Nitin Chaudhari’s Post

What are Types of Instances in EC2..? In Amazon Elastic Compute Cloud (EC2) on AWS, there are several types of instances, each designed for different use cases. Some common types include: 1. General Purpose Instances (e.g., t4g, t3, t3a, t2):Balanced CPU, memory, and networking resources. Suitable for a variety of diverse workloads. 2. Compute Optimized Instances (e.g., c7g, c6g, c5, c5a, c5n): Ideal for compute-bound applications that benefit from high-performance processors. 3. Memory Optimized Instances (e.g., r7g, r6g, r5, r5a, u4gim): Designed to deliver fast performance for workloads that process large data sets in memory. 4. Storage Optimized Instances (e.g., i3, i3en, h1): Built for workloads that require high, sequential read and write access to very large data sets on local storage. 5. Accelerated Computing Instances (e.g., p4, inf1, f1, g4dn): Equipped with specialized hardware (GPUs, FPGAs) to perform functions such as graphics processing, machine learning inference, or data pattern matching more efficiently. Each instance type comes with different specifications, including vCPUs, memory, storage, and networking capacity. The choice of instance type depends on the specific requirements of your applications and workloads.

types of ec2 Instances are :- Amazon Elastic Compute Cloud (EC2) offers a variety of instance types, each designed for different use cases. Here are some common types: 1. General Purpose Instances:- -> t3, t4g, t3a:-Balanced compute, memory, and networking resources. Suitable for diverse applications. 2. Compute Optimized Instances:- ->c6g, c5, c5n:- High-performance processors, ideal for compute-bound applications that benefit from high CPU power. 3. Memory Optimized Instances:- - r6g, r5, r5n, u4g:- Designed to deliver fast performance for workloads that process large data sets in memory. 4. Storage Optimized Instances:- - i3, i3en, d2, h1:-Optimized for high, sequential read and write access to very large data sets on local storage. 5. Accelerated Computing Instances:- - p4, p3, inf1, f1:-Include specialized hardware, like GPUs or FPGAs, for tasks such as machine learning, graphics processing, or high-performance computing. 6. Bare Metal Instances:- - i3, i3en, m5zn, u-6tb1.metal:- Provide access to the underlying physical hardware for applications that benefit from bare-metal performance. Each instance type comes with different combinations of CPU, memory, storage, and networking capacity to meet the needs of diverse workloads. Choose the type that aligns best with your specific application requirements.

HPC coverage with AMD EPYC processors in AWS has expanded yet again! Leverage AMD powered instances for the highest performance x86 compute in AWS. Amazon EC2 Hpc7a instances are now available in Stockholm Region and Hpc6a instances are available in Sydney Region.

Leveraging scalable compute capacity in the cloud to boost performance, flexibility, and cost-efficiency. EC2 is a game-changer for deploying applications seamlessly. The types of Amazon EC2 include: General Purpose Instances (A, T, M, and T3): Balanced compute, memory, and networking resources, suitable for a variety of diverse workloads. Compute Optimized Instances (C): Ideal for compute-bound applications that require high-performance processors. Memory Optimized Instances (R, X, U, and Z): Designed to deliver fast performance for workloads that process large data sets in memory. Storage Optimized Instances (I, D, H, and I3): Geared towards workloads that demand high, sequential read and write access to very large data sets on local storage. Accelerated Computing Instances (P, F, and G): Equipped with specialized hardware (GPUs or FPGAs) to accelerate specific workloads such as machine learning or graphics processing. Selecting the right instance type ensures optimal performance for your specific application and workload. 💻🔧

More performance, more wins!! Amazon #EC2 instances deliver 50% higher performance compared to the previous gen of instances—making them ideal for demanding applications. Amazon Web Services (AWS) #technology #infrastructure #informationtechnology #informationtechnology #processors #computing #AWS #Compute https://lnkd.in/dP8SM-NG

Excited to share our latest innovation - Google Compute Engine’s N4 and C4 VMs 🚀 Designed to maximize performance and optimize spend for all your general-purpose workloads. Olivia Melendez and I break down the details in our latest blog post – don't miss it! #google #cloud #compute #infrastructure #GoogleCloudNext https://lnkd.in/gDk3TeF9 

New OS tools allow running HPC codes on EC2 Spot with minimal impact from interruptions. The tools provide checkpointing to enable using spot instances. #aws #awscloud #cloud #compute #highperformancecomputing #ec2 #ec2spot #elasticfabricadapter #hpc #molecularmodeling #researchcomputing #scientificcomputing #simulations

Cost Optimization everywhere. Andy highlight it in his "Letter to Shareholders" https://lnkd.in/dchJag3d Andy says: "Shifting to AWS, we started 2023 seeing substantial cost optimization, with most companies trying to save money in an uncertain economy. Much of this optimization was catalyzed by AWS helping customers use the cloud more efficiently and leverage more powerful, price-performant AWS capabilities like Graviton chips (our generalized CPU chips that provide up to ~40% better price-performance than other leading x86 processors)", the past year was also a significant delivery year for AWS. We announced our next generation of generalized CPU chips (Graviton4), which provides up to 30% better compute performance and 75% more memory bandwidth than its already-leading predecessor (Graviton3)." Here you have further info about AWS Graviton4-based Amazon EC2 R8g Instances Preview: https://lnkd.in/dRbXjYgX #aws #ec2 #graviton #cloud #sustainability

⏺️Hey Folks! Let's have a look at the key components of virtualization among Azure, AWS and GCP🧐 👉 ## Key Components of Virtualization across Azure, AWS, and GCP: 1. Hypervisor: 💡Acts as the core foundation, dividing physical hardware into multiple virtual machines (VMs). 💡 Ensures resource isolation, security, and efficient usage. ⚡Azure: Hyper-V (Type 1) or Azure Fabric Controller (Type 2) ⚡AWS: Nitro System (custom-built for VMs) ⚡GCP: KVM (Kernel-based Virtual Machine) 2. Virtual Machines (VMs): 💡Emulated computers running their own operating system and software. 💡Offer flexibility, portability, and scalability. ⚡Azure: Virtual Machines (VMs) ⚡AWS: Amazon Elastic Compute Cloud (EC2) instances ⚡GCP: Compute Engine VMs 3. Virtual Networks: 💡Provide isolated logical networks for VMs to communicate securely. 💡Offer segmentation and control over network traffic. ⚡Azure: Virtual Network (VNet) ⚡AWS: Amazon Virtual Private Cloud (VPC) ⚡GCP: Cloud VPN and Cloud Nat 4. Virtual Storage: 💡Provides flexible and scalable storage options for VMs. 💡Includes options like block, file, and object storage. ⚡Azure: Azure Storage (Managed Disks, Blobs, Files) ⚡AWS: Amazon Elastic Block Store (EBS) and Simple Storage Service (S3) ⚡GCP: Cloud Storage (Persistent Disks, Cloud Filestore, Cloud SQL) 5. Management Tools: 💡Offer control and orchestration of virtualized resources. 💡Allow provisioning, deployment, monitoring, and scaling of VMs and other components. ⚡Azure: Azure Resource Manager (ARM), Azure Portal ⚡AWS: AWS Management Console, CloudFormation ⚡GCP: Cloud Console, Cloud Deployment Manager #azure #aws #gcp #virtualization stay tuned for more info :- https://lnkd.in/gAmfAEuY