Selecting the appropriate compute platform

What factors should be considered when choosing an EC2 instance type for a compute-heavy workload?

When choosing an EC2 instance type for compute-heavy workloads, one should consider the following factors: CPU performance, whether the workload can leverage Vector Processing (AVX), memory-to-CPU ratio, network bandwidth, and whether the instance type supports Enhanced Networking or Elastic Fabric Adapter (EFA) for high-performance computing. Additionally, it’s essential to consider the cost and whether the workload is consistent or would benefit from Spot Instances.

How would you choose between deploying on EC2, ECS, EKS, and Lambda?

The choice between EC2, ECS, EKS, and Lambda depends on the specific requirements of the application. EC2 provides the most control and is suitable for traditional applications. ECS is optimal for containerized applications that require orchestration without managing the infrastructure. EKS is ideal for Kubernetes-based applications. Lambda is best for event-driven, short-duration workloads as it abstracts all infrastructure management and scaling.

Can you explain what AWS Fargate is and why you might choose it over other compute options?

AWS Fargate is a serverless compute engine for containers. It works with both Amazon ECS and EKS, allowing users to run containers without managing servers or clusters. Fargate is chosen for its simplicity, as it automatically manages the underlying infrastructure, scaling, and scheduling of containers, which is ideal for workloads where infrastructure management is not desired.

When would you recommend using AWS Elastic Beanstalk over other compute services?

AWS Elastic Beanstalk is recommended for developers who want to deploy and manage web applications and services quickly and without worrying about the underlying infrastructure. It automatically handles deployment, from capacity provisioning and load balancing to auto-scaling and application health monitoring. It’s ideal when ease of use and quick deployment are prioritized over granular control.

What are some indicators that AWS Batch would be the most appropriate compute platform for a workload?

AWS Batch is most appropriate when dealing with batch processing workloads, which involve running a series of jobs, typically on a large scale. Use cases include data processing, batch file processing, and running compute jobs as part of a larger workflow or pipeline. AWS Batch is chosen for its efficiency in provisioning resources, job scheduling, and ability to optimize costs through Spot Instances or On-Demand pricing.

Explain when you would advise using Spot Instances and the risks associated with them.

Spot Instances should be used for fault-tolerant, flexible workloads that can handle interruptions, such as batch processing, stateless web services, and background tasks. The primary risks associated with Spot Instances are interruptions due to price changes or capacity availability, which can result in workloads being stopped prematurely. It is essential to have a strategy for checkpointing and saving work, or quickly moving workloads to other instances, to mitigate these risks.

For a customer looking to modernize their monolithic legacy application, what AWS compute options would you recommend?

For modernizing a legacy monolithic application, AWS offers several paths. If the customer is aiming for minimal changes, they might choose to lift and shift to EC If they are ready to containerize, AWS ECS or EKS with AWS Fargate would be suitable to manage container orchestration without the need for infrastructure management. For breaking the application into microservices, AWS Lambda can be used for event-driven components, allowing for greater scalability and cost savings.

What use cases are best suited for AWS serverless architectures, and why would you choose AWS Lambda for compute?

AWS serverless architectures are best suited for event-driven applications, web APIs, mobile backends, data processing tasks, and automation scripts. AWS Lambda is particularly suitable for short-duration, event-driven workloads because it manages the infrastructure, scaling, and provisioning automatically, allowing developers to focus on the code. It is also cost-effective since you pay only for the compute time you consume.

Discuss the benefits of using EC2 Auto Scaling and how it can impact the selection of the appropriate compute platform.

EC2 Auto Scaling benefits include the ability to maintain application availability by automatically adjusting the number of EC2 instances based on demand, improving fault tolerance, and optimizing costs by terminating unnecessary instances. Its impact on selecting the appropriate compute platform is significant as it offers a powerful solution for workloads with variable usage patterns, making EC2 a viable option for such scenarios.

When would you recommend using AWS Lightsail over EC2 instances?

AWS Lightsail is recommended for small businesses or individuals who need a simple virtual private server (VPS) solution with easy-to-understand pricing and simple setup. It’s ideal for simpler workloads such as small web applications, websites, and personal projects. EC2 is recommended for more complex applications requiring detailed configuration, scaling options, and access to a broader range of EC2 features.

How can AWS Outposts be beneficial in selecting a compute platform, and in what scenarios might it be necessary?

AWS Outposts is beneficial for workloads that require low latency access to on-premises systems, local data processing, or data residency requirements. It extends AWS infrastructure, services, APIs, and tools to virtually any data center, co-location space, or on-premises facility. It’s necessary in scenarios where compliance regulations mandate data to remain on-premises or where connectivity to the cloud is limited.

What considerations should be made when selecting between Provisioned, On-Demand, and Reserved Instances in AWS?

When selecting among Provisioned, On-Demand, and Reserved Instances, one must consider the following:
– Provisioned Instances (as in Provisioned IOPS for storage) are chosen for mission-critical applications that require consistent I/O performance.
– On-Demand Instances are suitable for short-term, irregular workloads with no upfront commitment.
– Reserved Instances are ideal for long-term workloads with predictable usage, offering significant cost savings over on-demand pricing. Consider the commitment period (1 or 3 years), payment options (No Upfront, Partial Upfront, All Upfront), and whether Standard or Convertible Reserved Instances best meet your flexibility needs.