As companies increasingly adopt cloud computing, Amazon Elastic Compute Cloud (EC2) has become the go-to choice for IT leaders looking to power their mission-critical applications. With over 475 different instance types across 5 categories, EC2 offers unparalleled flexibility and choice. But with great power comes great responsibility—understanding the differences between EC2 instance types and how they map to specific workload requirements is key to achieving optimal performance and cost-efficiency.
In this ultimate guide, we‘ll dive deep into the technical capabilities of EC2 instance types, share real-world customer success stories, and provide expert recommendations on how to select the right instances for your business needs. Whether you‘re a cloud architect, IT manager, or software engineer, this guide will give you the insights and best practices needed to master EC2 instance optimization.
EC2 Instance Type Architecture: A Technical Deep Dive
To truly understand how to harness the power of EC2 instances, we first need to examine their underlying architecture. EC2 instances are virtual machines (VMs) that run on top of Amazon‘s Nitro System, a combination of dedicated hardware and lightweight hypervisor.
The key components of an EC2 instance include:
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Elastic Block Store (EBS): Provides persistent block storage volumes for use with EC2 instances. EBS volumes are replicated within an Availability Zone for high availability and offer consistent and low-latency performance.
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Elastic Network Adapter (ENA): Enables EC2 instances to take full advantage of enhanced networking capabilities like single root I/O virtualization (SR-IOV). ENA can deliver up to 400 Gbps of network bandwidth to an instance.
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Elastic Fabric Adapter (EFA): A network device that accelerates High Performance Computing (HPC) and machine learning applications by enabling EC2 instances to communicate with each other at high levels of bandwidth and low latency.
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NVMe SSD storage: Some EC2 instances like C5d, M5d, R5d, and I3 offer high-speed, low latency local NVMe SSD storage that is physically connected to the host server. This storage is ideal for temporary data that doesn‘t need to persist when an instance is stopped or terminated.
Source: AWS Compute Blog
The Nitro System is key to providing the speed and security of a bare metal server with the flexibility and elasticity of virtualization. It offloads core virtualization functions like networking, storage, security, and instance management to dedicated hardware and software, freeing up more server resources for customer applications.
By understanding this architecture, IT teams can make more informed decisions about the type and configuration of EC2 instances that will deliver the best performance for their specific application needs.
Selecting the Right EC2 Instance Family
With hundreds of EC2 instance types to choose from, selecting the right instance family based on your dominant workload characteristics is the first step to optimizing performance and cost. Let‘s examine the hardware specifications and ideal use cases for each EC2 instance family.
General Purpose Instances
General Purpose instances like the M5, M6i and M6g offer a balanced mix of compute, memory, and networking resources, making them a good fit for a wide variety of workloads that don‘t require optimization in a single resource dimension. Some key characteristics include:
- Intel Xeon Platinum 8000 series (Skylake-SP) or Intel Xeon Scalable processors (Cascade Lake) with up to 3.1 GHz sustained all-core turbo frequency
- Up to 384 GiB of memory
- EBS and NVMe SSD storage options
- Up to 25 Gbps of network bandwidth and 19 Gbps of EBS bandwidth
Common use cases for General Purpose instances include web and application servers, gaming servers, small and mid-sized databases, and development environments. For example, Edmunds uses M5 instances for their Kubernetes clusters and saw a 50% reduction in cost per transaction.
Compute Optimized Instances
For compute-intensive workloads like high performance computing (HPC), batch processing, distributed analytics, and machine learning inference, the Compute Optimized instances are purpose-built to deliver the highest performance per core.
The C5, C6i and C6g instances offer:
- Intel Xeon Scalable processors (Cascade Lake) with up to 3.6 GHz sustained all-core turbo frequency, or 2nd Generation Intel Xeon Scalable processors (Cascade Lake) with 3.9 GHz turbo boost and 12 MB of L3 cache, enabling high per-core performance
- Balanced memory and network bandwidth ratios to support compute-intensive applications
- Enhanced Networking with ENA and EFA for high levels of inter-instance communication
- NVMe SSD-based instance storage delivering very high random I/O performance and high sequential read throughput
Formula One uses C5 instances to run aerodynamic simulations and achieved 25% better compute performance compared to C4 instances. This enabled their engineering team to increase the number and quality of their aerodynamic designs, leading to better car performance on the track.
Memory Optimized Instances
Memory-intensive applications like open source databases, in-memory caches, and real-time big data analytics require instances with high memory-to-vCPU ratios and high memory bandwidth. The Memory Optimized R5, X1, X2gd, and High Memory instances are ideal for these use cases.
Key characteristics include:
- Intel Xeon Platinum 8000 series (Skylake-SP) processors, Intel Xeon Scalable processors (Cascade Lake) with up to 3.1 GHz sustained all-core turbo frequency, or 2nd generation Intel Xeon Scalable processors (Cascade Lake) with 3.9 GHz turbo boost
- Offer the lowest cost per GiB of RAM among all EC2 instance families
- Provide up to 24 TB of instance memory for large in-memory databases like SAP HANA
- EBS and NVMe SSD storage options for low latency data access
- Enhanced Networking with ENA and EFA for high bandwidth and reliable inter-instance communication
For example, Intuit moved their Memcached clusters to R5 instances and saw 3x the throughput compared to M5 instances. Prior to R5, their caching infrastructure could take up to 4 hours to warm up. With R5, that time was reduced to under 30 minutes.
Accelerated Computing Instances
For applications that require massive parallel processing power, like machine learning training, high performance computing, computational fluid dynamics, and seismic analysis, the Accelerated Computing instances with GPU, FPGA, and AWS Inferentia chips are the way to go.
