BzSpi/fame

Fame - Function for Azure Monitoring Extension

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Fame - Function for Azure Monitoring Extension

This repository hosts an Azure Function App Python code in order to run Log Analytics and Resource Graph queries and send results to Splunk Observability (formerly SignalFx) or Datadog.

Pre-requisites

Variables

  • QUERIES_STORAGE_ACCOUNT_NAME (optional): The name of the Storage Account containing the table with the queries. If not set, use the AzureWebJobsStorage connection string.
  • QUERIES_STORAGE_ACCOUNT_KEY (optional): The key to access the Storage Account containing the table with the queries, will try to fetch it if empty. If not set, use the AzureWebJobsStorage connection string.
  • QUERIES_STORAGE_TABLE_NAME (optional, defaults to LogQueries): The name of the table in the Storage Account with the queries
  • METRICS_EXTRA_DIMENSIONS (optional): Extra dimensions/tags to send along the metrics. Example: env=prod,dd_monitored=true

Metrics Backend Configuration (one backend required)

Splunk Observability Configuration
  • SFX_TOKEN (required for Splunk): The Splunk Observability token for metric sending
  • SFX_REALM (optional, defaults to eu0): Splunk realm (region) to use for metric sending
Datadog Configuration
  • DD_API_KEY (required for Datadog): The Datadog API key for metric sending
  • DD_API_HOST (optional, defaults to https://api.datadoghq.eu): Datadog API host

Other Configuration

  • LOG_ANALYTICS_WORKSPACE_GUID (required): ID of the Log Analytics Workspace for Log Analytics queries
  • SUBSCRIPTION_ID (required): ID of the Subscription for Resource Graph queries
  • LOG_LEVEL (optional, defaults to INFO): Logging level
  • AZURE_CLIENT_ID (optional): Azure Service Principal ID if Service Principal authentication is used
  • AZURE_TENANT_ID (optional): Azure Tenant ID if Service Principal authentication is used
  • AZURE_CLIENT_SECRET (optional): Azure Service Principal secret key if Service Principal authentication is used

How it works

The function runs all the queries stored in the associated Table Storage every minute within the given Log Analytics Workspace and sends the results to either Splunk Observability or Datadog, depending on the configuration.

Each query specifies the value of the metric and its associated time. Every column in the query is sent as metric dimension along with the defined extra dimensions.

Table storage format

The records in the Table Storage must have the following columns:

Log queries requirements

The query must contain the columns metric_value with a metric value and timestamp with the datetime of the metric to send. The others columns must be strings and are treated as dimensions for the metric.

For Log Analytics queries, you must specify a time range in your query to avoid retrieving and sending a huge amount of data.

How to deploy

You can use Zip deployment, Azure Function Core Tools or any other Azure deployment method to deploy this application.

Contributors

BzSpiShr3psjmaprorossifumaxsemantic-release-bot

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