Monitoring and Logging in Azure Kubernetes Service (AKS)

Effective monitoring and logging are crucial for maintaining the health, performance, and security of your Azure Kubernetes Service (AKS) clusters. This section covers essential tools, strategies, and best practices for observing your AKS environment.

Key Monitoring Components

Cluster Metrics

Kubernetes exposes a wealth of metrics about its components and workloads. AKS integrates with Azure Monitor to collect and visualize these metrics.

  • Node Metrics: CPU, memory, disk I/O, and network traffic for each node in your cluster.
  • Pod Metrics: Resource utilization (CPU, memory) for individual pods.
  • Container Metrics: Resource usage at the container level.
  • Kubernetes Control Plane Metrics: API server latency, etcd performance, scheduler queue lengths.

Application Performance Monitoring (APM)

Beyond infrastructure metrics, monitoring the performance of your applications is vital. Tools like Azure Application Insights can provide deep insights into application behavior.

  • Request rates, response times, and failure rates.
  • Dependency tracking across microservices.
  • Exception tracking and analysis.

Logging

Centralized logging allows you to aggregate logs from all your cluster components and applications, making it easier to diagnose issues and perform audits.

  • Container Logs: Standard output and standard error from your application containers.
  • Node Logs: System logs from the operating system and Kubelet on your worker nodes.
  • Control Plane Logs: Logs from the Kubernetes API server, scheduler, controller manager, and etcd.

Azure Services for AKS Monitoring

Azure Monitor

Azure Monitor is the foundational service for collecting, analyzing, and acting on telemetry from your Azure and on-premises environments. For AKS, it provides:

  • Container Insights: A comprehensive solution for collecting, analyzing, and acting on telemetry from your container workloads. It's deployed via a Helm chart and collects metrics and logs from your nodes and pods.
  • Log Analytics Workspaces: The backend data store for Azure Monitor logs. You can query your logs using Kusto Query Language (KQL).
  • Dashboards: Create custom dashboards to visualize key metrics and logs.
  • Alerts: Configure alerts based on metric thresholds or log query results to proactively notify you of potential issues.
Note: Container Insights requires enabling specific diagnostic settings on your AKS cluster to send logs and metrics to a Log Analytics Workspace.

Azure Application Insights

A powerful APM service that helps you monitor the availability, performance, and usage of your web applications. You can instrument your applications running in AKS with the Application Insights SDK.

Azure Policy for Kubernetes

While primarily for governance, Azure Policy can enforce monitoring configurations and audit compliance for your cluster resources.

Implementing Logging Solutions

Cluster-Level Logging Agents

AKS supports deploying logging agents as DaemonSets to collect logs from nodes and pods.

  • Fluentd/Fluent Bit: Popular open-source log collectors that can be configured to send logs to various backends, including Azure Log Analytics. Container Insights typically deploys Fluent Bit.
  • Custom Logging Stack: You can deploy your own logging stack using tools like Elasticsearch, Logstash, and Kibana (ELK) or Grafana Loki if you prefer a self-managed solution.

Example: Forwarding Logs to Log Analytics

When you enable Container Insights, it configures Fluent Bit to collect logs and forward them to your selected Log Analytics workspace. You can also manually configure agents if needed.


# Example of configuring a Fluentd output plugin for Azure Monitor
<match kubernetes.**>
  @type azure_monitor
  log_analytics_workspace_id "YOUR_WORKSPACE_ID"
  log_analytics_shared_key "YOUR_SHARED_KEY"
  resource_id "YOUR_AKS_RESOURCE_ID"
  log_type "ContainerLogs"
  flush_interval 5s
</match>

Key Monitoring Scenarios

Resource Utilization

Monitor CPU, memory, and disk usage across nodes, pods, and containers to identify performance bottlenecks or over-provisioning.

Application Errors and Exceptions

Set up alerts for high error rates or specific exceptions reported by your applications.

Network Latency and Throughput

Monitor network traffic between services and external endpoints to detect connectivity issues.

Pod Restarts and Crash Looping

Investigate why pods are frequently restarting, which often indicates application crashes or misconfigurations.

Security Events

Monitor audit logs for suspicious activities or unauthorized access attempts.

Best Practices

  • Centralize Logs: Use a centralized logging solution like Azure Log Analytics to aggregate logs from all your cluster components.
  • Define Key Metrics: Identify the most important metrics for your applications and cluster infrastructure.
  • Set Up Meaningful Alerts: Configure alerts for critical events and thresholds to enable proactive intervention.
  • Use Dashboards: Create custom dashboards to provide a quick overview of your cluster's health and performance.
  • Regularly Review Logs: Periodically review your logs to identify trends, potential issues, and areas for optimization.
  • Instrument Applications: Use APM tools to gain deep insights into application behavior.
  • Implement Health Checks: Ensure your applications expose health endpoints that Kubernetes can use for readiness and liveness probes.
Tip: Leverage AKS predefined Container Insights dashboards, but don't hesitate to customize them or create new ones tailored to your specific application needs.
Important: Ensure your Log Analytics workspace is configured with sufficient retention periods based on your compliance and operational requirements.