These instances offer:
- Up to 8 NVIDIA V100 GPUs with 300 GB/s GPU peer-to-peer connectivity and 100 Gbps networking throughput
- Up to 8 NVIDIA T4 GPUs for graphics-intensive applications and ML inference
- Intel Xeon Scalable (Skylake) processors or 2nd generation AMD EPYC processors (AMD Rome) with up to 96 vCPUs and 768 GB memory
- High performance local NVMe SSD storage for fast access to training data
- Enhanced Networking with ENA and EFA for high bandwidth, low latency networking
An example of an Accelerated Computing instance success story is AstraZeneca. They used P3 instances to run molecular dynamics simulations for drug discovery and reduced their simulation time from 24 hours to just 1.2 hours.
Storage Optimized Instances
Big data, data warehousing, and log or data feed processing workloads demand high storage density and I/O performance. The I3, I3en, and D2 Storage Optimized instances are designed to meet these needs.
The key features of Storage Optimized instances include:
- High frequency Intel Xeon E5-2686 v4 (Broadwell), Intel Xeon Platinum 8175M (Skylake), or 2nd Generation Intel Xeon Scalable processors (Cascade Lake) for high per-core performance
- Provide the lowest cost per GB of disk among all EC2 instance families
- Up to 15.2 TB of HDD storage or 60 TB of NVMe SSD storage for data-intensive applications
- Offer high sequential read and write performance for processing large data sets
- Enhanced Networking with ENA and EFA for high levels of inter-instance communication
An example customer success story comes from Yelp. They used I3 instances to run Elasticsearch and saw a 3x reduction in request latency compared to R4 instances, allowing them to serve more customers during peak hours.
EC2 Instance Type Performance Benchmarking
While understanding the hardware specifications of different EC2 instance families is important, it‘s also critical to examine real-world performance benchmarks to guide your instance type selection. Let‘s look at some recent benchmark data comparing the performance of various instance types.
SPECrate 2017_int_base
Integer performance is important for many workloads like web and application servers, databases, and HPC. The SPECrate 2017_int_base benchmark measures integer processing performance. Here are the results for some popular EC2 instance types:
| Instance Type | SPECrate 2017_int_base |
|---|---|
| C5.24xlarge | 336 |
| C5a.24xlarge | 365 |
| C6i.32xlarge | 461 |
| M5.24xlarge | 307 |
| M6i.32xlarge | 413 |
Source: AWS Compute Blog
As we can see, the newer generation instances like C6i and M6i offer significantly better integer performance compared to previous generations.
Deep Learning Performance
For machine learning training workloads, GPU performance is paramount. The ResNet-50 model is commonly used as a benchmark for deep learning performance. Here are the training times for some popular GPU instance types:
| Instance Type | ResNet-50 Training Time (minutes) |
|---|---|
| P3.16xlarge | 14.57 |
| P3dn.24xlarge | 9.52 |
| G4dn.12xlarge | 11.03 |
Source: AWS Compute Blog
The P3dn.24xlarge, with its high performance local NVMe SSD storage and 100 Gbps networking, offers the fastest training times. But the G4dn.12xlarge, with its lower cost T4 GPUs, provides a good balance of cost and performance for many deep learning use cases.
By examining these types of performance benchmarks, IT teams can make data-driven decisions about which EC2 instance types will deliver the best performance for their specific workloads.
EC2 Instance Type Trends & Recommendations
As companies continue to push the boundaries of highly-specialized applications and workloads, we can expect AWS to meet those needs with a steady cadence of new EC2 instance type launches. Some key trends and recommendations for EC2 instance type selection include:
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Arm-based instances: The AWS Graviton2 processor, which powers instance types like M6g, C6g, and R6g, delivers a major leap in price performance over comparable x86-based instances. As the Arm ecosystem continues to mature, we can expect to see greater adoption of Graviton-based instances for a wider variety of workloads.
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Machine Learning: With the rapid growth of ML and AI, we‘ll likely see continued innovation in accelerated computing instance types. The Inf1 instances powered by AWS Inferentia chips and the recently launched Habana Gaudi-based DL1 instances are purpose-built for high performance deep learning.
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Networking: As data volumes continue to grow, so will the need for high bandwidth, low latency networking between instances. Enhanced networking options like ENA and EFA will become increasingly important, as will 100 Gbps and higher networking options.
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Specialization: Expect to see more specialized instance types optimized for specific workloads and use cases. For example, the G4ad instances with AMD GPUs and AMD CPUs are designed specifically for graphics-intensive and machine learning workloads.
By staying on top of these trends and continually evaluating new instance type options, IT decision makers can ensure they are delivering the best performance and value for their organizations.
Conclusion
EC2 instance type selection is both an art and a science. By understanding the technical capabilities and performance characteristics of each instance family, as well as the requirements of your specific workloads and applications, you can make informed decisions that balance performance, cost, and operational efficiency.
But optimizing your EC2 instances is not a one-time event. As your business needs evolve and AWS releases new instance types, it‘s important to continually monitor and re-evaluate your instance type choices. By leveraging tools like AWS Cost Explorer, Trusted Advisor, and CloudWatch, you can get visibility into instance usage and performance and identify opportunities to right-size or upgrade your instances.
No matter where you are in your cloud journey, taking the time to master EC2 instance type selection will pay dividends in terms of faster time-to-market, lower costs, and better customer experiences. By following the best practices and recommendations in this guide, you‘ll be well on your way to becoming an EC2 instance type expert.
