Aws part 4 → Types of EC2 instance in Detailed

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In last blog we discuss about the types of EC2 instance and its 1 types in detailed →Genral purpose instance

Here , we discuss all types of details →

1. General Purpose Instance →

3 series Available having different specifications

General Purpose Instances are a type of EC2 instance that is designed for a wide range of workloads, including web servers, small databases, and development and test environments. They provide a balance of compute, memory, and network resources, making them a good choice for many different use cases.

There are several types of General Purpose instances, each with its own specifications and highlights:

1. T4g instances — These instances are powered by AWS Graviton2 processors and provide a cost-effective option for workloads that don’t require a lot of compute power. They are good for small websites, development environments, and other lightweight workloads. Key highlights include:

• Up to 5 Gbps network bandwidth
• Up to 16 vCPUs and 64 GiB of memory
• Lowest cost option among all the instance types
• Good for running ARM-based applications

2. T3 instances — These instances are designed for general-purpose workloads that require a balance of compute, memory, and network resources. They are good for small to medium-sized databases, web servers, and other similar applications. Key highlights include:

• Up to 5 Gbps network bandwidth
• Up to 32 vCPUs and 96 GiB of memory
• Lowest cost option for burstable workloads
• Good for workloads that require occasional spikes in compute power

3. M6g instances — These instances are powered by AWS Graviton2 processors and provide a balance of compute, memory, and network resources. They are good for general-purpose workloads, such as web servers, small databases, and development environments. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 64 vCPUs and 256 GiB of memory
• Good performance for workloads that require a lot of memory
• Lower cost compared to other instance types with similar specifications

4. M5 instances — These instances are designed for general-purpose workloads that require a balance of compute, memory, and network resources. They are good for small to medium-sized databases, web servers, and other similar applications. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 96 vCPUs and 384 GiB of memory
• High performance for workloads that require a lot of compute power
• Good for running large-scale applications

Each of these General Purpose instance types has its own unique specifications and highlights, allowing you to choose the right instance type for your workload based on your specific requirements.

2. Compute Optimized Instance →

Compute Optimized Instances are a type of EC2 instance that is designed for workloads that require a lot of compute power. These instances are well-suited for high-performance computing, scientific modeling, and machine learning workloads that require a lot of CPU power.

There are several types of Compute Optimized instances, each with its own unique specifications and highlights:

1. C6g instances — These instances are powered by AWS Graviton2 processors and provide a balance of compute, memory, and network resources. They are good for workloads that require a lot of CPU power, such as machine learning, high-performance computing, and video encoding. Key highlights include:

• Up to 100 Gbps network bandwidth
• Up to 64 vCPUs and 256 GiB of memory
• Lower cost compared to other instance types with similar specifications
• Good for running ARM-based applications

2. C5 instances — These instances are designed for workloads that require a lot of CPU power, such as high-performance computing, scientific modeling, and machine learning. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 96 vCPUs and 384 GiB of memory
• High performance for workloads that require a lot of CPU power
• Good for running large-scale applications

3. C4 instances — These instances are designed for workloads that require a lot of CPU power, such as high-performance computing, scientific modeling, and machine learning. Key highlights include:

• Up to 10 Gbps network bandwidth
• Up to 36 vCPUs and 60 GiB of memory
• High performance for workloads that require a lot of CPU power
• Good for running large-scale applications

4. C3 instances — These instances are designed for workloads that require a lot of CPU power, such as high-performance computing, scientific modeling, and machine learning. Key highlights include:

• Up to 10 Gbps network bandwidth
• Up to 32 vCPUs and 60 GiB of memory
• High performance for workloads that require a lot of CPU power
• Good for running large-scale applications

Each of these Compute Optimized instance types provides a high amount of CPU power, making them well-suited for workloads that require a lot of processing power. By selecting the right Compute Optimized instance type for your workload, you can ensure that you have the necessary CPU power to run your application efficiently.

3. Memory Optimized Instance →

Memory Optimized Instances are a type of EC2 instance that is designed for workloads that require a lot of memory (RAM). These instances are well-suited for high-performance databases, in-memory analytics, and other memory-intensive workloads.

There are several types of Memory Optimized instances, each with its own unique specifications and highlights:

1. R6g instances — These instances are powered by AWS Graviton2 processors and provide a balance of compute and memory resources. They are good for workloads that require a lot of memory, such as in-memory databases and real-time big data processing. Key highlights include:

• Up to 100 Gbps network bandwidth
• Up to 64 vCPUs and 512 GiB of memory
• Lower cost compared to other instance types with similar specifications
• Good for running ARM-based applications

2. R5 instances — These instances are designed for workloads that require a lot of memory, such as in-memory databases and real-time big data processing. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 96 vCPUs and 768 GiB of memory
• High memory capacity for memory-intensive workloads
• Good for running large-scale databases

3. R4 instances — These instances are designed for workloads that require a lot of memory, such as in-memory databases and real-time big data processing. Key highlights include:

• Up to 10 Gbps network bandwidth
• Up to 64 vCPUs and 488 GiB of memory
• High memory capacity for memory-intensive workloads
• Good for running large-scale databases

4. X1 instances — These instances are designed for large-scale in-memory databases, such as SAP HANA, Apache Spark, and Cassandra. Key highlights include:

• Up to 10 Gbps network bandwidth
• Up to 128 vCPUs and 1,952 GiB of memory
• Highest memory capacity of any EC2 instance type
• Good for running very large-scale databases

Each of these Memory Optimized instance types provides a high amount of memory, making them well-suited for workloads that require a lot of memory. By selecting the right Memory Optimized instance type for your workload, you can ensure that you have the necessary memory to run your application efficiently.

