How to Choose a Compute Option on AWS

One of the most important decisions that you have to make when building your applications on AWS is how to run your code. AWS offers a variety of compute options that cater to different needs and preferences. But how do you choose the right one for your use case?

In this blog post, we will explore the three main types of compute options on AWS: virtual machines, container services, and serverless functions. We will compare their features, benefits, drawbacks, and scenarios where they are most suitable.

Virtual Machines

A virtual machine (VM) is a software emulation of a physical computer that runs an operating system and applications. On AWS, you can use Amazon Elastic Compute Cloud (EC2) to launch VMs with different configurations of CPU, memory, storage, network, and security.

Some of the advantages of using VMs are:

• You have full control over your infrastructure and can customize it according to your needs
• You can leverage existing skills and tools that work with VMs
• You can run any type of application or workload that requires specific operating systems or software packages

Some of the drawbacks of using VMs are:

• You have to manage the underlying infrastructure such as patching, scaling, backup, etc.
• You have to pay for the resources that you provision even if they are not fully utilized
• You have to deal with potential performance issues such as boot time or latency

Some scenarios where VMs are ideal are:

• You need to run legacy applications that cannot be easily migrated or refactored
• You need to run complex or specialized workloads that require fine-grained control over your environment
• You need to comply with certain regulations or standards that require specific configurations or settings

Container Services

A container is a lightweight package of code and dependencies that can run anywhere without requiring a separate operating system. On AWS,
you can use Amazon Elastic Container Service (ECS)^[2]^ or Amazon Elastic Kubernetes Service (EKS)
to run your containers on clusters of EC2 instances or on AWS Fargate^[3]^ , which is a serverless platform for containers.

Some of the advantages of using container services are:

• You can improve portability and consistency across different environments by packaging your code and dependencies together
• You can increase efficiency and utilization by running multiple containers on the same host without wasting resources
• You can simplify deployment and scaling by using orchestration tools such as ECS or EKS

Some of the drawbacks of using container services are:

• You still have to manage some aspects of your infrastructure such as networking, security groups, load balancing, etc.
• You still have to pay for the resources that you provision even if they are not fully utilized unless you use Fargate
• You still have to deal with potential performance issues such as cold starts or latency

Some scenarios where container services are ideal are:

• You want to adopt a microservices architecture where each service runs in its own container
• You want to leverage existing skills and tools that work with containers such as Docker or Kubernetes
• You want to migrate existing applications from other platforms without changing much code

Serverless Functions

A serverless function is a piece of code that runs in response to an event such as an HTTP request, a message from a queue, a change in a database.

On AWS, you can use AWS Lambda to run your serverless functions without provisioning any servers.

Some of the advantages of using serverless functions are:

• You only pay for the resources that you consume when your code runs
• You don’t have to worry about managing any infrastructure such as scaling, patching, backup, etc.
• You can easily integrate with other AWS services and third-party APIs

Some of the drawbacks of using serverless functions are:

• You have to adhere to certain limitations such as memory size, execution time, concurrency.
• You have to deal with potential performance issues such as cold starts or latency
• You have to refactor your code to fit into small and stateless functions

Some scenarios where serverless functions are ideal are:

• You want to build event-driven applications that react to changes in data or user behavior
• You want to create simple and scalable APIs or microservices that don’t require complex logic or state
• You want to perform short-lived and asynchronous tasks such as image processing or data transformation

Conclusion

As you can see, there is no one-size-fits-all solution when it comes to choosing a compute option on AWS. Each option has its own pros and cons, and you have to consider factors such as cost, performance, scalability, flexibility, and complexity.
The best way to decide is to understand your requirements and use cases, and then experiment with different options until you find the one that works best for you. If you need help with choosing a compute option on AWS, you can use AWS Compute Optimizer, which is a service that recommends optimal AWS compute resources for your workloads based on performance and cost data.
Please let us know if you have any feedback or suggestions.
Thank you for reading. 😊