Azure Monitor and New Relic Integration

Input and output integration overview

Gather metrics from Azure resources using the Azure Monitor API.

This plugin allows the sending of metrics to New Relic Insights using the Metrics API, enabling effective monitoring and analysis of application performance.

Integration details

Azure Monitor

The Azure Monitor Telegraf plugin is specifically designed for gathering metrics from various Azure resources using the Azure Monitor API. Users must provide specific credentials such as client_id, client_secret, tenant_id, and subscription_id to authenticate and gain access to their Azure resources. Additionally, the plugin supports functionality to collect metrics from both individual resources and resource groups or subscriptions, allowing for flexible and scalable metric collection tailored to user needs. This plugin is ideal for organizations leveraging Azure cloud infrastructure, providing crucial insights into resource performance and utilization over time, facilitating proactive management and optimization of cloud resources.

New Relic

This plugin writes metrics to New Relic Insights utilizing the Metrics API, which provides a robust mechanism for sending time series data to the New Relic platform. Users must first obtain an Insights API Key to authenticate and authorize their data submissions. The plugin is designed to facilitate easy integration with New Relic’s monitoring and analytics capabilities, supporting a variety of metric types and allowing for efficient data handling. Core features include the ability to add prefixes to metrics for better identification, customizable timeouts for API requests, and support for proxy settings to enhance connectivity. It is essential for users to configure these options according to their requirements, enabling seamless data flow into New Relic for comprehensive real-time analytics and insights.

Configuration

Azure Monitor

# Gather Azure resources metrics from Azure Monitor API
[[inputs.azure_monitor]]
  # can be found under Overview->Essentials in the Azure portal for your application/service
  subscription_id = "<>"
  # can be obtained by registering an application under Azure Active Directory
  client_id = "<>"
  # can be obtained by registering an application under Azure Active Directory.
  # If not specified Default Azure Credentials chain will be attempted:
  # - Environment credentials (AZURE_*)
  # - Workload Identity in Kubernetes cluster
  # - Managed Identity
  # - Azure CLI auth
  # - Developer Azure CLI auth
  client_secret = "<>"
  # can be found under Azure Active Directory->Properties
  tenant_id = "<>"
  # Define the optional Azure cloud option e.g. AzureChina, AzureGovernment or AzurePublic. The default is AzurePublic.
  # cloud_option = "AzurePublic"

  # resource target #1 to collect metrics from
  [[inputs.azure_monitor.resource_target]]
    # can be found under Overview->Essentials->JSON View in the Azure portal for your application/service
    # must start with 'resourceGroups/...' ('/subscriptions/xxxxxxxx-xxxx-xxxx-xxx-xxxxxxxxxxxx'
    # must be removed from the beginning of Resource ID property value)
    resource_id = "<>"
    # the metric names to collect
    # leave the array empty to use all metrics available to this resource
    metrics = [ "<>", "<>" ]
    # metrics aggregation type value to collect
    # can be 'Total', 'Count', 'Average', 'Minimum', 'Maximum'
    # leave the array empty to collect all aggregation types values for each metric
    aggregations = [ "<>", "<>" ]

  # resource target #2 to collect metrics from
  [[inputs.azure_monitor.resource_target]]
    resource_id = "<>"
    metrics = [ "<>", "<>" ]
    aggregations = [ "<>", "<>" ]

  # resource group target #1 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.resource_group_target]]
    # the resource group name
    resource_group = "<>"

    # defines the resources to collect metrics from
    [[inputs.azure_monitor.resource_group_target.resource]]
      # the resource type
      resource_type = "<>"
      metrics = [ "<>", "<>" ]
      aggregations = [ "<>", "<>" ]

    # defines the resources to collect metrics from
    [[inputs.azure_monitor.resource_group_target.resource]]
      resource_type = "<>"
      metrics = [ "<>", "<>" ]
      aggregations = [ "<>", "<>" ]

  # resource group target #2 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.resource_group_target]]
    resource_group = "<>"

