AWS vs Azure vs GCP Load Balancers: Which One Costs Less?

Choosing a cloud load balancer based on the lowest advertised hourly price can be misleading.

A load balancer may have a small fixed charge but a higher data-processing cost. Another may charge according to capacity consumed. A third may charge for forwarding rules and processed traffic.

Once traffic reaches hundreds of gigabytes or several terabytes per month, these differences can matter more than the base hourly price.

AWS, Azure, and Google Cloud all offer managed load-balancing services, but they use different pricing models.

So which one costs less?

For a simple, regional Layer 4 workload, Azure can be very cost-effective because of its rule-based pricing and relatively low data-processing rate. AWS can be competitive when an Application Load Balancer’s LCU consumption remains low. Google Cloud can also be attractive, particularly when its global load-balancing architecture fits the application and avoids additional architectural components.

The cheapest option ultimately depends on the workload.

How Cloud Load Balancer Pricing Works

The first mistake is comparing only the hourly charge.

A realistic calculation should consider:

Load balancer cost = base charge + capacity/rule charges + data processing + data transfer + related services

The exact components differ by provider.

Provider	Main pricing model	Major cost drivers
AWS	Hourly + capacity units	ALB/NLB hours, LCUs/NLCUs, data transfer
Azure	Rules + data processed	Rules, processed data, bandwidth
GCP	Forwarding rules + data processing	Forwarding rules, processed traffic, network charges

This difference in pricing models is why a simple “$X per hour” comparison can produce the wrong answer.

AWS Load Balancer Pricing

AWS Elastic Load Balancing includes Application Load Balancer, Network Load Balancer, Gateway Load Balancer, and Classic Load Balancer.

For modern application architectures, the Application Load Balancer and Network Load Balancer are the most relevant options.

AWS charges an hourly amount for the load balancer and then charges according to Load Balancer Capacity Units (LCUs) or Network Load Balancer Capacity Units (NLCUs), depending on the service. Standard AWS data-transfer charges can also apply.

For an Application Load Balancer, LCU usage is calculated across several dimensions, including processed bytes, active connections, new connections, and rule evaluations. AWS bills according to the highest consumption dimension rather than simply adding all four together.

This is important because two applications with the same amount of traffic can have different ALB costs.

Where AWS can become expensive

AWS ALB costs can increase when you have:

• High traffic volume
• Large numbers of new connections
• Many active connections
• Complex routing rules
• Multiple load balancers
• High LCU consumption
• Additional data-transfer charges

AWS also supports LCU reservations for predictable workloads, which can change the economics for applications with stable traffic patterns.

AWS cost optimization

Do not automatically assume that consolidating every application behind one ALB is optimal.

Instead, look at:

• LCU consumption
• Rule evaluations
• Processed bytes
• Connection patterns
• Number of ALBs
• Cross-AZ and internet traffic
• Whether an ALB or NLB is actually required

For high-traffic workloads, processed bytes can become the dominant LCU dimension.

Azure Load Balancer Pricing

Azure Standard Load Balancer uses a different model.

Azure’s pricing is based primarily on load-balancing rules and the amount of data processed. Microsoft states that the first five rules have a bundled hourly price, with additional rules charged separately, while data processed is charged separately for the regional tier.

Current published pricing information shows the first five rules at $0.025/hour and additional rules at $0.01 per rule/hour, with regional data processing at approximately $0.005/GB. Verify the price for your specific region and agreement before using it in a production estimate.

That gives Azure an important advantage for certain workloads.

If you have a relatively simple load-balancing configuration with several rules and predictable traffic, the pricing model can be easier to estimate than a capacity-unit model.

Where Azure can become expensive

The main variable to watch is data processed.

For a high-volume application, even a relatively small per-GB processing charge can become significant.

Azure also charges for outbound bandwidth separately, so the load-balancer processing charge should not be confused with the total networking cost.

Azure cost optimization

Review:

• Number of load-balancing rules
• Data processed
• Internet egress
• Cross-region traffic
• Whether global or regional load balancing is required

Do not compare Azure Load Balancer directly with Azure Application Gateway. They solve different problems.

Azure Load Balancer is primarily a Layer 4 service, while Application Gateway provides Layer 7 capabilities and has a different pricing structure.

GCP Load Balancing Pricing

Google Cloud uses another model.

For many external load-balancing configurations, Google Cloud charges for forwarding rules and data processed by the load balancer. Current pricing shows the first five forwarding rules at $0.025 per hour and additional forwarding rules at $0.01 per hour. For the listed regional external load-balancing configurations, inbound and outbound data processing is currently $0.008 per GiB in regions such as Mumbai.

