Cloud Powerhouses 
Compared: 10 Crucial 
AWS EC2 vs Azure VM 
Considerations

TABLE OF CONTENTS

Comparing AWS EC2 vs Azure VM: 10 Instances General Purpose Instances Compute Optimized Instances Memory Optimized Instances Storage Optimized Instances GPU (Graphics Processing Unit) Instances FPGA (Field Programmable Gate Array) Instances Bare Metal Instances High Performance Instances Burstable Performance Instances Specialized Instances

Pricing Comparison: AWS EC2 vs. Azure VM

Leveraging AWS EC2 and Azure VM with Cloud4C

Frequently Asked Questions (FAQs)

 

In the current cloud space, Amazon Web Services (AWS) and Microsoft Azure stand as titans, collectively commanding over 50% of the global cloud market share. At the heart of their offerings lie two fundamental services: AWS EC2 (Elastic Compute Cloud) and Azure Virtual Machines (VMs). These services form the backbone of countless applications and workloads worldwide, powering everything from small startups to Fortune 500 enterprises.

As businesses increasingly migrate to the cloud, understanding the nuances between AWS EC2 and Azure VM instances becomes crucial. This comprehensive blog delves into various instance types, pricing models, use cases of both AWS's EC2 and Microsoft Azure's VM platforms, and more. Let us dive in.

Comparing AWS EC2 vs Azure VM: Breaking Down the 10 Major Instance Types

1. General Purpose Instances: The Versatile Workhorses

AWS EC2:

Types: T3, M5, M6g

• T instances: Burstable performance for workloads with variable CPU usage
• M instances: Balanced compute, memory, and network resources
• Key features: Balanced compute, memory, and network resources
• Use case: Web servers, small databases, development environments

Azure VM:

Types: B-series, Av2-series, D-series

• B-series: Economical burstable instances for workloads with intermittent CPU usage
• D-series: General purpose VMs with balanced CPU-to-memory ratio
• Use case: Testing and development, small to medium databases, low-traffic web servers

Comparison: Both AWS EC2 and Azure VM offer versatile general-purpose instances suitable for a wide range of applications. AWS EC2's T3 instances provide burstable performance, similar to Azure's B-series VMs. However, AWS cloud has an edge with its Graviton2-based M6g instances, offering better price-performance for ARM-based workloads.

2. Compute Optimized Instances: High-Performance Processing

AWS EC2:

Types: C5, C6g

• C instances: High-performance computing with the highest ratio of CPU to memory
• Key features: High CPU-to-memory ratio, enhanced networking capabilities
• Use case: High-performance web servers, scientific modeling, batch processing

Azure VM:

Types: F-series, Fsv2-series

• F-series: Compute optimized VMs with a high CPU-to-memory ratio
• Key features: High CPU-to-memory ratio, support for premium storage
• Use case: Gaming servers, media transcoding, high-performance computing

Comparison: When it comes to compute-intensive workloads, both platforms offer specialized instances. AWS EC2 C instances and Azure VM F-series are designed for applications that require high processing power, such as batch processing, scientific modeling, and gaming servers. The AWS EC2 network performance of these instances are typically higher than general purpose options, making them suitable for compute-intensive tasks with high network demands.

3. Memory Optimized Instances: Handling Data-Intensive Workloads

AWS EC2:

Types: R5, R6g, X1, High Memory

• R instances: Designed for memory-intensive applications
• X instances: Optimized for large-scale, enterprise-class, in-memory applications
• Key features: Large memory-to-CPU ratio, support for SAP HANA workloads
• Use case: High-performance databases, distributed cache, in-memory analytics

Azure VM:

Types: Ev3, Esv3, M-series

• E-series: Memory optimized VMs for high-memory applications
• M-series: Large memory VMs for demanding workloads
• Key features: High memory-to-CPU ratio, support for SAP HANA
• Use case: Relational database servers, medium to large caches, in-memory analytics

Comparison: Both providers offer robust memory-optimized instances. AWS has an advantage with its X1 and High Memory instances, providing up to 24 TB of memory for massive in-memory databases. Azure's M-series VMs are catching up, offering up to 11.4 TB of memory.

4. Storage Optimized Instances: Dealing with Data at Scale

AWS EC2:

Types: I3, D2, H1

• I instances: High I/O performance for NoSQL databases and data warehousing
• D instances: Designed for high throughput of sequential read and write access
• Key features: High I/O performance, large instance storage volumes
• Use case: NoSQL databases, data warehousing, distributed file systems

Azure VM:

Types: Ls-series, Lsv2-series

• Ls-series: Storage optimized VMs for high disk throughput and IO
• Lsv2-series: Improved version of Ls-series with higher performance
• Key features: High disk throughput and IOPS, support for Ultra Disk Storage
• Use case: Big Data applications, SQL and NoSQL databases, data warehousing

Comparison: When it comes to storage-intensive workloads, both platforms offer specialized instances. Both are optimized for applications that require high, sequential read and write access to large data sets, such as big data processing, relational and NoSQL databases, and data warehousing solutions.

