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Amazon EC2 Instance Types

5 minutes 5 Questions

Amazon EC2 provides a variety of instance types, optimized for different use cases. Instance types are grouped into families based on their general characteristics, such as memory, CPU, storage, network capacity, GPUs, and more. This enables customers to choose the best instance type for their workloads, considering factors like performance, cost, and resource requirements. Examples of instance type families include T2, M5, C5, R5, I3, G4, and P3.

Guide: Understanding Amazon EC2 Instance Types

Why it is important:
EC2 Instance Types are the backbone of AWS services and computing. Understanding EC2 Instance Types is crucial as it helps in effective resource allocation, cost optimization, and performance enhancement of AWS infrastructure.

What it is:
Amazon EC2 instance types define the hardware of the host computer for the instance. It consists of varying combinations of CPU, memory, storage, and networking capacity which are optimized to suit different use cases.

How it works:
Users can pick an appropriate instance type based on their workload requirements. A diverse range of instance types allows supporting different kinds of workloads- compute optimized, memory optimized, storage optimized, etc.

Exam Tips - Answering Questions on Amazon EC2 Instance Types:
1. Understand the different instance types and their suitable workloads.
2. Be familiar with the impact of instance types on costing.
3. Know how to choose the right EC2 instance types for various use-cases.
4. Study about optimization strategies for EC2 instances.

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AWS Certified Solutions Architect - Amazon EC2 Example Questions

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Question 1

A company needs to run a deep learning application that requires high-performance GPU acceleration. Which Amazon EC2 instance type should they choose for optimal performance?

Correct Answer: P3 instances, which are optimized for machine learning and HPC applications with NVIDIA Tesla V100 GPUs

For a deep learning application that requires high-performance GPU acceleration, the best choice among the given Amazon EC2 instance types is the P3 instances. P3 instances are specifically optimized for machine learning and high-performance computing (HPC) applications, and they are equipped with NVIDIA Tesla V100 GPUs, which provide the necessary GPU acceleration for deep learning workloads. The other instance types mentioned, such as C5 (compute-optimized), R5 (memory-optimized), and M5 (general-purpose), are not specifically designed for GPU-accelerated workloads and may not offer the optimal performance for the given deep learning application.

Question 2

A company needs instances optimized for large-scale, enterprise-class, in-memory applications such as SAP HANA. Which EC2 instance would be best suited for this type of workload?

Correct Answer: X1e

X1e instances are designed for large-scale, enterprise-class, in-memory applications as they provide up to 4 TB of memory . Other instance types cater to different use-cases: T2 (burstable general purpose), M5 (general purpose), P3 (GPU processing), C5 (compute optimized), and A1 (ARM-based workloads).

Question 3

A client requires low-cost instances for their batch processing workload that can tolerate interruptions. The workload is not time-critical and can be run during non-peak hours to minimize cost. Which purchasing option should they choose?

Correct Answer: Spot Instances

The client should choose Spot Instances for their batch processing workload that can tolerate interruptions. Spot Instances are ideal for this use case due to the following reasons: Spot Instances are available at a significantly lower cost compared to On-Demand Instances, which helps minimize the overall cost of running the workload. Since the workload is not time-critical and can be run during non-peak hours, the client can take advantage of the lower prices offered by Spot Instances during off-peak times. Spot Instances are suitable for workloads that can tolerate interruptions. If the Spot Instance is terminated by AWS due to price or capacity changes, the batch processing job can be resumed from the last checkpoint without causing significant issues. The other purchasing options are less suitable for this scenario: On-Demand Instances are more expensive and are best suited for workloads that require immediate and uninterrupted access to compute resources. Reserved Instances and Convertible Reserved Instances are not ideal for this use case because they require a long-term commitment and upfront payment, which may not be necessary for a workload that can be run during non-peak hours. Scheduled Instances are not as cost-effective as Spot Instances and are designed for workloads that require a specific schedule, which is not mentioned as a requirement in this case. Dedicated Instances are more expensive and are used when the client needs dedicated hardware for their instances, which is not a requirement for this batch processing workload. Therefore, Spot Instances provide the most cost-effective and suitable option for the client's batch processing workload that can tolerate interruptions and run during non-peak hours.

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