How to Select the Right EC2 Instance – A Guide to EC2 Instances and Their Capabilities

Amazon EC2 is one of the core services in AWS‘s compute offerings, enabling you to provision virtual servers in the cloud to run practically any workload imaginable. With over 300 instance types across more than a dozen families, the options for configuring an EC2 instance are nearly endless.

While choice and flexibility are certainly positive, the sheer number of EC2 instance types can make selecting the right one for your specific use case a daunting challenge. You need to weigh several factors such as the compute, memory, storage and network requirements of your application, as well as your performance and cost constraints.

In this post, I‘ll break down the key decisions you need to make when choosing an EC2 instance and share some expert tips to help you find the optimal instance for your workload. Whether you‘re deploying a small web application or running intensive machine learning jobs, read on to learn how to get the most performance for your dollar with EC2.

Understanding the EC2 Instance Families

The first key to making sense of the hundreds of EC2 instance types is understanding the different instance families. An instance family is a group of instance types that share similar hardware specifications and are optimized for a specific use case.

There are five main EC2 instance families:

1. General Purpose – Balanced mix of compute, memory and network resources. Ideal for a wide variety of workloads.
2. Compute Optimized – Highest ratio of vCPUs to memory. Ideal for compute-intensive applications like high performance computing (HPC).
3. Memory Optimized – Largest amount of memory per vCPU. Ideal for memory-intensive workloads like in-memory databases and caches.
4. Storage Optimized – Attached high-performance local storage (instance store). Ideal for I/O-intensive workloads like distributed filesystems and NoSQL databases.
5. Accelerated Computing – Equipped with hardware accelerators like GPUs. Ideal for machine learning, 3D rendering, and other floating-point intensive tasks.

Within each family, there are several instance types that vary in their exact CPU, memory, storage and network specifications. The instance type naming conventions encode information about the instance‘s generation and capabilities.

For example, in the instance type m5.2xlarge:

• m: instance family (General Purpose)
• 5: instance generation (5th generation)
• 2xlarge: instance size (2x number of vCPUs and memory of xlarge)

Some instance types also have additional capabilities indicated by a suffix after the family, for example:

• m5a: AMD CPUs
• m5n: Higher network bandwidth
• i3en: Enhanced networking and Elastic Network Adapter (ENA)

With the naming basics out of the way, let‘s dive into the key considerations you should keep in mind when selecting an EC2 instance.

Key Considerations When Choosing an EC2 Instance

Compute

One of the primary considerations is the compute power you need, determined by the number of vCPUs and the clock speed (in GHz). More vCPUs enable greater parallelism as you can run more threads concurrently. A higher clock speed means faster execution of sequential tasks.

For example, the c5.large compute-optimized instance comes with 2 vCPUs and a 3.4 GHz base clock speed. The c5.24xlarge, on the other hand, comes with 96 vCPUs but the same 3.4 GHz clock speed. So while the 24xlarge has 48x the parallel processing power, both instances have the same sequential processing speed.

When choosing vCPUs, keep in mind that the vCPUs on EC2 instances are actually hyperthread units, which means 2 threads run on a single physical core. The exception is EC2 instances with full-cores, like the M5zn and C5n.

Memory

Another critical resource to consider is the amount of memory (RAM) available on the instance. Having sufficient memory is essential for good application performance. If your application exceeds the available memory and starts swapping to disk, you‘ll see a major slowdown.

The ratio of memory to vCPUs varies between instance families and types. Memory optimized instances like R5 offer the highest amount of RAM per vCPU. For example, r5.xlarge instances have 4 vCPUs and 32 GiB of memory, so 8 GiB of memory per vCPU.

In contrast, compute optimized instances prioritize vCPUs over memory. The c5.xlarge also has 4 vCPUs but only 8 GiB of memory, so 2 GiB per vCPU.

To determine your memory needs, you‘ll need to load test your application and measure the memory utilization. As a general rule of thumb, you want to select an instance where your peak memory utilization is no more than 80% of the total available memory. This headroom will allow you to handle any unforeseen spikes in usage.

Storage

EC2 instances have two options for storage – Elastic Block Store (EBS) and Instance Store.

EBS volumes are network-attached storage that can be dynamically attached and detached from instances. They are durable, and data stored on them persists even after the instance is stopped. EBS is used by most EC2 instances.

Instance Store volumes are physically attached to the host server and offer very high I/O performance. However, data on Instance Store is lost when the instance is stopped, terminated, or crashes. Only a few instance families, such as Storage Optimized (I3, D2), support Instance Store.

When configuring EBS volumes, the key metrics to consider are the size (in GiB) and the performance (in IOPS). For an instance with 100 GiB of storage, a baseline performance of 300 IOPS means it can perform around 300 read or write operations per second.

Provisioned IOPS (io1/io2) volumes can deliver higher performance than general purpose volumes (gp2/gp3) but also cost more. For example, io2 Block Express volumes can achieve a maximum throughput of 4,000 MB/s versus 1,000 MB/s for gp3.

Network

The networking capabilities of your EC2 instance determine how quickly it can communicate with other resources like EC2 instances, S3 buckets or on-premises servers.

