5 Good Reasons to Migrate on Azure Public Cloud
Amazon and Microsoft have emerged as leaders in the public cloud computing space. As a result, many of us have Googled "AWS vs. Azure" or "Azure vs...Learn More
In this post, we’ll take a closer look at how AWS and Azure compare in these areas.
There’s no denying that AWS is currently the largest player in the public cloud space; AWS was first, and it offers a staggering depth and breadth in a dynamic platform.
Azure, long thought to be an ‘also ran’ or only appropriate for Microsoft-centered workloads, has become very competitive.
Take a look at this image from a recent Gartner report:
Azure is slightly behind AWS in the leader space. Microsoft has invested billions of dollars in making Azure competitive in this space, and clearly, it is paying off. Not only Gartner but also, cloud industry thought leaders such as David Linthicum of Cloud Technology Partners have begun taking notice (listen to this Doppler podcast episode on Azure’s market growth).
For technologists and IT decision makers (and anyone who controls the budget), this means that a commitment to either one of these platforms is a relationship with a technology-forward, market leading organization. (Read more about Gartner’s analysis in this ZDNet article.)
Cloud computing resources are primarily divided into three distinct categories: compute, storage, and database. Each category has its own performance-related concerns and best practices. There is, however, a right way and wrong way to ask about the performance differences between AWS and Azure.
The wrong question to ask is: Which cloud platform performs better? That’s the wrong question because performance outcomes depend on what services are in-use, what solutions have been built using those services, and how well (or poorly) you’ve architected those solutions.
The right question is to ask is: What are the differences between the key service components and how do you decide which tool is best for the job?
To learn more about the performance considerations for each platform, check out the following resources: Best Practices for Amazon RDS and “Performance best practices for SQL Server in Azure Virtual Machines. You can review Amazon storage classes here and those for Azure here.
Let’s take a closer look at AWS and Azure virtual machines with performance in mind.
The fundamental computational building block of AWS is EC2 (Elastic Compute Cloud). The corresponding Azure building block is the Azure Virtual Machine.
Both services offer Windows and Linux machine images. It’s important to understand the types of virtual machines and when to use them; this will help you intelligently design solutions by applying the correct resources to your goal.
Amazon provides a detailed description of each type and usage guidance (with scenarios) here. Note that each of these instance types has subtypes (for example, the T2 type ranges in size from “nano” to “2xlarge.”
Also, note that there isn’t a one-size-fits-all approach to using computing resources. Instead, there are a wide variety of instance types, each designed to optimize specific computing elements and meet different requirements to help you create a well-architected solution.
Amazon provides guidance to help you choose the right EC2 type in the article, “Choosing the Right EC2 Instance Type for Your Application.”
Like AWS EC2 machines, Azure virtual machines are divided into types, which are optimized for particular use cases.
Here’s a rundown of the different types:
Microsoft divides these machine types according to category:
Obviously, it isn’t enough to be familiar with the VM types (and the corresponding optimization categories). You also need guidance.
Fortunately, Microsoft has created a helpful concept called the Azure Compute Unit:
“We have created the concept of the Azure Compute Unit (ACU) to provide a way of comparing compute (CPU) performance across Azure SKUs. This will help you easily identify which SKU is most likely to satisfy your performance needs. ACU is currently standardized on a Small (Standard_A1) VM being 100 and all other SKUs then represent approximately how much faster that SKU can run a standard benchmark.”
Read the full documentation at “Overview of the Azure Compute Unit.”
More guidance can be found in Lee Stott’s excellent article, “Choosing the most appropriate Azure Virtual Machine Specification.”
Both Microsoft and Amazon offer serverless platforms that enable you to run code without the need to create, provision, or manage the VMs we reviewed above. The virtual machines detailed comprise these serverless solutions but they’re abstracted as a service.
Serverless computing changes your focus from infrastructure to the code that runs on whatever infrastructure is appropriate. Amazon’s serverless computing platform is called Lambda. Azure Functions is Microsoft’s serverless solution.
