Fluentd and Azure Application Insights Integration

Input and output integration overview

The Fluentd Input Plugin gathers metrics from Fluentd’s in_monitor plugin endpoint. It provides insights into various plugin metrics while allowing for custom configurations to reduce series cardinality.

This plugin writes Telegraf metrics to Azure Application Insights, enabling powerful monitoring and diagnostics.

Integration details

Fluentd

This plugin gathers metrics from the Fluentd plugin endpoint provided by the in_monitor plugin. It reads data from the /api/plugin.json resource and allows exclusion of specific plugins based on their type.

Azure Application Insights

The Azure Application Insights plugin integrates Telegraf with Azure’s Application Insights service, facilitating the seamless transmission of metrics from various sources to a centralized monitoring platform. This plugin empowers users to harness the capabilities of Azure Application Insights, a powerful application performance management tool, allowing developers and IT operations teams to gain valuable insights into the performance, availability, and usage of their applications. By employing this plugin, users can monitor application telemetry and operational data efficiently, contributing to better diagnostics and improved application performance.

Key features of this plugin include the ability to specify an instrumentation key for the Application Insights resource, configure the endpoint URL for tracking, and enable additional diagnostic logging for a more comprehensive analysis. Furthermore, the plugin provides context tagging capabilities, allowing the addition of specific Application Insights context tags to enhance the contextual information associated with metrics being sent. These features collectively make the Azure Application Insights Output Plugin a vital tool for organizations looking to optimize their monitoring capabilities within Azure.

Configuration

Fluentd

[[inputs.fluentd]]
  ## This plugin reads information exposed by fluentd (using /api/plugins.json endpoint).
  ##
  ## Endpoint:
  ## - only one URI is allowed
  ## - https is not supported
  endpoint = "http://localhost:24220/api/plugins.json"

  ## Define which plugins have to be excluded (based on "type" field - e.g. monitor_agent)
  exclude = [
    "monitor_agent",
    "dummy",
  ]

Azure Application Insights

[[outputs.application_insights]]
  ## Instrumentation key of the Application Insights resource.
  instrumentation_key = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxx"

  ## Regions that require endpoint modification https://docs.microsoft.com/en-us/azure/azure-monitor/app/custom-endpoints
  # endpoint_url = "https://dc.services.visualstudio.com/v2/track"

  ## Timeout for closing (default: 5s).
  # timeout = "5s"

  ## Enable additional diagnostic logging.
  # enable_diagnostic_logging = false

  ## 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

  ## Context Tag Sources add Application Insights context tags to a tag value.
  ##
  ## For list of allowed context tag keys see:
  ## https://github.com/microsoft/ApplicationInsights-Go/blob/master/appinsights/contracts/contexttagkeys.go
  # [outputs.application_insights.context_tag_sources]
  #   "ai.cloud.role" = "kubernetes_container_name"
  #   "ai.cloud.roleInstance" = "kubernetes_pod_name"

Input and output integration examples

Fluentd

1. Basic Configuration: Set up the Fluentd Input Plugin to gather metrics from your Fluentd instance’s monitoring endpoint, ensuring you are able to track performance and usage statistics.
2. Excluding Plugins: Use the exclude option to ignore specific plugins’ metrics that are not necessary for your monitoring needs, streamlining data collection and focusing on what matters.
3. Custom Plugin ID: Implement the @id parameter in your Fluentd configuration to maintain a consistent plugin_id, which helps avoid issues with high series cardinality during frequent restarts.

Azure Application Insights

1. Application Performance Monitoring: Utilize the Azure Application Insights plugin to continuously monitor the performance of your web applications or microservices. By sending Telegraf metrics directly to Application Insights, teams can visualize real-time application performance data, enabling proactive tuning and optimization of application resources. This setup not only enhances the reliability of applications but also ensures user satisfaction through consistent performance monitoring.

2. Integrated Logging and Telemetry: Combine this plugin with centralized logging solutions to provide a comprehensive observability stack. By sending telecom data to Azure Application Insights, teams can correlate performance metrics with log data and gain deeper insights into application behavior, allowing for more efficient troubleshooting and root cause analysis.

3. Contextual Monitoring of Cloud Resources: Use the context tagging feature to enrich your application metrics with specific contextual information related to your cloud environment. This enhanced context can be invaluable for understanding the performance of cloud-native applications, enabling better scaling decisions and resource management based on real usage patterns.

4. Real-time Alerts Setup: Configure Application Insights to trigger alerts based on specific metrics received via this plugin. This allows teams to be notified of performance degradation or anomalies in real-time, enabling immediate action to mitigate issues and maintain high availability of applications.

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.