Different instance types offer varying network bandwidth, from Low to 100 Gigabit. EC2 instances with the n suffix are network-optimized and offer higher bandwidth and lower latency. For example, the c5n.18xlarge instance has 100 Gbps network bandwidth compared to 25 Gbps on the c5.18xlarge.

When to opt for network-optimized instances? For applications that need to transfer large amounts of data or have a high number of network requests, like content delivery or telecommunication workloads. You‘ll also see better performance for latency-sensitive workloads like real-time gaming or video streaming.

Accelerators

For specialized workloads, you may need EC2 instances equipped with hardware accelerators like GPUs, FPGAs or AWS Inferentia chips.

GPUs excel at parallel processing of data and are commonly used for compute-intensive workloads like machine learning training, 3D rendering and video encoding. The P3 and G4 instance families are equipped with NVIDIA Tesla V100 and T4 GPUs respectively.

FPGAs are programmable hardware accelerators and can offer even better performance than GPUs for certain algorithms. F1 instances include Xilinx UltraScale+ FPGAs that you can program using the AWS FPGA developer kit.

Finally, AWS Inferentia is a custom chip designed by AWS specifically for machine learning inference. It powers the Inf1 instances and can deliver higher throughput and lower cost compared to GPU-based instances.

Pricing Model

The final key consideration in choosing an EC2 instance is the pricing model. EC2 offers four main pricing options:

1. On-Demand – Pay by the second for the instances you launch, with no long-term commitments or upfront payments. Highest cost but most flexibility.

2. Savings Plans – Commit to a consistent usage (measured in $/hour) for a 1-year or 3-year term. This can provide up to 72% savings compared to On-Demand pricing.

3. Reserved Instances – Commit to a specific instance configuration for a 1-year or 3-year term. Provides up to 75% savings compared to On-Demand pricing.

4. Spot Instances – Request spare EC2 computing capacity for up to 90% off the On-Demand price. The catch is that these instances can be interrupted by AWS with just a 2-minute warning.

For production workloads with predictable and steady-state usage, Reserved Instances or Savings Plans can offer significant cost savings. For flexible or interruptible workloads, Spot Instances can be an attractive option to optimize costs.

Putting it All Together: Choosing Your EC2 Instance

With an understanding of the key capabilities and trade-offs of EC2 instances, let‘s walk through a process for selecting the right instance for your application.

Step 1: Determine Your Dominant Resource Needs

Analyze your application and determine which resource is most critical for performance: compute, memory, storage I/O, network bandwidth, or accelerators like GPUs. This will point you towards the right instance family to start with.

For example, an in-memory caching service like Redis or Memcached would be best served by a Memory Optimized (R5) instance, while a big data processing engine like Apache Spark would benefit more from Compute Optimized (C5) or Storage Optimized (I3) instances.

Step 2: Select the Latest Generation

Within the target instance family, pick the latest generation instance type available for the best price/performance. For example, an R5 instance would be preferred over R4 or R3 as it uses a newer version (Intel Xeon Platinum 8000 series) of the underlying CPU.

AWS frequently refreshes instance families with the latest CPU models and optimized hardware configurations. A newer generation will typically deliver better performance per dollar spent.

Step 3: Determine Any Special Feature Needs

Narrow down your instance type by determining if you have any special feature requirements such as:
– Advanced networking (enhanced networking, ENA, placement groups)
– Local storage (NVMe instance store volumes)
– Dedicated hardware (Dedicated Instances, Dedicated Hosts)

For example, if your application needs access to a high-performance local filesystem, you may want to select an I3en instance that comes equipped with high IOPS NVMe SSD instance store volumes.

Step 4: Benchmark and Right-size Your Instance

Now that you have a target instance type selected, it‘s time to put it through its paces and validate your choice. Load test your application on the selected instance type and monitor key metrics like CPU, memory, disk, and network utilization.

Ideally, you want to select an instance size where your application‘s peak usage is around 70-80% of the available resource capacity. This will ensure you have some headroom for unexpected spikes without overprovisioning and paying for unused resources.

Be sure to test different instance sizes within the family to find the right balance. Tools like AWS CloudWatch or the EC2 Instance Metrics API can help you collect utilization metrics to guide your decision.

Step 5: Optimize Costs With Pricing Models

As a final optimization, look to see if you can reduce the cost of your instance by committing to EC2 Savings Plans or using Spot Instances for non-critical portions of your application.

Even if you can‘t commit usage for the full application, you may be able to supplement On-Demand Instances with Reserved Instances for components that have predictable usage like databases, message queues or search indexes.

Conclusion

Finding the optimal EC2 instance for your application starts with understanding your resource needs and matching them to the capabilities of the EC2 instance families. By following a data-driven approach and employing some of the tips shared in this guide, you‘ll be well on your way to configuring cost-effective and high-performance EC2 instances for your workloads.

The diverse options and flexibility that EC2 offers are a key part of what makes it such a compelling service for a wide variety of applications. As AWS continues to innovate and release new EC2 instance types, the potential use cases will only expand. Invest the time to understand how your application uses cloud resources and continuously iterate on your instance choices – your effort will be rewarded in performance, scalability and cost savings.