5 Hidden AWS Cost Drivers Malaysian Companies Overlook (And How to Manage Them)

Cloud adoption for many Malaysian companies has matured. 

What hasn’t matured at the same pace is cloud cost management. 

With 78% of companies report 21-50% of cloud expenditure wasted annually. 

These costs don’t appear fully on dashboards. They’re hidden in the setup. 

In unreviewed architectural and governance blind spots.

In this article, we will reveal the hidden AWS costs that most companies in Malaysia overlook and how AWS managed services can help control and reduce them.

1. Hidden data flow expenses

Compute and storage—these are what most teams budget for. 

But in high-traffic environments, data movement is actually the real cost driver in your network architecture.

Particularly for e-commerce platforms, SaaS providers, and mobile apps with traffic growth, expenses can appear in:

• Internet traffic handling fees (billed per GB processed)
• Cross data center traffic fees
• Data leaving AWS fees
• Cross-region data copying fees

The more traffic is unnecessarily routed through intermediaries, the higher the processing fees.

2. Overbuilt cloud setup

Cloud promises elasticity for systems that require shifting workloads and fluctuating demands.

However, this is only valuable when actively governed. 

Across Malaysian AWS environments, we frequently observe:

• Servers at 10-20% utilization sitting idle
• Databases built for maximum traffic all the time
• IOPS storage set to the highest performance, even if not needed
• Test environments operating 24/7
• Old unused storage and forgotten backups accumulating

Naturally, engineering teams tend to optimize systems for uptime. 

But for cloud, setting systems up at their max based on hypothetical capacity will cost companies more than they actually use.

3. Design issues from rapid scaling

Generally, many Malaysian companies adopted AWS using “lift-and-shift” strategies to avoid lengthy, complex re-architecting processes during modernization. 

While effective for speed, the method often preserves legacy data centre design patterns.

These patterns cannot adapt to AWS’s evolving pricing models and environment.

And several issues emerge: 

• Apps that cannot scale down when traffic is low
• Outdated servers that cost more but have less performance
• Charged extra fees to keep old databases running
• Monitoring and logging costs as much as the infrastructure

An architecture designed for a data centre behaves differently in the cloud. 

If a “lift-and-shift” environment isn’t optimized after migration, it will become financially inefficient over time.

4. Governance gaps

AWS cannot be operated with a “set and forget” mindset.

Cloud spend is elastic and uncapped by default. Without governance, cost control becomes reactive rather than strategic. 

Every resource launched has to have clear tagging standards and ownership policies. 

Common governance gaps include:

• Lack of tagging and cost allocation standards
• Absence of budget thresholds and anomaly detection
• No clear ownership of cloud expenditure
• Limited alignment between engineering and finance reporting

Every resource launched has to have clear tagging standards and ownership policies. Without it, finance teams risk 

• Unclear cost attribution
• Disappearing project-level visibility

A single misconfiguration or unexpected traffic surge can consume a month’s budget in hours.

5. Serverless and microservices cost creeps

Serverless and microservices can deliver exceptional cost efficiency as companies only pay when the code runs. 

However, they introduce nuanced cost behaviours:

• Startup time when a serverless function has been inactive 
• Keeping serverless running to avoid slow startup delays
• Overcommunication between small services in the architecture

If not designed intentionally, companies would end up: 

• Paying extra for startup time
• Paying a “pay only when used” server similarly or even more to a server running 24/7 
• Paying for the accumulated API fees and extra coordination costs 

At scale, cumulative effects can exceed the cost of a well-architected container-based platform.