Instance Types
Amazon EC2 provides a wide selection of instance types optimized to fit different use cases. Instance types comprise varying combinations of CPU, memory, storage, and networking capacity and give you the flexibility to choose the appropriate mix of resources for your applications.
General Purpose Instances
General purpose instances provide a balance of compute, memory, and networking resources and are ideal for a variety of workloads.
| Instance Type | Use Case | Features |
|---|---|---|
| T3 | Web servers, development environments, and small databases | Burstable performance, low cost, suitable for moderate CPU usage with temporary spikes. |
| M5 | Web servers, enterprise applications, and databases | High performance, balanced compute, memory, and networking resources. |
Compute-Optimized Instances
Compute-optimized instances are ideal for compute-bound applications that benefit from high-performance processors.
| Instance Type | Use Case | Features |
|---|---|---|
| C5 | High-performance computing, batch processing, and video encoding | High performance, compute-optimized processors, suitable for high-performance applications. |
| C6g | High-performance computing, batch processing, and video encoding | High performance, compute-optimized processors, suitable for high-performance applications. |
Memory-Optimized Instances
Memory-optimized instances are designed to deliver fast performance for workloads that process large data sets in memory.
| Instance Type | Use Case | Features |
|---|---|---|
| R5 | In-memory databases, real-time processing of unstructured data, and high-performance computing | High memory capacity, high memory bandwidth, suitable for high-memory applications. |
| X1e | In-memory databases, real-time processing of unstructured data, and high-performance computing | High memory capacity, high memory bandwidth, suitable for high-memory applications. |
Storage-Optimized Instances
Storage-optimized instances are designed for workloads that require high, sequential read and write access to very large data sets on local storage.
| Instance Type | Use Case | Features |
|---|---|---|
| I3 | NoSQL databases, data warehousing, and Elasticsearch | High I/O performance, high storage capacity, suitable for high I/O workloads. |
| D2 | Massively parallel processing, data warehousing, MapReduce, and Hadoop | High disk throughput, high sequential read/write access, suitable for large datasets. |
Accelerated Computing Instances
Accelerated computing instances use hardware accelerators, or co-processors, to perform functions such as floating-point number calculations, graphics processing, or data pattern matching more efficiently than software running on a general-purpose CPU.
| Instance Type | Use Case | Features |
|---|---|---|
| P3 | Machine learning, deep learning, and high-performance computing | High-performance GPUs, suitable for compute-intensive workloads. |
| G4 | Graphics-intensive applications, machine learning, and video encoding | High-performance GPUs, suitable for graphics processing and machine learning. |
Networking-Optimized Instances
Networking-optimized instances are designed to deliver high-performance networking capabilities for applications that require low-latency, high-throughput networking.
| Instance Type | Use Case | Features |
|---|---|---|
| H1 | Big data processing, distributed file systems, and network appliances | High network throughput, high disk throughput, suitable for big data and network-heavy apps. |
| A1 | Scale-out workloads, web servers, and containerized microservices | High network throughput, high disk throughput, suitable for scale-out and microservices. |
Conclusion
Choosing the right instance type is essential for optimizing the performance and cost of your applications. By selecting the appropriate mix of resources, you can ensure that your applications run efficiently and cost-effectively on Amazon EC2.