    [[inputs.azure_monitor.resource_group_target.resource]]
      resource_type = "<>"
      metrics = [ "<>", "<>" ]
      aggregations = [ "<>", "<>" ]

  # subscription target #1 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.subscription_target]]
    resource_type = "<>"
    metrics = [ "<>", "<>" ]
    aggregations = [ "<>", "<>" ]

  # subscription target #2 to collect metrics from resources under it with resource type
  [[inputs.azure_monitor.subscription_target]]
    resource_type = "<>"
    metrics = [ "<>", "<>" ]
    aggregations = [ "<>", "<>" ]
</code></pre>

New Relic

[[outputs.newrelic]]
  ## The 'insights_key' parameter requires a NR license key.
  ## New Relic recommends you create one
  ## with a convenient name such as TELEGRAF_INSERT_KEY.
  ## reference: https://docs.newrelic.com/docs/apis/intro-apis/new-relic-api-keys/#ingest-license-key
  # insights_key = "New Relic License Key Here"

  ## Prefix to add to add to metric name for easy identification.
  ## This is very useful if your metric names are ambiguous.
  # metric_prefix = ""

  ## Timeout for writes to the New Relic API.
  # timeout = "15s"

  ## HTTP Proxy override. If unset use values from the standard
  ## proxy environment variables to determine proxy, if any.
  # http_proxy = "http://corporate.proxy:3128"

  ## Metric URL override to enable geographic location endpoints.
  # If not set use values from the standard
  # metric_url = "https://metric-api.newrelic.com/metric/v1"

Input and output integration examples

Azure Monitor

1. Dynamic Resource Monitoring: Use the Azure Monitor plugin to dynamically gather metrics from Azure resources based on specific criteria like tags or resource types. Organizations can automate the process of loading and unloading resource metrics, enabling better performance tracking and optimization based on resource utilization patterns.

2. Multi-Cloud Monitoring Integration: Integrate metrics collected from Azure Monitor with other cloud providers using a centralized monitoring solution. This allows organizations to view and analyze performance data across multiple cloud deployments, providing a holistic overview of resource performance and costs, and streamlining operations.

3. Anomaly Detection and Alerting: Leverage the metrics gathered via the Azure Monitor plugin in conjunction with machine learning algorithms to detect anomalies in resource utilization. By establishing baseline performance metrics and automatically alerting on deviations, organizations can mitigate risks and address performance issues before they escalate.

4. Historical Performance Analysis: Use the collected Azure metrics to conduct historical analysis by feeding the data into a data warehousing solution. This enables organizations to track trends over time, allowing for detailed reporting and decision-making based on historical performance data.

New Relic

1. Application Performance Monitoring: Use the New Relic Telegraf plugin to send application performance metrics from a web service to New Relic Insights. By integrating this plugin, developers can collect data such as response times, error rates, and throughput, enabling teams to monitor application health in real-time and resolve issues quickly before they impact users. This setup promotes proactive management of application performance and user experience.

2. Infrastructure Metrics Aggregation: Leverage this plugin to aggregate and send system-level metrics (CPU usage, memory consumption, etc.) from various servers to New Relic. This helps system administrators maintain an comprehensive view of infrastructure performance, facilitating capacity planning and identifying potential bottlenecks. By centralizing metrics in New Relic, teams can visualize trends over time and make informed decisions regarding resource allocation.

3. Dynamic Metric Naming for Multi-tenant Applications: Implement dynamic prefixing with the metric_prefix option to differentiate between different tenants in a multi-tenant application. By configuring the plugin to include a unique identifier per tenant in the metric names, teams can analyze usage patterns and performance metrics per tenant. This provides valuable insights into tenant behavior, supporting tailored optimizations and enhancing service quality across different customer segments.

4. Real-time Anomaly Detection: Combine the New Relic plugin with alerting mechanisms to trigger notifications based on unusual metric patterns. By sending metrics such as request counts and response times, teams can set thresholds in New Relic that, when breached, will automatically alert responsible parties. This user-driven approach supports immediate responses to potential issues before they escalate into larger incidents.

Feedback

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