Microsoft Azure: Everything You Need to Know About the Microsoft Cloud Computing Platform
What is Azure?
What is Microsoft Azure used for? Microsoft Azure, or simply Azure, is Microsoft’s cloud computing platform and service that provides a wide range of cloud services, including platform, infrastructure, and software as a service.
What is Azure Used For?
Organizations of various sizes use Microsoft Azure to host websites, analyze data, conduct disaster recovery, and develop software—among other applications.
Azure Infrastructure as a Service (Azure IaaS). Azure IaaS is one of several tiers of service. With Azure IaaS, users can run and manage computing resources through the Azure Virtual Desktop interface.
Platform as a Service (PaaS). The PaaS model supports and maintains tools, programming languages, frameworks, and infrastructure.
Azure storage and databases. Solutions such as Azure Storage Explorer backup and store data using an SaaS model.
Machine learning (ML) and artificial intelligence (AI). Azure ML and AI tools and cognitive services include data models, image recognition, and natural language processing.
Internet of Things (IoT). The Azure IoT Hub allows monitoring and analysis of IoT sensor and device data.
DevOps and application lifecycle management. Azure DevOps provides tools and services for automating software development processes, such as code repositories and build pipelines.
Security and identity services. Microsoft Azure features robust security services across mobile devices, such as Azure Active Directory for identity and access management, as well as features for threat protection and compliance.
Azure Content Delivery Networks (CDN). Azure CDN improves performance and scalability of websites and applications by distributing content to edge locations across regions.
Hybrid cloud solutions. Azure integrates on-premises data centers with the cloud to produce hybrid cloud environments organizations may access for increased flexibility and scalability.
Containers and Kubernetes. Azure provides container orchestration with Azure Kubernetes Service (AKS) and supports containerization using Docker.
Networking. Azure offers various services like Azure Virtual Network, load balancers, VPN Gateway, and ExpressRoute for creating and managing network resources in the cloud.
Serverless computing. Azure Functions is a serverless computing service that lets users run event-driven code without infrastructure.
Azure Infrastructure Explained
What does Azure do to ensure data security, availability, and reliability? Azure global infrastructure is built on a global network of data centers and resources categorized in several ways:
Data centers. Azure operates multiple data centers across regions worldwide.
Regions. Azure is organized into geographic regions, each containing one or more data centers designed to be independent, with its own power, cooling, and networking capabilities. Users choose the region in which they want to deploy their resources, based on factors like data residency, compliance requirements, and proximity to end-users.
Availability zones. Azure regions are often divided into Availability Zones, isolated data center locations with their own power, cooling, and networking to provide redundancy and fault tolerance for added high availability and resilience.
Edge locations. The Azure network of edge locations is composed of geographically distributed points of presence around the world that are part of the content delivery networks. Azure edge locations help accelerate content delivery, reduce latency, and improve user experience for web applications and media streaming.
Network infrastructure. High-speed, redundant, software-defined networking (SDN) connections between data centers and regions provide flexibility and control over infrastructure configurations.
Content delivery network (CDN). Azure CDN service caches and delivers content close to end-users via edge locations. This reduces latency and enhances the performance of web applications and media delivery.
Azure availability sets. Availability sets allow users to group VMs to provide fault tolerance and ensure availability even if there is a failure within the data center or region.
Azure resource manager. This is the management layer that provides resource deployment, management, and monitoring capabilities.
Azure Infrastructure as Code (IaC). IaC is the methodology and practice of using code and automation to manage and provision Microsoft Azure infrastructure and resources. In other words, rather than configuring resources through the Azure Portal or command-line interfaces manually, IaC allows users to define Azure infrastructure and services as code. This approach has several benefits, including improved efficiency, scalability, and consistency via the ability to version, test, and deploy Microsoft Azure infrastructure in a consistent and repeatable manner.
Azure Products and Services
Microsoft Azure products and services are typical of other enterprise-scale cloud platforms. Azure features deliver the standard benefits of a cloud platform for businesses: scale and flexibility without the need to manage physical hardware.
Parallel architecture. Unlike the design of traditional central processing units (CPUs, see “GPU vs CPU” discussion below), GPU design involves a massive number of smaller processing units (cores) that can handle tasks in parallel—tasks that can be divided into many smaller subtasks to be processed simultaneously.
Data and task parallelism. GPUs excel at both data parallelism (performing the same operation on multiple data elements simultaneously) and task parallelism (performing different operations on different sets of data simultaneously.
Thread execution. Threads, small units of work that allow concurrent execution, are central to how GPUs work. A GPU handles thousands of threads simultaneously so it can efficiently process multiple tasks at once.
CUDA cores (NVIDIA) or stream processors (AMD). These are the fundamental processing units within a GPU, each capable of independently performing calculations. Modern GPUs have hundreds to thousands of these cores.
Memory hierarchy. The memory hierarchy of GPUs includes high-speed memory caches that minimize data access times to maintain high throughput during parallel processing.
Memory bandwidth. GPUs have high memory bandwidth designed to feed data to the numerous cores quickly and optimally utilize their processing power.
Shader units. These specialized processing units within a GPU handle specific tasks, such as vertex shading, geometry shading, pixel shading (fragment shading), and compute tasks. These units collectively contribute to rendering graphics and performing computations.
