Amazon EC2 provides a number of kinds of digital servers, also referred to as situations, that helps clients select the CPU, reminiscence, storage, and networking capability wanted to run their functions.
Currently, out there Instance sorts are General Purpose, Compute Optimized, Memory Optimized, Accelerated Computing, Storage Optimized, and Bare Metal.
General Purpose Instances
General goal situations are designed to offer customers a steadiness of compute, reminiscence, and networking efficiency.
A1 situations are perfect for workloads supported by the Arm ecosystem. These situations do effectively for software comparable to Web Servers, Containerized microservices, caching fleets, distributed information shops and functions that want Arm instruction set.
| Model | vCPU | Mem (GiB) | Storage | Network Performance (Gbps) |
| a1.medium | 1 | 2 | EBS-Only | Up to 10 |
| a1.massive | 2 | 4 | EBS-Only | Up to 10 |
| a1.xlarge | 4 | 8 | EBS-Only | Up to 10 |
| a1.2xlarge | 8 | 16 | EBS-Only | Up to 10 |
| a1.4xlarge | 16 | 32 | EBS-Only | Up to 10 |
T2 and T3 Instances supply a base stage of CPU efficiency however have the skill to go (burst) larger when required by the work load. Ideal for functions comparable to web sites and internet functions, code repositories, growth, construct, take a look at and staging environments.
| Model | vCPU* | CPU Credits/hour | Mem (GiB) | Storage | Network Performance (Gbps) |
| t3.nano | 2 | 6 | 0.5 | EBS-Only | Up to five |
| t3.micro | 2 | 12 | 1 | EBS-Only | Up to five |
| t3.small | 2 | 24 | 2 | EBS-Only | Up to five |
| t3.medium | 2 | 24 | 4 | EBS-Only | Up to five |
| t3.massive | 2 | 36 | 8 | EBS-Only | Up to five |
| t3.xlarge | 4 | 96 | 16 | EBS-Only | Up to five |
| t3.2xlarge | 8 | 192 | 32 | EBS-Only | Up to five |
| t2.nano | 1 | 3 | 0.5 | EBS-Only | Low |
| t2.micro | 1 | 6 | 1 | EBS-Only | Low to Moderate |
| t2.small | 1 | 12 | 2 | EBS-Only | Low to Moderate |
| t2.medium | 2 | 24 | 4 | EBS-Only | Low to Moderate |
| t2.massive | 2 | 36 | 8 | EBS-Only | Low to Moderate |
| t2.xlarge | 4 | 54 | 16 | EBS-Only | Moderate |
| t2.2xlarge | 8 | 81 | 32 | EBS-Only | Moderate |
M5, M5a, and M5d Instances supply a steadiness of compute, reminiscence and community assets for a variety of functions comparable to Web and software servers, small and medium databases, gaming servers, caching fleets and to run backend servers for Microsoft Sharepoint, SAP, cluster computing and enterprise functions.