5. GPU Instances: Improving AI and Graphics Workloads

AWS EC2:

Types: P3, P4, G4

• P instances: General-purpose GPU computing
• G instances: Graphics-intensive applications and CUDA computing
• Key features: NVIDIA Tesla GPUs, high GPU-to-CPU ratio
• Use case: Machine learning, high-performance computing, 3D visualization

Azure VM:

Types: NCv3, NDv2, NVv3

• N-series: GPU-enabled VMs for visualization and deep learning
• NV-series: Optimized for remote visualization, streaming, and VDI
• Key features: NVIDIA Tesla GPUs, support for NVIDIA GPU Cloud
• Use case: AI training and inference, scientific simulations, remote visualization

Comparison: Both AWS EC2 and Azure VM provide GPU-enabled instances for graphics-intensive and machine learning workloads. AWS has a slight edge with its P4 instances featuring NVIDIA A100 Tensor Core GPUs, which are optimized for machine learning workloads. However, Azure's NDv2-series provides excellent performance for distributed AI training tasks.

6. FPGA (Field Programmable Gate Array) Instances: Custom Acceleration for Specialized Workloads

AWS EC2:

• F1 instances: Customizable FPGAs for hardware acceleration
• Key features: Xilinx UltraScale+ VU9P FPGAs, hardware acceleration
• Use case: Genomics research, financial analytics, real-time video processing

Azure VM:

• Currently, Azure does not offer FPGA-specific VM types

7. Bare Metal Instances: Cloud Power with Direct Hardware Access

AWS EC2:

Types: i3.metal, c5.metal, r5.metal, etc.

• Key features: Direct access to hardware, no virtualization overhead
• Use case: Performance-sensitive applications, applications requiring specific hypervisors

Azure VM:

Types: Azure Dedicated Host

• Ev3-series, Esv3-series (in preview)
• Key features: Physical servers dedicated to one Azure subscription
• Use case: Compliance requirements, licensing considerations, legacy applications

Comparison: Both platforms offer bare metal instances, allowing applications to run directly on the server hardware without virtualization overheads. These instances are ideal for workloads that require access to physical hardware or for applications that are not compatible with virtualized environments.

8. High Performance Instances: Pushing the Boundaries of Cloud

AWS EC2:

Types: Z1d, X1e

• Key features: High frequency Intel Xeon processors, large memory capacity
• Use case: Electronic Design Automation, financial modeling, real-time analytics

Azure VM:

Types: HB-series, HC-series

• Key features: AMD EPYC processors, high core count, InfiniBand networking
• Use case: Molecular dynamics simulations, weather forecasting, computational fluid dynamics

Comparison: AWS EC2's Z1d instances excel in scenarios requiring high per-core performance, while Azure's HB and HC-series VMs are optimized for HPC applications that can leverage high core counts and fast interconnects.

9. Burstable Performance Instances: Cost-Effective Solutions for Variable Workloads

AWS EC2:

Types: T3, T3a

• Key features: Baseline performance with ability to burst, CPU credits
• Use case: Dev/test environments, small databases, microservices

Azure VM:

Types: B-series

• Key features: Economical burstable VMs, ideal for workloads with variable usage patterns
• Use case: Low-traffic web servers, small databases, development and testing

Comparison: Both AWS EC2 and Azure VM offer burstable instances that provide cloud cost optimization solutions for workloads with variable performance needs. The pricing models are similar, with both charging for baseline performance and allowing bursting through a credit system.

10. Specialized Instances: Tailored Solutions for Unique Workloads

AWS EC2:

Types: Inf1 (Inferentia chips for machine learning inference), Mac (for iOS/macOS development)

• Key features: Purpose-built hardware for specific use cases
• Use case: Cost-effective Machine Learning inference

Azure VM:

Types: NV-series (visualization and remote desktop), H-series (High Performance Computing)

• Key features: Specialized hardware for specific workloads
• Use case: Graphics-intensive remote applications, clustered HPC applications

Comparison: AWS has an edge with its custom-designed Inferentia chips for machine learning inference, while Azure offers strong options for remote visualization and HPC workloads.

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Pricing Comparison: AWS EC2 vs. Azure VM

When it comes to AWS EC2 vs Azure VM pricing, both platforms offer a variety of pricing models:

• On-demand pricing: Pay for compute capacity by the hour or second
• Reserved Instances: Discounted rates for committing to a specific instance type for 1 or 3 years
• Spot Instances (AWS) / Low-priority VMs (Azure): Significantly discounted rates for interruptible workloads

The actual costs can vary significantly based on the specific instance type, region, and usage patterns. Generally, AWS EC2 tends to offer more granular pricing options, while Azure VM pricing is often bundled with other services, which can be advantageous for organizations heavily invested in the Microsoft ecosystem.

Leveraging AWS EC2 and Azure VM with Cloud4C

Both AWS EC2 and Azure VM offer a rich array of instance types and configurations to suit diverse computing needs. The choice between AWS EC2 vs. Azure VM ultimately depends on your specific requirements, existing infrastructure, budget constraints, and long-term cloud strategy.

Cloud4C offers a diverse range of AWS cloud and Azure cloud solutions tailored to meet the specific needs of enterprises across various industries. Our expertise in AWS EC2 and Azure VM services as Azure Expert MSP and AWS MSP allows organizations to leverage the full capabilities of these platforms, ensuring optimal performance and cost-effectiveness. With a focus on automation, security, and compliance, our certified cloud engineers work closely with your teams to design, implement, and manage cloud architectures that align with your business goals.

Our comprehensive suite of services includes cloud migration, infrastructure management, and disaster recovery solutions, and FinOps, all designed to maximize the benefits of AWS and Azure. Our commitment to continuous monitoring and optimization ensures that your cloud environment remains agile and responsive to changing business demands

Partner with Cloud4C to utilize the full potential of AWS EC2, Azure VM, and the entire spectrum of cloud services. Contact us to learn how.

 

Frequently Asked Questions: