ARM vs X86: Cloud Performance Showdown in 2024

• 15/12/2024
• 5-minute read

ARM vs x86: The Cloud Architecture Battle

The choice between ARM and x86 processors has become increasingly relevant for cloud computing workloads. As organizations continue to migrate applications to the cloud and optimize for cost-efficiency, understanding the architectural differences between these processor families can lead to significant performance gains and cost savings. Let’s dive into this technical comparison and examine how major cloud providers are reshaping their offerings around these architectures.

Architectural Foundations: Understanding the Difference

The fundamental difference between ARM and x86 lies in their instruction set architectures (ISAs).

x86 Architecture:

• Complex Instruction Set Computing (CISC) design
• Originated from Intel’s processors in the 1970s
• Dominates desktop, laptop, and traditional server markets
• Optimized for single-threaded performance
• Higher power consumption

ARM Architecture:

• Reduced Instruction Set Computing (RISC) design
• Originally developed for mobile and embedded systems
• Focus on power efficiency
• Simpler instruction set requiring fewer transistors
• Typically lower cost to manufacture

These fundamental differences have created distinct performance profiles that are now being leveraged strategically in cloud computing environments.

Real-World Performance: Benchmarks Tell the Story

Recent benchmark tests provide fascinating insights into the real-world performance gap between ARM and x86 processors in cloud environments.

According to benchmarks from Tsypuk’s blog comparing AWS Fargate performance, ARM-based instances showed impressive results:

• CPU-intensive workloads: ARM processors demonstrated 15-20% better performance for mathematical computations and data processing tasks
• Memory operations: ARM showed approximately 10% improvement in memory-intensive applications
• Cost-efficiency: ARM instances delivered up to 40% better performance-per-dollar compared to equivalent x86 instances

However, x86 still maintained advantages in certain scenarios:

• Applications heavily optimized for x86 instruction sets
• Workloads using specific x86 extensions (AVX, SSE)
• Legacy software without ARM-compatible versions

Cloud Providers Embracing ARM: AWS Graviton Leading the Charge

Amazon Web Services has made the most significant push toward ARM architecture with its custom-designed Graviton processors.

AWS Graviton Processors

AWS Graviton processors, now in their third generation, represent Amazon’s commitment to ARM architecture. According to AWS documentation, Graviton3 processors offer:

• Up to 40% better price-performance over comparable x86-based instances
• 2x faster floating-point performance
• 3x better performance for CPU-based machine learning workloads
• 50% more memory bandwidth

This performance advantage becomes particularly significant when operating at scale. Consider this practical example:

# Example: Monthly cost comparison for a web application cluster
# x86-based (m6i.xlarge): 20 instances × $0.192/hr × 730 hours = $2,803.20
# ARM-based (m7g.xlarge): 20 instances × $0.154/hr × 730 hours = $2,248.40
# Monthly savings: $554.80 (approximately 20%)

For organizations running hundreds or thousands of instances, these savings quickly compound into substantial operational cost reductions.

Google Cloud’s ARM Approach

Google Cloud has also entered the ARM space, though with a different strategy than AWS. Rather than developing custom silicon, Google Cloud offers Tau T2A machines based on Ampere Altra processors. These instances provide:

• Up to 32 ARM cores per VM
• Competitive pricing compared to x86 instances
• Strong performance for scale-out workloads
• Integration with standard Google Cloud services

Early adopters have reported that T2A instances perform particularly well for containerized microservices and web serving workloads where parallel processing capabilities are beneficial.

Migration Considerations: Is ARM Right for Your Workload?

While the performance and cost benefits of ARM are compelling, organizations should consider several factors before migrating:

1. Application compatibility: Not all software is optimized for ARM. Custom applications may require recompilation or code modifications.

2. Dependency ecosystem: Some third-party libraries or dependencies might not have ARM versions available.

3. Performance profile: Workloads that benefit from x86’s stronger single-thread performance might not see the same advantages on ARM.

4. Testing requirements: Thorough testing is essential to ensure application behavior remains consistent after migration.

Let’s look at a simplified decision framework:

Real-World Migration Example

A medium-sized SaaS company recently migrated their API layer from x86 instances to ARM-based AWS Graviton3 instances. Their migration process provides valuable insights:

1. They began by creating a parallel ARM-based environment for testing
2. They identified and addressed compatibility issues in their dependency chain
3. They recompiled custom components with ARM targets
4. They implemented a blue-green deployment to gradually shift traffic
5. They monitored performance and costs continuously during the transition

The results were impressive:

• 28% reduction in infrastructure costs
• 15% improvement in average response times
• 22% lower CPU utilization across the cluster

Conclusion: The Future is Heterogeneous

The cloud computing landscape is evolving toward a heterogeneous future where both ARM and x86 architectures coexist, each serving the workloads they’re best suited for. As major cloud providers continue investing in ARM technology, we can expect further performance improvements and broader software compatibility.

For organizations looking to optimize their cloud spending and performance, evaluating ARM-based instances represents a significant opportunity. The key is conducting thorough testing with your specific workloads and implementing a methodical migration strategy.

As the benchmark data clearly shows, ARM’s ascendancy in cloud computing is not merely a temporary trend but a fundamental shift in the infrastructure landscape that will continue to reshape how we architect and deploy cloud applications.

Further Reading

• AWS Graviton Fast Start Guide
• Arm’s Cloud Computing Solutions
• Google Cloud’s ARM-based Tau T2A instances
• AnandTech’s Ampere Altra Technical Review