| Model | vCPU* | Mem (GiB) | Storage (GiB) | Dedicated EBS Bandwidth (Mbps) | Network Performance (Gbps) |
| m5.massive | 2 | 8 | EBS-only | Up to three,500 | Up to 10 |
| m5.xlarge | 4 | 16 | EBS-only | Up to three,500 | Up to 10 |
| m5.2xlarge | 8 | 32 | EBS-only | Up to three,500 | Up to 10 |
| m5.4xlarge | 16 | 64 | EBS-only | 3,500 | Up to 10 |
| m5.12xlarge | 48 | 192 | EBS-only | 7,000 | 10 |
| m5.24xlarge | 96 | 384 | EBS-only | 14,000 | 25 |
| m5d.massive | 2 | 8 | 1 x 75 NVMe SSD | Up to three,500 | Up to 10 |
| m5d.xlarge | 4 | 16 | 1 x 150 NVMe SSD | Up to three,500 | Up to 10 |
| m5d.2xlarge | 8 | 32 | 1 x 300 NVMe SSD | Up to three,500 | Up to 10 |
| m5d.4xlarge | 16 | 64 | 2 x 300 NVMe SSD | 3,500 | Up to 10 |
| m5d.12xlarge | 48 | 192 | 2 x 900 NVMe SSD | 7,000 | 10 |
| m5d.24xlarge | 96 | 384 | Four x 900 NVMe SSD | 14,000 | 25 |
| m5a.massive | 2 | 8 | EBS-only | Up to 2,120 | Up to 10 |
| m5a.xlarge | 4 | 16 | EBS-only | Up to 2,120 | Up to 10 |
| m5a.2xlarge | 8 | 32 | EBS-only | Up to 2,120 | Up to 10 |
| m5a.4xlarge | 16 | 64 | EBS-only | 2,120 | Up to 10 |
| m5a.12xlarge | 48 | 192 | EBS-only | 5,000 | 10 |
| m5a.24xlarge | 96 | 384 | EBS-only | 10,000 | 20 |
| Model | vCPU* | Mem (GiB) | Storage | Dedicated EBS Bandwidth (Mbps) | Network Performance |
| m4.massive | 2 | 8 | EBS-only | 450 | Moderate |
| m4.xlarge | 4 | 16 | EBS-only | 750 | High |
| m4.2xlarge | 8 | 32 | EBS-only | 1,000 | High |
| m4.4xlarge | 16 | 64 | EBS-only | 2,000 | High |
| m4.10xlarge | 40 | 160 | EBS-only | 4,000 | 10 Gigabit |
| m4.16xlarge | 64 | 256 | EBS-only | 10,000 | 25 Gigabit |
Compute Optimized situations
As the identify signifies, Compute Optimized situations are nice for functions that want a excessive quantity of compute energy. Ideal for compute-intensive functions like high-performance internet servers, high-performance computing (HPC), scientific modelling, distributed analytics and machine studying inference.
| Model | vCPU* | Mem (GiB) | Storage (GiB) | Dedicated EBS Bandwidth (Mbps) | Network Performance (Gbps) |
| c5.massive | 2 | 4 | EBS-Only | Up to three,500 | Up to 10 |
| c5.xlarge | 4 | 8 | EBS-Only | Up to three,500 | Up to 10 |
| c5.2xlarge | 8 | 16 | EBS-Only | Up to three,500 | Up to 10 |
| c5.4xlarge | 16 | 32 | EBS-Only | 3,500 | Up to 10 |
| c5.9xlarge | 36 | 72 | EBS-Only | 7,000 | 10 |
| c5.18xlarge | 72 | 144 | EBS-Only | 14,000 | 25 |
| c5d.massive | 2 | 4 | 1 x 50 NVMe SSD | Up to three,500 | Up to 10 |
| c5d.xlarge | 4 | 8 | 1 x 100 NVMe SSD | Up to three,500 | Up to 10 |
| c5d.2xlarge | 8 | 16 | 1 x 200 NVMe SSD | Up to three,500 | Up to 10 |
| c5d.4xlarge | 16 | 32 | 1 x 400 NVMe SSD | 3,500 | Up to 10 |
| c5d.9xlarge | 36 | 72 | 1 x 900 NVMe SSD | 7,000 | 10 |
| c5d.18xlarge | 72 | 144 | 2 x 900 NVMe SSD | 14,000 | 25 |
| c5n.massive | 2 | 5.25 | EBS-Only | Up to three,500 | Up to 25 |
| c5n.xlarge | 4 | 10.5 | EBS-Only | Up to three,500 | Up to 25 |
| c5n.2xlarge | 8 | 21 | EBS-Only | Up to three,500 | Up to 25 |
| c5n.4xlarge | 16 | 42 | EBS-Only | 3,500 | Up to 25 |
| c5n.9xlarge | 36 | 96 | EBS-Only | 7,000 | 50 |
| c5n.18xlarge | 72 | 192 | EBS-Only | 14,000 | 100 |
| c4.massive | 2 | 3.75 | EBS-Only | 500 | Moderate |
| c4.xlarge | 4 | 7.5 | EBS-Only | 750 | High |
| c4.2xlarge | 8 | 15 | EBS-Only | 1,000 | High |
| c4.4xlarge | 16 | 30 | EBS-Only | 2,000 | High |
| c4.8xlarge | 36 | 60 | EBS-Only | 4,000 | 10 Gigabit |
Memory Optimized situations
Memory-optimized situations supply massive reminiscence dimension for reminiscence intensive functions together with in-memory functions, in-memory databases, in-memory analytics options, High Performance Computing (HPC), scientific computing, and different memory-intensive functions.