Google Cloud also distinguishes between global and regional load-balancing architectures.

That distinction matters from a cost perspective.

For example, Google Cloud states that global forwarding rules do not have a separate global data-processing charge, although data processing is charged by the region where traffic is processed.

A regional external Application Load Balancer can also be attractive when an application only needs to operate in one region because it uses the Standard Network Tier.

Where GCP can become expensive

Watch:

• Forwarding rules
• Data processing
• Cross-region traffic
• Internet egress
• Global versus regional architecture
• Additional services such as Cloud Armor and Cloud CDN

Google Cloud notes that Cloud Armor and Cloud CDN can help reduce the impact of outbound data-processing charges for global external Application Load Balancers.

AWS vs Azure vs GCP: Pricing Model

The simplest way to understand the difference is to look at what each provider is actually measuring.

Factor	AWS	Azure	GCP
Base load-balancer charge	Yes	Depends on rules/configuration	Forwarding-rule based
Traffic processing	Through LCU/NLCU model	Per GB	Per GiB for applicable configurations
Rule charges	Part of LCU calculation for ALB	Explicit rule charges	Forwarding rules
Connection usage	Can affect LCUs/NLCUs	Not the primary pricing dimension	Not the primary pricing dimension
Egress	Additional charges can apply	Additional charges can apply	Additional charges can apply
Global architecture	Separate services/configurations	Global and regional options	Strong global LB options
Cost predictability	Moderate	Relatively straightforward for simple workloads	Moderate

The important distinction is this:

AWS is more usage/capacity-oriented.

Azure is more rule-and-data-oriented.

GCP is more forwarding-rule-and-data-processing-oriented.

So Which One Is Cheapest?

There is no universal winner.

But we can identify situations where each provider can have a cost advantage.

Azure can be cheaper for simple regional workloads

If you are running a straightforward Layer 4 application with predictable traffic and a modest number of rules, Azure’s pricing model can be attractive.

Its current regional data-processing rate is lower than the published GCP regional rate, while the rule structure is relatively straightforward.

This can make Azure particularly interesting for workloads where processed traffic is the dominant variable.

AWS can be cheaper when ALB capacity consumption is low

AWS’s model becomes more nuanced because an ALB’s cost depends on the highest LCU consumption dimension.

A relatively low-traffic application with modest connection counts and simple routing can keep LCU usage low.

AWS’s own example shows an ALB using 2.88 LCUs/hour at $0.008 per LCU-hour, producing $0.023/hour of LCU cost before adding the hourly load-balancer charge.

The important point is that you should calculate actual LCU consumption rather than comparing the $0.008 LCU rate directly against a per-GB rate.

GCP can be attractive when global load balancing matters

Cost is not the only consideration.

Google Cloud’s global load-balancing architecture can be valuable when an application serves users across multiple regions.

If achieving the same global architecture on another platform requires additional routing or networking services, the total architecture cost can change significantly.

Google Cloud also provides regional load-balancing options when global distribution is unnecessary.

So GCP should not be judged solely by its per-GiB processing charge.

A Practical Example

Consider a hypothetical application with:

• 1 load balancer
• 5 configured rules
• 1 TB of traffic processed per month
• Regional deployment
• No additional CDN or WAF charges
• No unusual cross-region traffic
• Pay-as-you-go pricing

This is only an illustrative comparison; actual costs depend on region, service type, traffic direction, billing agreement, and other architecture details.

Azure

Using the currently published regional data-processing rate of approximately $0.005/GB:

1,000 GB × $0.005 ≈ $5/month in data processing

The first five rules have a $0.025/hour charge:

$0.025 × 730 hours ≈ $18.25/month

That produces roughly:

$23.25/month

before applicable bandwidth and other networking charges.

GCP

Using the published $0.008/GiB processing rate:

1,024 GiB × $0.008 ≈ $8.19/month

The first five forwarding rules are:

$0.025 × 730 ≈ $18.25/month

That produces approximately:

$26.44/month

before applicable internet egress and other charges.

The example suggests Azure is cheaper than GCP under these particular assumptions.

But that does not mean Azure is always cheaper.

The AWS result cannot be calculated from traffic volume alone because the ALB’s bill depends on LCU consumption across multiple dimensions.

That is precisely why load-balancer comparisons need workload-specific calculations.

Why Traffic Volume Changes the Answer

Suppose the application grows from 1 TB to 50 TB per month.

The data-processing component becomes much more important.

