AKS Cost Optimization Guide: How to Reduce Azure Kubernetes Costs in 2025

Azure Kubernetes Service (AKS) makes it easy to run Kubernetes in the cloud—but that convenience can come with hidden costs. Between VM usage, persistent volumes, and add-on services like Container Insights, it’s easy to overspend without realizing where the waste is coming from.

This guide breaks down how AKS pricing works, what drives your costs, and the most effective ways to reduce them. You’ll learn how to right-size workloads, use Spot VMs strategically, automate cost controls, and get real-time visibility into what your workloads actually consume.

Understanding AKS Pricing

AKS gives you a managed control plane and flexibility in how you run workloads—but that flexibility comes with cost complexity. What you pay for depends on how you configure your cluster, which VM types you use, and which add-ons are enabled.

Here’s a simplified breakdown of what contributes to your AKS bill:

Cost Component	What You Pay For
Control Plane	Free for standard clusters. Uptime SLA available as optional add-on.
Node Pools	Billed per VM (vCPU, RAM, disk) using Azure VM pricing (e.g., D-series, B-series).
Spot VMs	Deep discounts (up to 90%) for interruptible workloads—ideal for CI jobs or batch.
Storage	Charged per GB-month. Premium disks cost more.
Network Egress	Intra-VNet is free. Egress to the internet or between regions adds up quickly.
Monitoring + Logs	Azure Monitor, Log Analytics, and Container Insights are billed separately.

AKS pricing also varies based on region and VM type. For up-to-date rates, use the official Azure pricing calculator and AKS pricing guide.

Key AKS Cost Drivers

Knowing what you’re billed for is one thing—understanding why your costs are high is another. Most AKS overspend comes down to a few common issues:

1. Overprovisioned Requests

Many teams set CPU and memory requests far above actual usage. In AKS, this leads to:

Poor binpacking and wasted VM capacity
Unnecessary VM scale-ups (and cost)

2. Underutilized Nodes

AKS doesn’t automatically remove underused nodes unless you configure autoscaling correctly. If workloads don’t fully use a node, you’re still billed for the full VM.

3. Expensive or Mismatched VM SKUs

Choosing general-purpose VMs for memory-heavy apps—or using premium SKUs when cheaper ones would do—adds up fast.

4. Persistent Volume Waste

Leftover PVCs, unused disks, and oversized volumes silently rack up charges. Premium and zone-redundant disks cost even more.

5. Add-On Bloat

Azure Monitor, Log Analytics, and Container Insights are useful—but often left with default retention and sampling settings that generate unnecessary cost.

Understand Your Utilization

Before you can optimize AKS costs, you need visibility into how your workloads actually behave. It’s common to overprovision resources simply because there’s no clear insight into usage trends.

Here are the key metrics to track:

Metric	Why It Matters
CPU & Memory Usage	Helps you right-size requests and avoid overprovisioning.
Node Utilization	Low utilization means wasted VM spend.
Pod Density per Node	Indicates how efficiently pods are packed.
Persistent Volume Usage	Reveals oversized or unused storage volumes.
Network Egress	Unexpected outbound traffic can drive up costs.

Native Azure dashboards give you a high-level view, but don’t always connect usage to cost impact.

To get a clear picture of which teams, namespaces, or workloads are consuming the most—and wasting the most—use DevZero’s Kubernetes cost monitoring tool. It provides real-time visibility into per-pod, per-namespace, and per-team usage, so you can take action before the bill arrives.

Best Practices for AKS Cost Optimization

Once you understand what’s driving your AKS costs, these are the most effective actions to reduce them—without sacrificing performance.

1. Right-Size Your Workloads

Set realistic CPU and memory requests based on actual usage.
Avoid using the same value for requests and limits—it restricts binpacking and inflates cost.
Revisit requests regularly, especially after scaling up teams or traffic.

2. Use Cluster Autoscaler Correctly

Enable autoscaler on each node pool to remove unused nodes automatically.
Ensure workloads aren’t using fixed node affinities or taints that block rescheduling.
Balance between minimum node count (for baseline availability) and autoscale flexibility.

3. Use Spot VMs for Ephemeral Workloads

Ideal for CI/CD pipelines, batch jobs, and stateless microservices.
Add tolerations so Spot-compatible workloads can fall back to on-demand if needed.
Combine with separate node pools for better control.

4. Clean Up Unused Resources

Delete unused PVCs, volumes, and backup snapshots.
Audit LoadBalancers and IPs not tied to active services.
Lower retention on logs and metrics where possible.

5. Match Node Types to Workload Needs

Workload Type	Recommended VM Type
CPU-bound	F-series or D-series VMs
Memory-heavy	E-series VMs
Mixed usage	B-series for dev/test
Ephemeral / batch jobs	Spot VMs with appropriate fallbacks

Choosing the right instance type and packing workloads efficiently can reduce node spend significantly.

Automate AKS Cost Optimization

Manual cost tuning doesn’t scale. To keep costs low as workloads evolve, use automation to maintain efficiency, enforce policies, and detect issues early—without requiring engineers to check every detail.

1. Set Up Budget Alerts

Use Azure Budgets to trigger alerts when spend exceeds thresholds.
Track costs by subscription, resource group, or tags.
Notify teams via email or Action Groups when limits are hit.

2. Automate Labeling and Cost Attribution

Tag resources by team, service, or environment.
Apply labels automatically through policies or CI/CD.
Filter Azure Cost Management reports by label for better visibility.

3. Clean Up with Retention Policies

Set shorter log and metric retention for non-critical workloads.
Exclude noisy namespaces from Azure Monitor.
Tune diagnostic settings to avoid collecting unused data.

Native tools are a good starting point—but they don’t always show how usage maps to spend.

DevZero’s Kubernetes cost optimization tool connects live resource behavior to cost impact, then acts on it automatically. It rightsizes pods in real time, rebalances workloads, and consolidates nodes—no redeploys or manual effort required.

Optimize AKS Costs with DevZero

Even with best practices and native Azure automation in place, inefficiencies still slip through—especially when resource requests drift, workloads shift unpredictably, or nodes sit partially idle.

DevZero adds a dynamic optimization layer that closes the gap between configuration and reality. It continuously analyzes how your AKS workloads behave in production and adjusts resource usage, node placement, and cost efficiency on the fly—without disrupting your workloads.

How DevZero Optimizes AKS Costs in Real Time

1. Live Rightsizing

Automatically adjusts CPU and memory requests as workloads run.
Prevents overprovisioning and complements HPA/VPA without conflict.
No pod restarts or redeploys required.

2. Binpacking Optimization

Consolidates workloads onto fewer nodes by right-sizing and rebalancing in real time.
Frees up unused capacity and reduces VM count.

3. Live Migration

Moves containers between nodes with snapshot + restore mechanisms.
Enables node consolidation or instance replacement without downtime.

4. Spot-Aware Scheduling

Automatically schedules workloads onto Spot VMs where possible.
Ensures safe fallback to on-demand nodes if Spot capacity is unavailable.

5. Instance Type Optimization

Selects optimal VM types based on actual workload shape and usage.
Adapts as traffic patterns and compute needs evolve.

DevZero connects directly to your AKS clusters and starts with an observability-first rollout—so you can see potential savings before enabling automation. Most teams using DevZero see a 40–60% reduction in AKS infrastructure costs.

Get started with DevZero and unlock live cost optimization for your AKS workloads.