R4, R5, and R5a Instances ship quick efficiency for workloads that course of massive information units in reminiscence.
These situations are nice for High-performance, relational (MySQL) and NoSQL (MongoDB, Cassandra) databases, Distributed internet scale cache shops that present in-memory caching of key-value sort information (Memcached and Redis), In-memory databases utilizing optimized information storage codecs and analytics for enterprise intelligence (for instance, SAP HANA), Applications performing real-time processing of huge unstructured information (monetary companies, Hadoop/Spark clusters) and High-performance computing (HPC) and Electronic Design Automation (EDA) functions.
| Model | vCPU | Mem (GiB) | Storage (GiB) | Dedicated EBS Bandwidth (Mbps) | Networking Performance (Gbps) |
| r5.massive | 2 | 16 | EBS-Only | as much as 3,500 | Up to 10 |
| r5.xlarge | 4 | 32 | EBS-Only | as much as 3,500 | Up to 10 |
| r5.2xlarge | 8 | 64 | EBS-Only | as much as 3,500 | Up to 10 |
| r5.4xlarge | 16 | 128 | EBS-Only | 3,500 | Up to 10 |
| r5.12xlarge | 48 | 384 | EBS-Only | 7,000 | 10 |
| r5.24xlarge | 96 | 768 | EBS-Only | 14,000 | 25 |
| r5d.massive | 2 | 16 | 1 x 75 NVMe SSD | as much as 3,500 | Up to 10 |
| r5d.xlarge | 4 | 32 | 1 x 150 NVMe SSD | as much as 3,500 | Up to 10 |
| r5d.2xlarge | 8 | 64 | 1 x 300 NVMe SSD | as much as 3,500 | Up to 10 |
| r5d.4xlarge | 16 | 128 | 2 x 300 NVMe SSD | 3,500 | Up to 10 |
| r5d.12xlarge | 48 | 384 | 2 x 900 NVMe SSD | 7,000 | 10 |
| r5d.24xlarge | 96 | 768 | Four x 900 NVMe SSD | 14,000 | 25 |
| r5a.massive | 2 | 16 | EBS-Only | as much as 2,120 | Up to 10 |
| r5a.xlarge | 4 | 32 | EBS-Only | as much as 2,120 | Up to 10 |
| r5a.2xlarge | 8 | 64 | EBS-Only | as much as 2,120 | Up to 10 |
| r5a.4xlarge | 16 | 128 | EBS-Only | 2,120 | Up to 10 |
| r5a.12xlarge | 48 | 384 | EBS-Only | 5,000 | 10 |
| r5a.24xlarge | 96 | 768 | EBS-Only | 10,000 | 20 |
| Model | vCPU | Mem (GiB) | Storage | Networking Performance (Gbps) |
| r4.massive | 2 | 15.25 | EBS-Only | Up to 10 |
| r4.xlarge | 4 | 30.5 | EBS-Only | Up to 10 |
| r4.2xlarge | 8 | 61 | EBS-Only | Up to 10 |
| r4.4xlarge | 16 | 122 | EBS-Only | Up to 10 |
| r4.8xlarge | 32 | 244 | EBS-Only | 10 |
| r4.16xlarge | 64 | 488 | EBS-Only | 25 |
High reminiscence, “u”, situations have 6 TiB, 9 TiB, and 12 TiB of reminiscence per occasion. They are designed to run massive in-memory databases, together with manufacturing installations of SAP HANA. These situations supply naked steel efficiency with direct entry to host {hardware}.
