04.01-types.md

Instance Types

https://aws.amazon.com/ec2/instance-types/

General Purposes

	A1	T3	T2	M5	M4	T3a (soon)
Features	64-bit Arm Neoverse, EBS optimized	Burstable CPU, EBS optimized	Burstable CPU, High frequency Intel Xeon processors, Balance of compute, memory, and network resources	2.5 GHz Intel Xeon® Platinum 8175, the latest generation	AMD EPYC 7000 series processors, the latest generation	the next generation burstable general-purpose instance type
Use Cases	Scale-out workloads such as web servers, containerized microservices, caching fleets, and distributed data stores, as well as development environments	Micro-services, low-latency interactive applications, small and medium databases, virtual desktops, development environments, code repositories, and business-critical applications	Websites and web applications, development environments, build servers, code repositories, micro services, test and staging environments, and line of business applications.	Small and mid-size databases, data processing tasks that require additional memory, caching fleets, and for running backend servers for SAP, Microsoft SharePoint, cluster computing, and other enterprise applications	Small and mid-size databases, data processing tasks that require additional memory, caching fleets, and for running backend servers for SAP, Microsoft SharePoint, cluster computing, and other enterprise applications	Micro-services, low-latency interactive applications, small and medium databases, virtual desktops, development environments, code repositories, and business-critical applications

Compute Optimized

	C5	C5n	C4
Features	optimized for compute-intensive workloads and deliver cost-effective high performance at a low price per compute ratio	ideal for high compute applications (including High Performance Computing (HPC) workloads, data lakes, and network appliances such as firewalls and routers)	optimized for compute-intensive workloads and deliver very cost-effective high performance at a low price per compute ratio.
Use Cases	High performance web servers, scientific modelling, batch processing, distributed analytics, high-performance computing (HPC), machine/deep learning inference, ad serving, highly scalable multiplayer gaming, and video encoding.	High performance web servers, scientific modelling, batch processing, distributed analytics, high-performance computing (HPC), machine/deep learning inference, ad serving, highly scalable multiplayer gaming, and video encoding.	High performance front-end fleets, web-servers, batch processing, distributed analytics, high performance science and engineering applications, ad serving, MMO gaming, and video-encoding.

Memory Optimized

	R5	R5a	R4	X1e	X1
Features	deliver 5% additional memory per vCPU than R4 and the largest size provides 768 GiB of memory. In addition, R5 instances deliver a 10% price per GiB improvement and a ~20% increased CPU performance over R4.	deliver 5% additional memory per vCPU than R4 and the largest size provides 768 GiB of memory. In addition, R5a instances deliver a 10% price per GiB improvement and a ~20% increased CPU performance over R4.	optimized for memory-intensive applications and offer better price per GiB of RAM than R3.	optimized for high-performance databases, in-memory databases and other memory intensive enterprise applications.	optimized for large-scale, enterprise-class and in-memory applications, and offer one of the lowest price per GiB of RAM among Amazon EC2 instance types.
Use Cases	R5 instances are well suited for memory intensive applications such as high performance databases, distributed web scale in-memory caches, mid-size in-memory databases, real time big data analytics, and other enterprise applications.	R5a instances are well suited for memory intensive applications such as high performance databases, distributed web scale in-memory caches, mid-size in-memory databases, real time big data analytics, and other enterprise applications.	High performance databases, data mining & analysis, in-memory databases, distributed web scale in-memory caches, applications performing real-time processing of unstructured big data, Hadoop/Spark clusters, and other enterprise applications.	High performance databases, in-memory databases (e.g. SAP HANA) and memory intensive applications. x1e.32xlarge instance certified by SAP to run next-generation Business Suite S/4HANA, Business Suite on HANA (SoH), Business Warehouse on HANA (BW), and Data Mart Solutions on HANA on the AWS cloud.	In-memory databases (e.g. SAP HANA), big data processing engines (e.g. Apache Spark or Presto), high performance computing (HPC). Certified by SAP to run Business Warehouse on HANA (BW), Data Mart Solutions on HANA, Business Suite on HANA (SoH), Business Suite S/4HANA.

Accelerated Computing

	P3	P2	G3	F1
Features	the latest generation of general purpose GPU instances.	intended for general-purpose GPU compute applications.	optimized for graphics-intensive applications.	offer customizable hardware acceleration with field programmable gate arrays (FPGAs).
Use Cases	Machine/Deep learning, high performance computing, computational fluid dynamics, computational finance, seismic analysis, speech recognition, autonomous vehicles, drug discovery.	Machine learning, high performance databases, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, genomics, rendering, and other server-side GPU compute workloads.	3D visualizations, graphics-intensive remote workstation, 3D rendering, application streaming, video encoding, and other server-side graphics workloads.	Genomics research, financial analytics, real-time video processing, big data search and analysis, and security.

Storage Optimized

	H1	I3	D2
Features	up to 16 TB of HDD-based local storage, deliver high disk throughput, and a balance of compute and memory.	SSD-backed instance storage optimized for low latency, very high random I/O performance, high sequential read throughput and provide high IOPS at a low cost	up to 48 TB of HDD-based local storage, deliver high disk throughput, and offer the lowest price per disk throughput performance on Amazon EC2.
Use Cases	MapReduce-based workloads, distributed file systems such as HDFS and MapR-FS, network file systems, log or data processing applications such as Apache Kafka, and big data workload clusters.	NoSQL databases (e.g. Cassandra, MongoDB, Redis), in-memory databases (e.g. Aerospike), scale-out transactional databases, data warehousing, Elasticsearch, analytics workloads.	Massively Parallel Processing (MPP) data warehousing, MapReduce and Hadoop distributed computing, distributed file systems, network file systems, log or data-processing applications.