Key features of EC2 instance types (Families M, T, A, C, Hpc, R, X, U, I, D, P, G)

The key features of general-purpose EC2 instances are:

  1. Balanced compute, memory, and networking resources:

    • General purpose instances are designed to provide a balance of computing, memory, and networking resources.
    • They are suitable for applications that require these resources in equal proportions, such as web servers and code repositories.

  2. Burstable performance:

    • The T instance family, also known as burstable performance instances, provides a baseline CPU performance that can burst above the baseline when needed.
    • These instances suit workloads that don't require sustained high CPU performance.

  3. Flexibility in instance size:

    • Each instance type includes one or more instance sizes, allowing you to scale your resources to the requirements of your target workload.

  4. Support for multiple network interfaces:

    • EC2 instances support multiple network interfaces, enabling management and data plane isolation at the network level.

  5. Placement group control:

    • EC2 offers placement groups, which provide additional control over where your instances are physically placed to optimize for lower latency or higher throughput.

  6. Pricing model flexibility:

    • You can change the pricing model from On-Demand to Reserved or Spot instances on the fly without any instance changes, which is useful for cost optimization.

  7. Security and compliance features:

    • EC2 supports encrypted root device volumes and Dedicated Instances, making it suitable for highly secure or regulated workloads.

The key features of Burstable Performance Instances (T-series) on AWS EC2 are:

  1. Baseline CPU Performance: Burstable instances provide a baseline level of CPU performance, which is designed to meet the needs of the majority of general-purpose workloads.

  2. Ability to Burst: These instances can burst above the baseline CPU performance when needed, allowing them to handle spikes in CPU utilization.

  3. CPU Credits: The baseline performance and ability to burst are governed by CPU credits. Each burstable instance continuously earns CPU credits when it stays below the CPU baseline, and consumes credits when it bursts above the baseline.

  4. Unlimited Mode: Burstable instances can operate in Unlimited mode, which allows the instance to sustain high CPU utilization for any period. In this mode, the hourly instance price automatically covers all CPU usage spikes if the average CPU utilization is at or below the baseline over a rolling 24-hour period.

  5. Cost-Effective: Burstable instances are generally more cost-effective than dedicated CPU instances (such as M or C families) for workloads that don't consistently require high CPU performance.

  6. Suitable Workloads: Burstable instances are well-suited for a broad range of general-purpose production workloads, such as web servers, small and medium databases, data logging, and development/test environments.


The key features of Compute Optimized Instances on AWS EC2 are:

  1. Designed for compute-intensive applications:

    • Compute optimized instances are designed to deliver high performance for applications that benefit from high-performance processors, such as batch processing, media transcoding, high-performance web servers, high-performance computing (HPC), scientific modelling, and machine learning inference.

  2. Powerful processors:

    • These instances are powered by the latest generation of Intel Xeon, AMD EPYC, or AWS Graviton processors, providing high clock speeds and advanced processor features.
    • For example, the C6i instances use 3rd generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.5 GHz.

  3. Optimized for performance:

    • Compute optimized instances are optimized for delivering high performance, with features like Intel AVX, Intel AVX2, and Intel Turbo Boost.
    • They also offer enhanced networking capabilities, with support for up to 50 Gbps of networking speed and 40 Gbps of bandwidth to Amazon Elastic Block Store.

  4. Flexible instance sizes:

    • Compute optimized instances are available in a range of instance sizes, from smaller instances with 2 vCPUs to larger instances with up to 128 vCPUs and 256 GiB of memory.
    • This allows you to choose the right instance size for your specific workload requirements.

  5. Use cases:

    • Compute optimized instances are well-suited for a variety of compute-intensive workloads, including:
      • Batch processing
      • Media transcoding
      • High-performance web servers
      • High-performance computing (HPC)
      • Scientific modeling
      • Dedicated gaming servers
      • Ad server engines
      • CPU-based machine learning inference

The key features of Memory Optimized Instances on AWS EC2 are:

  1. Designed for memory-intensive applications:

    • Memory-optimized instances are designed to deliver high performance for applications that require large amounts of memory, such as in-memory databases, real-time big data analytics, and other memory-intensive workloads.