Serverless is a software and therefore, a developer-centric model of computing; performance considerations are correspondingly centered on the needs of the code running on the solution and not the infrastructure.
Key considerations include:
A deeper exploration of performance optimization on Azure Functions and Lambda is well beyond this post’s scope, so I will direct the reader to these high-quality references:
Azure Functions Overview
AWS Lambda Overview
Measuring cloud platform performance isn’t as simple as, for example, comparing one service’s VM type or serverless offering against its competitor. Architecture and applying the right tools to the right workload use case are key for optimizing performance.
For a deeper consideration of this topic, I suggest consulting Microsoft’s “Azure Solution Architectures” and Amazon’s “AWS Architecture Center.”
For technologists, AWS and Azure provide exciting opportunities to design and implement solutions using computing resources in new, interesting, and dynamic ways.
Amid the reality (and hype) for these new opportunities, it’s important to understand that there’s an ongoing (and for many IT shops, unfamiliar) responsibility to actively monitor and control your cloud-related costs (for an excellent overview of cloud economics, see this Cloud Technology Partners article, “Cloud Economics – Are You Getting the Bigger Picture?”
I’ve seen cloud projects go terribly awry because cost control was not considered a critical task from the start, so don’t take this area for granted.
On AWS, cost controls are available from a collection of built-in tools centered on the Billing and Cost Management dashboard. The dashboard provides information about the following:
– Spend Summary
– Month-to-Date Spend by Service
– Month-to-Date Top Services by Spend
Additional guidance is available in the Amazon article, “Avoiding Unexpected Charges.”
Azure resources are organized around subscriptions (AWS resources are organized around accounts). Azure billing information is gathered from the resources created and consumed within individual subscriptions.
Just as there can be many AWS accounts, there can also be different subscriptions associated with an Azure AD instance (for more information about this see, “How Azure subscriptions are associated with Azure Active Directory“).
Azure’s built-in cost management tools can be labor intensive. You can review Microsoft’s guide to Azure billing at this article on Monitoring Usage and Costs.
Considering the amount of work required to track your Azure spend, luckily you can configure automated billing alerts, which is described here. Even more fortunate is the news that Microsoft recently acquired Cloudyn.
Cloudyn, which is often recommended by Microsoft cloud architects, is a fully featured cloud management and cost monitoring tool. No doubt, Cloudyn’s capabilities will eventually be streamlined into Azure, and we can soon expect simplification of Azure’s cost control toolset.
Last, but certainly not least in our comparative tour, let’s take a look at monitoring.
Here’s how Amazon describes Cloudwatch:
“Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS. You can use Amazon CloudWatch to collect and track metrics, collect and monitor log files, set alarms, and automatically react to changes in your AWS resources.”
The full description is here.
And, for an overview of everything you can monitor with Cloudwatch, go to the “Amazon CloudWatch Metrics and Dimensions Reference” article.
Here’s how Microsoft describes Azure Monitor:
“Azure Monitor is the platform service that provides a single source for monitoring Azure resources. With Azure Monitor, you can visualize, query, route, archive, and take action on the metrics and logs coming from resources in Azure. You can work with this data using the Monitor portal blade, Monitor PowerShell Cmdlets, Cross-Platform CLI, or Azure Monitor REST APIs. In this article, we walk through a few of the key components of Azure Monitor, using the portal for demonstration.”
The full description is here.
For an overview of Azure Monitor metrics (i.e., what it helps you track), consult the documentation here.
Both Microsoft’s Azure and Amazon’s AWS are powerful, dynamic cloud platforms; you can accomplish remarkable things with either offering.
To choose the right solution, don’t ask yourself, ‘which platform is better’ or faster or some other simplistic measure. Focus instead on understanding the following:
By keeping these items top of mind, you’ll increase your odds of a successful cloud project and create the foundation for a solid cloud strategy.
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