With so many compute service offerings from Azure, it’s hard to know which one is the right candidate for your workloads—especially when you’re new to the cloud arena.
For a better understanding, let us get to know how enterprises designed their underlying infrastructure to host their applications before the existence of the public cloud.
Before the public cloud offerings, compute, storage, and network were the three main foundation blocks to deploy an application. The specialized core team for each layer was responsible for evaluating, designing, and purchasing the hardware components independently according to the company's set standards towards security and funding.
Let's focus on compute
‘Compute’ is not a typo for computer, nor does it mean to calculate something. In terms of enterprise infrastructure, compute refers to the hosting model for the computing resources that your application runs on.
Before the Virtualization era, for each application hosted, one or two physical servers were bought according to the application's criticality. Then comes the revolutionary Virtual Machines wherein we could create multiple virtual server instances in a single physical server to save the cost and environment by reducing the number of physical servers.
For many years, businesses didn’t have a choice—they would pick either the physical server or Virtual Machine for the compute layer based on their cost, manageability, and security standards to host their applications.
Why Azure compute services?
Comprehending the merits of Microsoft Azure's public cloud, companies are drastically migrating their workloads to Azure, which allows customers to deploy different flavors of compute instances quickly based on requirements.
With so many options in the rapidly changing public cloud offerings and limited digital transformation skills, companies are finding challenges in choosing the right Azure compute service to fit their workloads.
Choosing the right Azure compute service
To suppress the hurdle, use this decision tree to choose the right azure compute service for your solution.
Access the original diagram from Azure documentation here.
- “Lift and shift" is a strategy for migrating a workload to the cloud without redesigning the application or making code changes (this is also known as rehosting). If you lift and shift without re-architecting, you should reserve your compute instances to reduce cost whilst you look to rearchitect later, as you’re already aware of the resource utilization on your workloads.
- Cloud optimized is a strategy for migrating to the cloud by refactoring an application to take advantage of cloud-native features and capabilities.
The output from this flowchart is a starting point for consideration. Next, perform a more detailed evaluation of the service to see if it meets your needs. Choosing the right Azure compute services is important for long-term success in the cloud—plan your strategy out first, and then execute.