  2. High memory capacity:

    • These instances offer a large amount of memory, ranging from 160 GiB to 488 GiB, depending on the instance type.
    • The R5 and R6g instances, for example, offer up to 488 GiB of memory.

  3. Powerful processors:

    • Memory-optimized instances are powered by the latest generation of Intel Xeon or AMD EPYC processors, providing high clock speeds and advanced processor features.

  4. Enhanced networking:

    • Memory-optimized instances support high-bandwidth networking, with up to 100 Gbps of aggregate network bandwidth using the Elastic Network Adapter (ENA) and Enhanced Networking.
    • This allows for low-latency, high-throughput network performance, which is important for memory-intensive workloads.

  5. EBS optimization:

    • Memory-optimized instances are EBS-optimized by default, providing dedicated bandwidth to Amazon Elastic Block Store (EBS) for fast, low-latency block storage access.

  6. Use cases:

    • Memory-optimized instances are well-suited for a variety of memory-intensive workloads, including:
      • In-memory databases (e.g., Redis, Memcached)
      • Real-time big data analytics
      • Distributed web-scale in-memory caching
      • High-performance computing (HPC)
      • Scientific computing
      • Memory-intensive enterprise applications


The key features of Storage Optimized Instances on AWS EC2 are:

  1. Designed for High I/O Workloads: Storage optimized instances are designed to deliver high, sequential read and write access to very large data sets on local storage. They are optimized to provide tens of thousands of low-latency, random I/O operations per second (IOPS) to applications.

  2. Local NVMe Storage: These instances use local NVMe (Non-Volatile Memory Express) storage, which provides ultra-low latency and high throughput for I/O-intensive workloads. The NVMe storage is directly attached to the instance, providing fast access to data.

  3. EBS Optimization: Storage-optimized instances are EBS-optimized by default, providing dedicated bandwidth to Amazon Elastic Block Store (EBS) for fast, low-latency block storage access.

  4. High Memory Capacity: These instances offer a large amount of memory, typically ranging from 32 GiB to 256 GiB, depending on the instance type. This helps maximize storage application throughput.

  5. Powerful Processors: Storage-optimized instances are powered by the latest generation of Intel Xeon or AMD EPYC processors, providing high clock speeds and advanced processor features.

  6. Use Cases: Storage-optimized instances are well-suited for workloads that require high, sequential read and write access to very large data sets, such as:

    • Transactional databases (e.g., Amazon DynamoDB, MySQL, PostgreSQL)
    • Real-time analytics (e.g., Apache Spark)
    • Data warehousing
    • Distributed file systems

The key features of Accelerated Computing Instances on AWS EC2 are:

  1. Hardware Acceleration: Accelerated Computing instances use hardware accelerators, or co-processors, to perform certain functions, such as floating-point number calculations, graphics processing, or data pattern matching, more efficiently than is possible in software running on CPUs.

  2. Instance Types:

    • GPU Compute Instances: Designed for general-purpose computing workloads that can benefit from GPU acceleration, such as machine learning, scientific computing, and high-performance computing.
    • GPU Graphics Instances: Optimized for graphics-intensive applications, such as game streaming, 3D visualization, and video encoding.
    • FPGA Instances: Provide programmable hardware acceleration for advanced scientific and engineering workloads, allowing you to customize the hardware to your specific needs.

  3. Powerful Processors: Accelerated Computing instances are powered by the latest generation of Intel Xeon or AMD EPYC processors, providing high clock speeds and advanced processor features.

  4. Enhanced Networking: These instances support high-bandwidth networking, with up to 100 Gbps of aggregate network bandwidth using the Elastic Network Adapter (ENA) and Enhanced Networking.

  5. EBS Optimization: Accelerated Computing instances are EBS-optimized by default, providing dedicated bandwidth to Amazon Elastic Block Store (EBS) for fast, low-latency block storage access.

  6. Use Cases:

    • Machine learning and deep learning training and inference
    • High-performance computing (HPC)
    • Scientific computing and simulations
    • 3D rendering and video encoding
    • Game streaming and virtual desktop infrastructure (VDI)

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