vnamani details key enhancements in Azure Application Gateway logging, including resource-specific tables, DCR transformations, and the basic log plan, helping teams optimize observability, efficiency, and compliance.

Enhanced Logging for Azure Application Gateway: Resource-Specific Tables, DCR, and Cost Optimization

Introduction

Modern web applications require scalable, secure, and observable architectures. Azure Application Gateway has introduced several logging enhancements to address the increasing need for actionable visibility, cost management, and simplification of monitoring operations. This article, authored by vnamani, breaks down three major capabilities now available:

  • Resource-specific tables
  • Data Collection Rule (DCR) transformations
  • Basic log plan

These features collectively enable teams to achieve deeper insights, better cost management, and adherence to compliance requirements when monitoring Azure Application Gateways.

Resource-Specific Tables: Structured and Efficient Logging

Traditionally, all Application Gateway diagnostic data was consolidated in the AzureDiagnostics table in Log Analytics. This generic approach often resulted in slow queries, increased complexity, and less efficient data management. With the introduction of resource-specific tables, logging in Application Gateway is now more organized:

Key Benefits:

  • Simplified queries with less complex filtering
  • Better schema discovery and log structure
  • Faster ingestion and query execution
  • More granular RBAC via Azure role-based access control

Example: From AzureDiagnostics to Resource-Specific Table Queries

  • Old style: Query needed complex filters for application gateway logs inside AzureDiagnostics.
  • New style: Direct queries to precise tables (e.g., AGWAccessLogs | where ClientIP == "203.0.113.1"), improving maintainability and speed.

Data Collection Rules (DCR) Transformations: Control Your Log Pipeline

DCR transformations let you filter, enrich, or transform log data before it enters your Log Analytics workspace, reducing unnecessary data ingestion and supporting cost and compliance goals.

Why It Matters:

  • Cost Optimization: Only store actionable data, reducing ingestion and storage costs
  • Compliance: Strip out sensitive data (PII) before logs are stored, supporting GDPR/CCPA
  • Volume Management: Focus on deriving value from high-throughput environments by filtering at the source

Real-World Use Cases:

  • E-commerce, healthcare, and development environments tailor log ingestion and retention to operational and regulatory needs

Learn More: Azure Monitor - Data Collection Transformations

Basic Log Plan: Cost-Effective Retention for Low-Priority Data

Not every diagnostic log requires real-time analysis. The Basic log plan in Log Analytics offers economical storage for high-volume, low-priority diagnostic data, ideal for debugging and compliance audits.

When to Use:

  • Save on costs with pay-as-you-go pricing and lower ingestion rates
  • Retain data for periodic troubleshooting and incident forensics

Trade-Offs:

  • No real-time alerts for critical metrics
  • Limited KQL capabilities and potentially higher query costs

Use Basic for logs that don’t require deep analysis or real-time alerting and allocate standard plans for more critical data streams.

Building a Smart Logging Strategy with Azure Application Gateway

To maximize the value of these enhancements:

  • Assess Needs: Determine which logs need real-time monitoring and which are for compliance/debugging
  • Design for Efficiency: Use Basic for low-priority, high-volume logs; reserve premium plans for critical data
  • Transform at Source: Apply DCR for efficient, compliant data ingestion
  • Query with Precision: Leverage resource-specific tables for fast, simple access and analytics

By integrating these capabilities, teams achieve a balance of deep operational visibility, regulatory compliance, and efficient log management in Azure.

References:

Author: vnamani, Azure Networking Blog

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