usage with the Dynatrace OneAgent you can omit any configuration,
  ## the only requirement is that the OneAgent is running on the same host.
  ## Only setup environment url and token if you want to monitor a Host without the OneAgent present.
  ##
  ## Your Dynatrace environment URL.
  ## For Dynatrace OneAgent you can leave this empty or set it to "http://127.0.0.1:14499/metrics/ingest" (default)
  ## For Dynatrace SaaS environments the URL scheme is "https://{your-environment-id}.live.dynatrace.com/api/v2/metrics/ingest"
  ## For Dynatrace Managed environments the URL scheme is "https://{your-domain}/e/{your-environment-id}/api/v2/metrics/ingest"
  url = ""

  ## Your Dynatrace API token.
  ## Create an API token within your Dynatrace environment, by navigating to Settings > Integration > Dynatrace API
  ## The API token needs data ingest scope permission. When using OneAgent, no API token is required.
  api_token = ""

  ## Optional prefix for metric names (e.g.: "telegraf")
  prefix = "telegraf"

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## Optional flag for ignoring tls certificate check
  # insecure_skip_verify = false

  ## Connection timeout, defaults to "5s" if not set.
  timeout = "5s"

  ## If you want metrics to be treated and reported as delta counters, add the metric names here
  additional_counters = [ ]

  ## In addition or as an alternative to additional_counters, if you want metrics to be treated and
  ## reported as delta counters using regular expression pattern matching
  additional_counters_patterns = [ ]

  ## 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

  ## Optional dimensions to be added to every metric
  # [outputs.dynatrace.default_dimensions]
  # default_key = "default value"

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.

Dynatrace

  1. Cloud Infrastructure Monitoring: Utilize the Dynatrace plugin to monitor a cloud infrastructure setup, feeding real-time metrics from Telegraf into Dynatrace. This integration provides a holistic view of resource utilization, application performance, and system health, enabling proactive responses to performance issues across various cloud environments.

  2. Custom Application Performance Metrics: Implement custom application-specific metrics by configuring the Dynatrace output plugin to send tailored metrics from Telegraf. By leveraging additional counters and dimension options, development teams can gain insights that are precisely aligned with their application’s operational requirements, allowing for targeted optimization efforts.

  3. Multi-Environment Metrics Management: For organizations running multiple Dynatrace environments (e.g., production, staging, and development), use this plugin to manage metrics for all environments from a single Telegraf instance. With proper configuration of endpoints and API tokens, teams can maintain consistent monitoring practices throughout the SDLC, ensuring that performance anomalies are detected early in the development process.

  4. Automated Alerting Based on Metrics Changes: Integrate the Dynatrace output plugin with an alerting mechanism that triggers notifications when specific metrics exceed defined thresholds. This scenario involves configuring additional counters to monitor crucial application performance indicators, enabling swift remediation actions to maintain service availability and user satisfaction.

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

Related Integrations

HTTP and InfluxDB Integration

The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.

View Integration

Kafka and InfluxDB Integration

This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.

View Integration

Kinesis and InfluxDB Integration

The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.

View Integration