| Model | Logical Proc* | Mem (TiB) | Network Perf. (Gbps) | Dedicated EBS Bandwidth (Gbps) | Network Performance |
| u-6tb1.steel | 448 | 6 | 25 | 14 | 25 Gigabit |
| u-9tb1.steel | 448 | 9 | 25 | 14 | 25 Gigabit |
| u-12tb1.steel | 448 | 12 | 25 | 14 | 25 Gigabit |
x1 and x1e situations are effectively fitted to in-memory databases comparable to SAP HANA, Big-data processing engines like Apace Spark or Presto, High efficiency computing functions and reminiscence intensive enterprise functions.
| x1e.xlarge | 4 | 122 | 1 x 120 | 500 | Up to 10 Gigabit |
| x1e.2xlarge | 8 | 244 | 1 x 240 | 1,000 | Up to 10 Gigabit |
| x1e.4xlarge | 16 | 488 | 1 x 480 | 1,750 | Up to 10 Gigabit |
| x1e.8xlarge | 32 | 976 | 1 x 960 | 3,500 | Up to 10 Gigabit |
| x1e.16xlarge | 64 | 1,952 | 1 x 1,920 | 7,000 | 10 Gigabit |
| x1e.32xlarge | 128 | 3,904 | 2 x 1,920 | 14,000 | 25 Gigabit |
| x1.16xlarge | 64 | 976 | 1 x 1,920 | 7,000 | 10 Gigabit |
| x1.32xlarge | 128 | 1,952 | 2 x 1,920 | 14,000 | 25 Gigabit |
z1d Instances ship excessive compute and excessive reminiscence. These situations are perfect for digital design automation and relational database workloads.
| Model | vCPU | Mem (GiB) | Networking Performance | SSD Storage (GB) |
| z1d.massive | 2 | 16 | Up to 10 Gigabit | 1 x 75 NVMe SSD |
| z1d.xlarge | 4 | 32 | Up to 10 Gigabit | 1 x 150 NVMe SSD |
| z1d.2xlarge | 8 | 64 | Up to 10 Gigabit | 1 x 300 NVMe SSD |
| z1d.3xlarge | 12 | 96 | Up to 10 Gigabit | 1 x 450 NVMe SSD |
| z1d.6xlarge | 24 | 192 | 10 Gigabit | 1 x 900 NVMe SSD |
| z1d.12xlarge | 48 | 384 | 25 Gigabit | 2 x 900 NVMe SSD |
Accelerated Computing situations
“Accelerated Computing occasion household is a household of situations which use {hardware} accelerators, or co-processors, to carry out some features, comparable to floating-point quantity calculation and graphics processing, extra effectively than is feasible in software program working on CPUs.
Amazon EC2 supplies three kinds of Accelerated Computing situations – GPU compute situations for general-purpose computing, GPU graphics situations for graphics intensive functions, and FPGA programmable {hardware} compute situations for superior scientific workloads.”
P3 situations are effectively fitted to deep studying, computational fluid dynamics, computational finance, seismic evaluation, molecular modeling, genomics, rendering, and different server-side GPU compute workloads.
| Model | GPUs | vCPU | Mem (GiB) | GPU Mem (GiB) | GPU P2P | Storage (GiB) | Dedicated EBS Bandwidth | Networking Performance |
| p3.2xlarge | 1 | 8 | 61 | 16 | – | EBS-Only | 1.5 Gbps | Up to 10 Gigabit |
| p3.8xlarge | 4 | 32 | 244 | 64 | NVLink | EBS-Only | 7 Gbps | 10 Gigabit |
| p3.16xlarge | 8 | 64 | 488 | 128 | NVLink | EBS-Only | 14 Gbps | 25 Gigabit |
| p3dn.24xlarge | 8 | 96 | 768 | 256 | NVLink | 2 x 900 NVMe SSD | 14 Gbps | 100 Gigabit |
P2 situations are effectively fitted to deep studying, graph databases, high-performance databases, computational fluid dynamics, computational finance, seismic evaluation, molecular modeling, genomics, rendering, and different server-side GPU compute workloads.
| Model | GPUs | vCPU | Mem (GiB) | GPU Memory (GiB) | Network Performance |
| p2.xlarge | 1 | 4 | 61 | 12 | High |
| p2.8xlarge | 8 | 32 | 488 | 96 | 10 Gigabit |
| p2.16xlarge | 16 | 64 | 732 | 192 | 25 Gigabit |
G3 situations are perfect for functions comparable to 3D visualizations, graphics-intensive distant workstations, 3D rendering, video encoding, digital actuality, and different server-side graphics workloads requiring massively parallel processing energy.
