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[h1]Azure Compute & Storage Deep-Dive: The Next Step After Core Fundamentals[/h1]
In Part 1, we covered the building blocks of Azure: subscriptions, resource groups, regions, availability concepts, and the overall cloud model. Now it is time to move from the “what is Azure?” stage into the “how does Azure actually run and store applications?” stage.
This is where Azure Compute and Azure Storage become essential.
If Part 1 gave you the map, this blog gives you the engine room. These are the services that power web apps, virtual machines, containers, serverless workloads, backups, file shares, and application data across Azure. Microsoft’s own architecture guidance positions compute as the hosting model for your workloads, while Azure Storage is described as highly available, massively scalable, durable, and secure for cloud data workloads.
For interview preparation, this topic matters a lot because Azure compute and storage questions reveal whether a candidate can do more than define cloud terms. Interviewers want to know whether you can choose the right service, explain trade-offs, and connect architecture decisions to performance, cost, resilience, and security.
[h2]Why compute and storage matter so much in Azure[/h2]
Almost every Azure solution is built on two decisions:
First, where will the application run?
Second, where will the data live?
That is the compute-and-storage conversation in one line.
A company building a public website may choose Azure App Service. A team running legacy enterprise software may choose Azure Virtual Machines. A modern microservices platform may use AKS. An event-driven system might rely on Azure Functions. On the storage side, the same organization may use Blob Storage for files, Azure Files for shared access, Queue Storage for message buffering, and managed disks for VM persistence. Microsoft’s official service guidance presents these as distinct choices because each compute and storage option is optimized for a different workload shape.
That is exactly why interviewers ask deep-dive questions here: there is no single “best” Azure service. There is only the best fit for the scenario.
[h2]Azure Compute: the core hosting options you need to know[/h2]
Azure compute is the set of services that provide processing power for applications and workloads. Microsoft’s compute decision guidance highlights that Azure offers multiple hosting models, and choosing correctly depends on control needs, scaling style, operational overhead, and app architecture.
Here are the major compute services you should understand.
[h3]1. Azure Virtual Machines[/h3]
Azure Virtual Machines are the closest cloud equivalent to traditional servers. They give you full control over the operating system, installed software, networking, and configuration.
VMs are ideal when:
In interviews, the key point is this: VMs give maximum control, but they also create the most management responsibility. You patch the OS, monitor capacity, secure access, and handle scaling design yourself.
You should also know the resilience story around VMs. Azure supports availability sets to reduce correlated failures and separate VM instances across fault domains and update domains, which is especially useful in regions without availability zones. Azure also supports availability zones, and the official Azure reliability documentation tracks which services support zonal and zone-redundant deployment options.
A strong interview answer sounds like this:
[h3]2. Azure Virtual Machine Scale Sets[/h3]
Scale Sets extend the VM model for applications that need elasticity. Instead of manually managing individual servers, you define a set of identical VMs that can scale out or in.
This is especially useful for:
For interviews, the message is simple: Scale Sets bring automation and elasticity to VM-based architectures. They are a better fit than standalone VMs when you expect changing demand or need easier fleet management. Microsoft includes VM Scale Sets directly in the AZ-104 skill areas for Azure administrators, which tells you how central they are in real-world Azure operations.
[h3]3. Azure App Service[/h3]
Azure App Service is a platform-as-a-service option for hosting web apps, APIs, and backend services without managing the underlying servers directly.
This is often one of the easiest Azure compute services to explain in an interview:
Use App Service when the goal is to deploy web applications quickly with lower infrastructure overhead.
The trade-off is control. App Service is faster and simpler than VMs for many workloads, but it is not the right fit if you need deep OS customization or highly specialized infrastructure behavior.
[h3]4. Azure Functions[/h3]
Azure Functions is Microsoft’s serverless compute offering. According to Microsoft Learn, it lets you build event-driven applications with less infrastructure and lower operational overhead.
Functions are best when:
Examples include:
The interview-ready way to position Functions is this:
Use Azure Functions when you want event-driven execution and minimal infrastructure management.
One useful detail from Microsoft’s documentation: Azure Functions depends on a storage account, and that account must support Blob, Queue, and Table storage. Some storage account types do not support all of those capabilities.
That gives you a nice cross-link between compute and storage in one answer.
[h3]5. Containers, Azure Container Instances, and AKS[/h3]
Containers matter because they package an application and its dependencies into a portable unit.
Azure gives you multiple ways to run containers:
AKS is the heavy-hitter for enterprise containerized applications and microservices. Microsoft’s architecture guidance for AKS shows it as a strong fit for microservices, DevOps pipelines, and production-grade container orchestration.
A useful interview distinction is:
If the interviewer asks, “Why not always use AKS?” the best answer is that AKS gives more flexibility and control, but it also adds complexity. Not every application needs Kubernetes.