4. Storage Optimized Instance →

Storage Optimized Instances are a type of EC2 instance that is designed for workloads that require high amounts of fast, sequential storage. These instances are well-suited for applications that require high levels of storage, such as big data analytics and data warehousing.

There are several types of Storage Optimized instances, each with its own unique specifications and highlights:

1. I3 instances — These instances are designed for workloads that require a lot of raw storage capacity, such as NoSQL databases and data warehouses. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 64 vCPUs and 15.2 TiB of NVMe SSD storage
• Low latency and high IOPS for fast storage performance
• Good for running large-scale databases

2. I3en instances — These instances are similar to I3 instances but offer higher storage capacity and more memory. They are well-suited for data warehousing, Hadoop, and other big data workloads. Key highlights include:

• Up to 100 Gbps network bandwidth
• Up to 96 vCPUs and 60.4 TiB of NVMe SSD storage
• High memory capacity for memory-intensive workloads
• Good for running very large-scale databases

3. D2 instances — These instances are designed for workloads that require a lot of sequential read and write access to very large datasets, such as Hadoop clusters and log processing. Key highlights include:

• Up to 10 Gbps network bandwidth
• Up to 48 vCPUs and 48 TiB of HDD storage
• High storage capacity for large-scale datasets
• Lower cost compared to other instance types with similar storage capacity

4. H1 instances — These instances are designed for workloads that require high throughput and large storage capacity, such as big data analytics and data warehousing. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 64 vCPUs and 16 TiB of HDD storage
• High storage capacity for large-scale datasets
• Lower cost compared to other instance types with similar storage capacity

Each of these Storage Optimized instance types provides a high amount of fast, sequential storage, making them well-suited for workloads that require high levels of storage. By selecting the right Storage Optimized instance type for your workload, you can ensure that you have the necessary storage capacity and performance to run your application efficiently.

5. Accelerated computing Instance →

Accelerated Computing Instances are a type of EC2 instance that is designed to provide high-performance computing capabilities for compute-intensive workloads. These instances are equipped with specialized hardware, such as GPUs, FPGAs, or TPUs, that can accelerate the processing of certain types of data.

There are several types of Accelerated Computing instances, each with its own unique specifications and highlights:

1. P3 instances — These instances are designed for compute-intensive workloads that require high-performance GPUs, such as deep learning and scientific simulations. Key highlights include:

• Up to 100 Gbps network bandwidth
• Up to 64 vCPUs and 8 NVIDIA V100 GPUs
• High-performance GPUs for fast processing of complex data
• Good for running deep learning models and scientific simulations

2.P4 instances — These instances are similar to P3 instances but offer higher GPU memory and more vCPUs. They are well-suited for machine learning training and inference workloads. Key highlights include:

• Up to 200 Gbps network bandwidth
• Up to 100 vCPUs and 8 NVIDIA A100 GPUs
• High GPU memory capacity for large-scale machine learning models
• Good for running machine learning training and inference workloads

3. G4 instances — These instances are designed for graphics-intensive workloads that require high-performance GPUs, such as gaming and virtual desktops. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 64 vCPUs and 1–8 NVIDIA T4 GPUs
• High-performance GPUs for fast graphics processing
• Good for running graphics-intensive applications, such as gaming and virtual desktops

4. Inf1 instances — These instances are designed for machine learning inference workloads that require low latency and high throughput. They are equipped with custom AWS Inferentia chips that can deliver high performance at a low cost. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 16 vCPUs and up to 16 AWS Inferentia chips
• Custom AWS Inferentia chips for high performance inference
• Good for running machine learning inference workloads at a low cost

Each of these Accelerated Computing instance types provides high-performance computing capabilities for compute-intensive workloads. By selecting the right Accelerated Computing instance type for your workload, you can ensure that you have the necessary computing power and performance to run your application efficiently.

6. High Memory Instance →

High Memory Instances are a type of EC2 instance that is designed to provide high memory capacity for memory-intensive workloads. These instances are equipped with a large amount of RAM that can support applications that require high memory usage.

There are several types of High Memory instances, each with its own unique specifications and highlights:

1. X1 instances — These instances are designed for large-scale, in-memory applications such as SAP HANA and Apache Spark. Key highlights include:

• Up to 100 Gbps network bandwidth
• Up to 128 vCPUs and up to 3.9 TB of RAM
• Large memory capacity for running in-memory applications at scale
• Good for running large-scale, in-memory applications

2. X1e instances — These instances are similar to X1 instances but offer higher memory capacity and faster networking. They are well-suited for large-scale, in-memory databases and analytics workloads. Key highlights include:

• Up to 100 Gbps network bandwidth
• Up to 128 vCPUs and up to 3.9 TB of RAM
• Large memory capacity and fast networking for running in-memory databases and analytics workloads
• Good for running large-scale, in-memory databases and analytics workloads

3. R5 instances — These instances are designed for memory-intensive workloads such as in-memory databases and real-time big data processing. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 96 vCPUs and up to 768 GB of RAM
• Good balance of compute and memory capacity for running memory-intensive workloads
• Good for running in-memory databases and real-time big data processing

4. R5a instances — These instances are similar to R5 instances but offer high memory density and are well-suited for memory-intensive workloads that require high memory density. Key highlights include:

• Up to 25 Gbps network bandwidth
• Up to 96 vCPUs and up to 768 GB of RAM
• High memory density for running memory-intensive workloads
• Good for running memory-intensive workloads that require high memory density

Each of these High Memory instance types provides high memory capacity for memory-intensive workloads. By selecting the right High Memory instance type for your workload, you can ensure that you have the necessary memory capacity to run your application efficiently.