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Virtual machines: Compute options on AWS

If you want to build and deploy applications in the cloud, it all starts with compute.

The benefits of outsourcing your compute clout to a major cloud vendor are near-endless, but in short, the agility, speed, and potential cost reductions that cloud computing power can bring allow a business to concentrate on innovating instead of worrying about hardware and infrastructure.

Utilizing cloud-based compute services means that your big processing “brain” is centralized, able to grow infinitely without additional hardware investment, and benefits from all the muscle enterprise-grade servers.

Taking advantage of some variety of virtualization means businesses can develop and run their software in a scalable, highly-available, and secure production environment.

As the world’s biggest cloud vendor, it should come as no surprise that AWS offers a range of compute types for a wide variety of use cases.

Compute types

So with options like virtual server hosting, container management, and serverless computing on the table, how do you choose the right one?

The first step is understanding the difference between the main compute types.

What is a virtual machine?

• A virtual machine, or VM for brevity, does what it says on the tin: it imitates a real, physical computer in that it can run apps and programs, but without having using any actual hardware.
• A VM is often called an “image,” and behaves like a tangible computer. A VM runs on top of a hypervisor, which itself runs on either a host machine or a “bare-metal” host.
• Because they’re a quarantined environment, VMs are perfect for testing, accessing infected data, creating backups, and trying out app compatibility on different operating systems.
• Unlike traditional operating systems, a hypervisor enables multiple “computers” to run on the same physical platform.
• A hypervisor also manages all the underlying virtual infrastructure—like the CPU, memory, hard drive, and network interface—of the numerous VMs running on it.
• Every VM has its own virtual hardware, like CPUs, memory, hard drives, and network interfaces. You need a significant amount of processing power to run VMs, as you’re essentially operating multiple “computers” at once.
• For this reason, most organizations that use VMs host them on the servers of major cloud vendors like AWS.
• Using VMs means you can consolidate applications onto a single server, even if they run on different operating systems.
• This can cause issues, however, with each VM having its own OS, you can run up significant overheads in terms of resource throughout the development lifecycle.

What is a container?

• Containers are also a type of virtualized compute but are slightly different from VMs in that they’re (wait for it) more self-contained.
• A Linux-based, standardized unit that holds everything you need to run a piece of software, a container rolls up the code, configurations, and dependencies that an app needs so that it can be dropped and run anywhere.
• Because they’re boxed up into a single package, containers are quick to start up and stop, and easy to move between environments.
• You can quickly shift your containerized app between a sandbox to a staging environment to live production, or from a physical machine to the cloud, safe in the knowledge that the program will run reliably and consistently.
• Unlike VMs, containers share the host’s operating system with other containers, making them smaller and allowing more workloads to be run on a single OS. Containers also use fewer resources than VMs.
• Though both options provide an environment to deploy, manage, and scale applications, containers can do it in a more streamlined way.
• We asked Trevor Sullivan, a software professional with more than 15 years of industry experience, to break down the key differences in performance between a VM and a container.
• “A container doesn’t have its own kernel, and performs isolation at the process level, instead of at the hardware level,” explains Trevor
• “Containers provide an additional layer of isolation on top of virtual machines, which means you can scale up applications on fewer VMs, on the same hardware. By utilizing fewer VMs, you have less management and monitoring overhead of your total infrastructure.”

What is serverless computing?

• Serverless computing, despite the name, doesn’t mean there are no servers involved at it; it just means you don’t have to worry about them at your end.
• Serverless allows you to write and configure an app, and then upload this parcel of code to a cloud server, usually one operated by a large cloud vendor like AWS or Microsoft. The cloud vendor then charges you based on the amount of time each app runs on its servers.
• Using serverless platforms means developers don’t have to think about having the right amount of bandwidth or servers to deploy their apps; all of this back-end admin is taken care of by the vendor, with your compute footprint automatically scaled to meet the needs of your app.
• Each of these compute types are available on AWS. Here’s a rundown of the virtualization, container, and serverless products that AWS offers on its platform.

Virtualization on AWS

Amazon EC2

• Amazon EC2 is the most popular of AWS’s mammoth stable of services. EC2 gives organizations access to a range of virtual computing environments—known as instances—with different compute, memory, storage, and network capabilities, that can be scaled up and down as needed.
• With Amazon EC2, you can launch as many or as few of these instances as you require, and retain full control over security, storage, and networking configurations. You can also opt to use preconfigured instance templates called Amazon Machine Images (AMIs).
• Amazon EC2 offers instances optimized for a range of use cases, including high-performance computing, real-time big data analytics, machine learning, and data warehousing.
• Using EC2 means that you are responsible for allocating capacity, monitoring performance, and designing for fault tolerance and scalability.

VMware Cloud on AWS

• VMware Cloud on AWS is an integrated cloud offering, developed in partnership between AWS and VMware.
• It’s a highly scalable and secure service that allows organizations to migrate or expand their on-premises VMware vSphere-based environments to the AWS Cloud.
• Running on Amazon EC2 bare metal infrastructure, it’s an ideal solution for organizations executing vSphere-based workloads internally, who want to migrate these workloads to the cloud or extend their data center capacities.

AWS Firecracker

• AWS Firecracker is a newcomer to the field that enables users to create micro VMs. An extremely efficient, open-source compute option, AWS itself uses Firecracker to run its Lambda service. Right now, no other cloud provider has anything similar.

• Its flexibility is another factor that Trevor believes makes it appealing to users: “Firecracker is not bound to AWS, so you can actually use it to run VMs on your own hardware, such as a development laptop, bare metal server, or customer-owned hardware in a co-location data center.

• “The flexibility to run Firecracker inside or outside AWS makes it easy to perform development work wherever your team is most comfortable, and then deploy to a heterogeneous cloud and non-cloud environment.”