At that point, the difference between:

$0.005/GB

and

$0.008/GiB

can become material.

But AWS does not map directly onto this comparison because its ALB pricing uses LCUs rather than a simple per-GB load-balancer fee.

The AWS bill could be driven primarily by processed bytes, or by another LCU dimension such as connections or rule evaluations.

Therefore, the correct comparison is not:

“Which provider has the lowest GB price?”

It is:

“Which provider produces the lowest total load-balancing cost for this application’s actual traffic and connection profile?”

Don’t Forget Data Transfer Costs

This is where many cloud cost comparisons go wrong.

The load balancer is only one part of the networking bill.

You may also pay for:

• Internet egress
• Cross-region data transfer
• Cross-zone traffic
• NAT gateways
• CDN
• WAF
• Private connectivity
• Inter-cloud data transfer

AWS explicitly notes that standard AWS data-transfer charges can apply in addition to Elastic Load Balancing charges.

Microsoft likewise states that Azure bandwidth charges apply in addition to Standard Load Balancer data-processing charges.

Google Cloud’s load-balancing pricing also needs to be evaluated alongside applicable internet and cross-region network charges.

This means a load balancer that appears cheaper on paper can produce a higher total networking bill if it creates an inefficient traffic path.

The Cheapest Load Balancer Is Often the One You Don’t Overprovision

One of the easiest ways to reduce load-balancing costs is to avoid unnecessary architecture.

Review whether you actually need:

• Multiple load balancers
• Global load balancing
• Cross-region distribution
• Complex routing
• Dedicated WAF infrastructure
• CDN for uncached content
• Multiple redundant networking layers

However, cost optimization should never mean removing a component that provides a genuine availability or security requirement.

The goal is to remove unnecessary complexity, not necessary resilience.

How to Reduce Load Balancer Costs on AWS

Start with your LCU/NLCU usage.

Look for:

• High processed-byte consumption
• Excessive rule evaluations
• High new-connection rates
• High active-connection counts
• Unnecessary load balancers
• Inefficient traffic routing

For predictable AWS workloads, evaluate whether LCU reservation makes economic sense.

Also review whether traffic should be served through CloudFront or another edge service before reaching the load balancer.

How to Reduce Load Balancer Costs on Azure

Focus on:

• Rule count
• Data processed
• Internet egress
• Cross-region traffic
• Unused load-balancing rules

If five or fewer rules are sufficient, avoid unnecessarily increasing the rule count.

For high-volume applications, investigate whether a CDN or edge architecture can reduce the amount of traffic that needs to reach the origin infrastructure.

How to Reduce Load Balancer Costs on GCP

Focus on:

• Forwarding rules
• Data-processing volume
• Global versus regional configuration
• Cross-region traffic
• Internet egress
• Cloud CDN usage

If the application is regional, don’t automatically deploy a global architecture.

Google Cloud specifically positions the regional external Application Load Balancer as a cost-effective option for applications that can operate in a single region.

A Better Way to Compare AWS, Azure, and GCP

Before choosing a provider, collect these numbers:

Monthly traffic: How many GB/TB pass through the load balancer?

New connections: How many connections are created per second?

Active connections: How many connections remain open?

Rules: How complex is the routing configuration?

Regions: Is the application regional or global?

Egress: How much traffic leaves the cloud?

Availability: How many zones or regions are required?

Security: Do you need WAF, DDoS protection, or edge security?

Architecture: Are you using CDN, NAT, service mesh, or other networking components?

Then calculate the complete monthly networking cost.

Final Verdict

If you are comparing only the basic load-balancer component, Azure can be highly cost-effective for straightforward regional Layer 4 workloads, particularly when processed traffic is significant.

AWS can be competitive for applications whose ALB/NLB capacity usage remains low or whose architecture benefits from AWS’s native integration and usage model.

GCP can be compelling when global load balancing, regional architecture, or integration with Google’s broader networking stack provides architectural advantages that outweigh a simple per-GB comparison.

So the answer to “AWS vs Azure vs GCP Load Balancers: Which one costs less?” is:

Azure often has the simpler cost advantage for straightforward regional workloads. AWS can win for specific low-to-moderate LCU workloads. GCP can win when its global or regional architecture reduces the need for additional networking components.

The correct choice should therefore be based on total networking cost, not the load balancer’s advertised unit price.

For a production decision, run the same traffic profile through each provider’s pricing calculator using the same region, throughput, connection pattern, availability requirements, and supporting services. That produces a meaningful comparison instead of a misleading price-per-hour table.