Solution Document for Enabling APM for Azure Kubernetes Services (AKS)

(Datadog APM via Terraform on AKS)

Purpose of the Document

This SOP defines the standardized process for deploying Datadog Application Performance Monitoring (APM) into Azure Kubernetes Service (AKS) using Terraform and Helm. The deployment introduces:

  • Automatic APM instrumentation
  • Request tracing + latency analysis
  • Application dependency analysis
  • Error/exception visibility
  • Platform-driven enablement without code changes

APM deployment is platform-driven and does not require rebuilding or modifying application containers.

Scope

In Scope:

  • Deployment to a single AKS cluster (POC or onboarding)
  • Terraform-based deployment automation
  • Platform-controlled APM enablement

Out of Scope:

  • Distributed business transaction modeling
  • OpenTelemetry pipelines
  • Cost & commercial modeling
  • Multi-cluster federation

Prerequisites

Access Requirements:

  • Azure subscription access
  • AKS RBAC (read/write)
  • Datadog account access

Tooling Requirements:

  • Terraform v1.x
  • Helm provider
  • kubectl (optional)

Networking Requirements:

Outbound access to Datadog ingestion endpoints for:

  • APM
  • Metadata
  • Metrics (optional)

Overview of the Solution

Datadog APM runs via the Datadog Agent deployed on AKS nodes. Workloads send traces to the agent using auto-instrumentation or runtime injection.

Architecture of Logic

Workload → Datadog Agent → APM Ingestion → Analytics → Visualization

Functional Components

Component Role
Datadog Agent Trace ingestion & instrumentation
Cluster Agent Workload metadata aggregation
APM UI Visualization & service mapping
Pipelines Application dependency processing

Repository Reference

Deployment artifacts and Terraform implementation are maintained in the following repository:

https://github.com/airowireNetworks/datadog-apm-azure.git

Clone Repository:

Bash
git clone https://github.com/airowireNetworks/datadog-apm-azure.git
cd datadog-apm-azure

Repository Includes:

  • Terraform deployment modules
  • Helm values configuration
  • tfvars examples
  • APM enablement artifacts

Deployment Procedure

Deployment Environment

Deployment VM configured with:

  • Terraform
  • Azure CLI (optional)
  • kubectl (optional)
  • Helm provider (via Terraform)

Terraform Initialization

Bash
terraform init

Deployment Variables

Example .tfvars:

Terraform
aks_cluster_name   = "cluster name"
aks_resource_group = "resource-group-name"
datadog_api_key    = "xxxxxxxx"
env                = "dev"

Enable APM via Helm Values

Terraform
apm:
  enabled: true

This enables:

  • automatic instrumentation support
  • trace ingestion
  • latency + error visibility

Execution of Deployment

Bash
terraform apply -var-file=cluster1.tfvars

Platform APM Capabilities

Once deployed, the platform supports:

  • Service-level tracing
  • Error monitoring
  • Latency analysis
  • Application dependency mapping
  • Performance insights

Datadog-Side Validation

Validation performed by verifying:

  • Traces visible in APM service catalog
  • Application services discovered
  • Error/latency analysis active
  • Endpoint-level request visibility

Observations & Findings

Key operational findings:

  • APM ingestion successful via IaC
  • No code-level instrumentation required
  • Application visibility improved
  • Error/latency analysis enriched debugging

Optional Enhancements

Recommended enhancements:

  • Distributed tracing correlation
  • OpenTelemetry alignment
  • Multi-cluster hybrid APM
  • Custom span enrichment

Final Outcome

APM successfully integrated into Datadog via Terraform and Helm for AKS, enabling platform-driven service performance visibility with no application code changes.

Contact

For more information about this Document and its contents please contact Airowire Solutions:

Patrick Schmidt — patrick@airowire.com
Piyush Choudhary — piyush@airowire.com
Dr. Shivanand Poojara — shivanand@airowire.com