EC2 Instances
An EC2 instance may only be a virtualized and abstracted subset of a physical server, but it
behaves just like the real thing. It’ll have access to storage, memory, and a network interface,
and its primary drive will come with a fresh and clean operating system running.
It’s up to you to decide what kind of hardware resources you want your instance to have,
what operating system and software stack you’d like it to run, and, ultimately, how much
you’ll pay for it. Let’s see how all that works.
Provisioning Your Instance
You configure your instance’s operating system and software stack, hardware specs (the
CPU power, memory, primary storage, and network performance), and environment before
launching it. The OS is defined by the Amazon Machine Image (AMI) you choose, and the
hardware follows the instance type.
EC2 Amazon Machine Images
An AMI is really just a template document that contains information telling EC2 what OS
and application software to include on the root data volume of the instance it’s about to
launch. There are four kinds of AMIs.
Amazon Quick Start AMIs
Amazon Quick Start images appear at the top of the list in the
console when you start the process of launching a new instance. The Quick Start AMIs are
popular choices and include various releases of Linux or Windows Server OSs and some
specialty images for performing common operations (like deep learning and database). These
AMIs are up-to-date and officially supported.
AWS Marketplace AMIs
Community AMIs
There are more than 100,000 images available as Community AMIs.
Many of these images are AMIs created and maintained by independent vendors and are
usually built to meet a specific need. This is a good catalog to search if you’re planning an
application built on a custom combination of software resources.
Private AMIs
You can also store images created from your own instance deployments as
private AMIs. Why would you want to do that? You might, for instance, want the ability
to scale up the number of instances you’ve got running to meet growing demand. Having a
reliable instance image as an AMI makes incorporating autoscaling easy. You can also share
images as AMIs or import VMs from your local infrastructure (by way of AWS S3) using the
AWS VM Import/Export tool.
A particular AMI will be available in only a single region—although there will often
be images with identical functionality in all regions. Keep this in mind as you plan your
deployments: invoking the ID of an AMI in one region while working from within a different
region will fail.
Instance Types
AWS allocates hardware resources to your instances according to the instance type—or
hardware profi le—you select. The particular workload you’re planning for your instance will
determine the type you choose. The idea is to balance cost against your need for compute
power, memory, and storage space. Ideally, you’ll fi nd a type that offers exactly the amount
of each to satisfy both your application and budget.
Should your needs change over time, you can easily move to a different instance type by
stopping your instance, editing its instance type, and starting it back up again.
As listed in Table 2.1 , there are currently more than 75 instance types organized into fi ve
instance families, although AWS frequently updates their selection. You can view the most
recent collection at https://aws.amazon.com/ec2/instance-types/ .
General Purpose The General Purpose family includes T3, T2, M5, and M4 types, which all
aim to provide a balance of compute, memory, and network resources. T2 types, for instance,
range from the t2.nano with one virtual CPU (vCPU0) and half a gigabyte of memory all
the way up to the t2.2xlarge with its eight vCPUs and 32 GB of memory. Because it’s Free
Tier–eligible, the t2.micro is often a good choice for experimenting. But there’s nothing
stopping you from using it for light-use websites and various development-related services.
M5 and M4 instances are recommended for many small and midsize data-centric operations.
Unlike T2, which requires EBS virtual volumes for storage, some M* instances come with
their own instance storage drives that are actually physically attached to the host server. M5
types range from m5.large (2 vCPUs and 6 GB of memory) to the monstrous m5d.24xlarge
(96 vCPUs and 382 GB of memory).
Also read this topic: Introduction to Cloud Computing and AWS -1
Compute Optimized For more demanding web servers and high-end machine learning
workloads, you’ll choose from the Compute Optimized family that includes C5 and C4
types. C5 machines—currently available from the c5.large to the c5d.18xlarge—give you as
much as 3.5 GHz of processor speed and strong network bandwidth.
Memory Optimized Memory Optimized instances work well for intensive database,
data analysis, and caching operations. The X1e, X1, and R4 types are available with
as much as 3 terabytes of DRAM-based memory and low-latency SSD storage volumes
attached.
Accelerated Computing You can achieve higher-performing general-purpose graphics processing
unit (GPGPU) performance from the P3, P2, G3, and F1 types within the Accelerated
Computing group. These instances make use of various generations of high-end NVIDIA
GPUs or, in the case of the F1 instances, a Xilinx Virtex UltraScale+ field-programmable gate
array (FPGA—if you don’t know what that is, then you probably don’t need it). Accelerated
Computing instances are recommended for demanding workloads such as 3D visualizations
and rendering, financial analysis, and computational fluid dynamics.
Storage Optimized The H1, I3, and D2 types currently make up the Storage Optimized
family that have large, low-latency instance storage volumes—as large as 16 TB (or, in the
case of D2, up to 48 TB of slower HDD storage). These instances work well with distributed
file systems and heavyweight data processing applications.
The specification details and instance type names will frequently change as AWS continues
to leverage new technologies to support its customers’ growing computing demands.
But it’s important to at least be familiar with the instance type families and the naming
conventions AWS uses to identify them.
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