[h2]Azure Storage: the foundation of cloud data in Azure[/h2]
Azure Storage is Microsoft’s cloud storage platform for modern data workloads. Microsoft describes it as highly available, scalable, durable, and secure, with support for multiple data object types.
The first concept to understand is the storage account.
[h3]Storage accounts[/h3]
A storage account is the top-level Azure resource that contains your storage data services. Microsoft’s storage account overview explains that different account types support different features, pricing models, redundancy options, tiers, encryption, and endpoints.
In interviews, remember this idea:
The storage account is the management boundary for Azure Storage services.
It affects:
This is why choosing the right account type is not a small detail. It can affect architecture decisions later.
[h2]The main Azure Storage services[/h2]
[h3]1. Blob Storage[/h3]
Azure Blob Storage is for unstructured object data such as:
Blob Storage is one of the most common services in Azure because modern applications generate huge volumes of file-like data. It is also deeply tied to analytics, backup, archival, and application content delivery.
One major interview point is access tiers. Azure storage supports tiering so organizations can balance performance and cost based on how frequently data is accessed. This is a practical way to show commercial awareness in an interview: hot data costs more to keep instantly available, while colder data can be optimized for lower storage cost.
[h3]2. Azure Files[/h3]
Azure Files provides managed file shares in the cloud. This is useful when applications or users need shared file system access rather than object storage behavior.
Think of Azure Files as the answer when a business says:
“We still need a shared drive, but we want it in Azure.”
This makes Azure Files especially relevant in hybrid scenarios and migrations from traditional file servers.
[h3]3. Queue Storage[/h3]
Azure Queue Storage is designed for storing large numbers of messages for asynchronous processing. Microsoft states that queue messages can be up to 64 KB and that queues can contain millions of messages, up to the storage account capacity limit.
This is a great service to mention when discussing decoupled architectures.
For example:
That design improves resilience and smooths workload spikes.
[h3]4. Table Storage[/h3]
Table Storage stores large volumes of structured, non-relational data. It is useful when you need a key-value or schemaless design and do not need a full relational database engine.
It is less flashy than other Azure services, but interviewers like it because it shows whether you understand that not all data belongs in SQL.
[h3]5. Managed Disks[/h3]
Managed disks are persistent block storage volumes for Azure VMs. If Blob Storage is object storage and Azure Files is shared file storage, managed disks are the storage that keeps a VM’s operating system and attached data alive.
This matters because Azure VM performance and reliability are often tightly linked to disk choices. Microsoft’s policy and service guidance also references zonal, zone-aligned, and zone-redundant disk options in certain scenarios.
Interviewers may ask:
Even if you do not dive into every SKU, you should show that disk selection is part of workload design, not an afterthought.
[h2]Redundancy and resilience in Azure Storage[/h2]
One of the most important deep-dive topics is redundancy.
Azure Storage supports different redundancy strategies to help protect data against hardware failure, datacenter failure, and sometimes regional failure, depending on the option chosen. Microsoft’s storage account overview highlights redundancy as a core design choice in storage accounts.
In an interview, do not just say “Azure is resilient.” Say something more useful:
That kind of answer signals architecture thinking.
[h2]Choosing the right compute service: interview mindset[/h2]
A very common Azure interview question is: How do you choose between VMs, App Service, Functions, and AKS?
A strong answer is based on decision criteria, not memorized definitions.
You can frame it like this:
That answer works because it shows judgment, not just recall.
[h2]Choosing the right storage service: interview mindset[/h2]
The same logic applies to storage.
A good candidate also mentions cost, performance, access patterns, and resilience requirements.
[h2]Common mistakes candidates make[/h2]
This is where many interviews go sideways.
Candidates often:
The better answer always links the service choice to the scenario.
For example:
Bad answer:
“AKS is the best because Kubernetes is powerful.”
Better answer:
“I’d choose AKS if the application is containerized, needs orchestration, and the team is prepared to manage Kubernetes complexity. If the app is a simpler web application, App Service might reduce operational overhead.”
That is the difference between sounding technical and sounding employable.
[h2]Final thoughts[/h2]
Azure Compute and Storage are where cloud architecture becomes real. This is the layer where applications run, scale, persist data, recover from failure, and balance cost against performance.
If you are preparing for an Azure Cloud Engineer or Azure Administrator interview, this topic deserves serious attention. Learn the services, but more importantly, learn the decision logic behind them. Interviewers are not only testing whether you know what Azure Virtual Machines or Blob Storage are. They are testing whether you know when to use them, why to use them, and what trade-offs come with them.
That is what turns Azure knowledge into interview-ready confidence.
[h2]Conclusion[/h2]
Part 1 introduced the Azure foundation. This part takes you deeper into the services that do the real work. Once you understand compute and storage, you can begin thinking like an Azure engineer rather than just someone studying definitions.
In the next part, a natural continuation would be Azure networking and security, where these compute and storage services are protected, connected, and exposed to users safely. 