| Model | GPUs | vCPU | Mem (GiB) | GPU Memory (GiB) | Network Performance |
| g3s.xlarge | 1 | 4 | 30.5 | 8 | Up to 10 Gigabit |
| g3.4xlarge | 1 | 16 | 122 | 8 | Up to 10 Gigabit |
| g3.8xlarge | 2 | 32 | 244 | 16 | 10 Gigabit |
| g3.16xlarge | 4 | 64 | 488 | 32 | 25 Gigabit |
“F1 situations are designed to speed up computationally intensive algorithms, comparable to data-flow or extremely parallel operations not suited to common goal CPUs.”
| Model | FPGAs | vCPU | Mem (GiB) | SSD Storage (GB) | Networking Performance |
| f1.2xlarge | 1 | 8 | 122 | 470 | Up to 10 Gigabit |
| f1.4xlarge | 2 | 16 | 244 | 940 | Up to 10 Gigabit |
| f1.16xlarge | 8 | 64 | 976 | Four x 940 | 25 Gigabit |
Storage Optimized situations
“Dense-storage instances are designed for workloads that require high sequential read and write access to very large data sets, such as Hadoop distributed computing, massively parallel processing data warehousing, and log processing applications. The Dense-storage instances offer the best price/GB-storage and price/disk-throughput across other EC2 instances.”
H1 situations are nice for data-intensive workloads comparable to MapReduce and distributed file programs, functions requiring sequential entry to massive quantities of information on direct-attached occasion storage, and functions that require high-throughput entry to massive portions of information
| Model | vCPU* | Mem (GiB) | Networking Performance | Storage (GB) |
| h1.2xlarge | 8 | 32 | Up to 10 Gigabit | 1 x 2,000 HDD |
| h1.4xlarge | 16 | 64 | Up to 10 Gigabit | 2 x 2,000 HDD |
| h1.8xlarge | 32 | 128 | 10 Gigabit | Four x 2,000 HDD |
| h1.16xlarge | 64 | 256 | 25 Gigabit | Eight x 2,000 HDD |
I3 situations are effectively fitted to High frequency on-line transaction processing (OLTP) programs, Relational databases, NoSQL databases, Cache for in-memory databases (for instance, Redis), Data warehousing functions, and Low latency Ad-Tech serving functions
| Model | vCPU* | Mem (GiB) | Networking Performance (Gbps) | Storage (TB) |
| i3.massive | 2 | 15.25 | Up to 10 | 1 x 0.475 NVMe SSD |
| i3.xlarge | 4 | 30.5 | Up to 10 | 1 x 0.95 NVMe SSD |
| i3.2xlarge | 8 | 61 | Up to 10 | 1 x 1.9 NVMe SSD |
| i3.4xlarge | 16 | 122 | Up to 10 | 2 x 1.9 NVMe SSD |
| i3.8xlarge | 32 | 244 | 10 | Four x 1.9 NVMe SSD |
| i3.16xlarge | 64 | 488 | 25 | Eight x 1.9 NVMe SSD |
| i3.steel | 72* | 512 | 25 | Eight x 1.9 NVMe SSD |
D2 situations are perfect for functions comparable to Massive parallel processing (MPP) information warehouse, MapReduce and Hadoop distributed computing and Log or information processing functions.
| Model | vCPU* | Mem (GiB) | Storage (GB) | Network Performance |
| d2.xlarge | 4 | 30.5 | Three x 2000 HDD | Moderate |
| d2.2xlarge | 8 | 61 | 6 x 2000 HDD | High |
| d2.4xlarge | 16 | 122 | 12 x 2000 HDD | High |
| d2.8xlarge | 36 | 244 | 24 x 2000 HDD | 10 Gigabit |
For finest efficiency, Amazon recommends clients use the newest technology situations when launching new compute companies. You can get the record of present technology occasion sorts by visiting Amazon EC2 Instance Types