APIs and libraries. To efficiently utilize GPU power, software applications use programming interfaces like CUDA or OpenCL to manage and execute parallel tasks. These APIs provide tools and libraries so developers can create programs that efficiently leverage GPU capabilities.
Task distribution. Workloads in tasks like graphics rendering or scientific simulations are divided into many smaller tasks, each assigned to a different thread which the GPU then executes in parallel. This approach significantly speeds the overall processing time.
Some commonly used Microsoft Azure products include:
Azure virtual machines. Azure VMs are a fundamental building block for web hosting, application development, and testing in Azure.
Azure SQL database. This managed database service offers options for SQL Server, MySQL, PostgreSQL, and MariaDB and is widely used for running relational databases in the cloud.
Azure Blob Storage. This is a kind of object storage service that enables users to store and manage images, videos, backups, and other unstructured data.
Azure Storage Explorer. Azure Storage Explorer is a standalone tool with a graphical user interface for working with other Azure Storage components, including Azure Blob storage.
Azure Active Directory (Azure AD). Azure AD is the basis for user authentication, identity and access management and single sign-on in Azure and many other Microsoft services.
Azure Cosmos DB. This globally distributed, multi-model database service can help build highly responsive, scalable applications that require low-latency data access.
Azure Virtual Desktop. What is Azure Virtual Desktop? Azure Virtual Desktop enables users to create isolated, secure virtual desktop environments for applications and resources.
Azure Key Vault. This secure cryptographic key management service safeguards keys and other secrets used by cloud applications and services.
Commonly-used Azure services include:
Azure DevOps services. The Azure DevOps suite for software development and application lifecycle management enables version control and continuous integration/continuous delivery (CI/CD).
Azure Kubernetes service (AKS). The Azure Kubernetes orchestration service simplifies containerized application deployment and management.
Azure app service. What is Azure app service? This platform as a service (PaaS) simplifies web app and API development and hosting.
Azure Cloud Services
What is Azure cloud services and how do they support Azure cloud computing?
There are a few types of Microsoft Azure cloud services:
Microsoft cloud computing. Several Azure cloud services are designed specifically to support the Microsoft cloud computing platform:
- Azure cloud storage services such as Azure Blob Storage, Azure queues, Azure data lake storage
- Azure app services for web and mobile apps
- Azure functions (serverless computing)
- Azure Kubernetes service (AKS)Azure batch for high-performance computing
Data storage and content delivery. Other Azure services support data storage and content delivery:
- Azure cloud storage services such as Azure Blob Storage, Azure queues, Azure data lake storage
- Databases such as Azure SQL database, Azure Cosmos DB (NoSQL), Azure Database for MySQL, PostgreSQL, and MariaDB
- Azure Cache for Redis
- Azure Synapse AnalyticsAzure content delivery networks
Networking. Azure virtual network, load balancer, application gateway, VPN gateway, and Azure firewall all support networking.
Identity and security. Microsoft Azure cloud services that protect identity and security include Azure Active Directory, Azure multi-factor Authentication, Azure security center, Azure key vault, Azure Information Protection, and Azure identity protection.
AI and ML. Azure ML tools Microsoft services offers include Azure Cognitive Services (computer vision, language, and speech services) and Azure Databricks (for use with big data and AI applications).
Azure cloud migration and disaster recovery. Azure Site Recovery and Azure Migrate are services in this area
What is Azure IAAS?
Within Microsoft Azure cloud are service models that cater to different levels of control and management. One of these models is Infrastructure as a Service (IaaS):
Control. IaaS offers the highest level of control over infrastructure in the cloud Azure provides. Users manage and control their Azure virtual machines to retain more control over the operating systems they run on them. However, this also reserves additional technical tasks such as patching, updating, and configuring the OS for the user.
Azure VMs. These are virtualized computing environments that run a wide range of operating systems, applications, and workloads on the workloads on the Azure cloud infrastructure.
Use cases. IaaS is well-suited for scenarios in which users need full control over the environment, such as running custom applications, hosting legacy systems, or using specialized configurations. Common use cases for Azure virtual machines include:
- Hosting websites and web applications
- Running enterprise applications
- Development and testing environments
- Big data and analytics workloads
- Running virtual desktops
- Machine learning and artificial intelligence
- Remote application accessHigh-performance computing (HPC) tasks
Azure IAAS vs PAAS
How does Azure work within two other common service models to offer different levels of control and management?
Azure Platform as a Service (Azure PaaS) offers a moderate level of control for users. Azure PaaS services abstract away underlying infrastructure, giving users control over the application code and configurations but not the underlying infrastructure.
PaaS is ideal for prioritizing building and deploying web applications, APIs, and microservices over infrastructure management.
Azure Software as a Service (Azure SaaS) offers the most simplicity and freedom but the least amount of control. Here users access applications online without managing any underlying infrastructure or code. Business applications such as email or customer relationship management (CRM) software often use the SaaS model.
Pros and cons: Azure IaaS PaaS SaaS comparisons. The IaaS model allows for flexible configuration for VMs as needed. It is also suitable for lifting and shifting on-premises workloads to the cloud. However, it may have higher operational overhead and requires more management effort compared to PaaS and SaaS.
The Azure PaaS model streamlines development and deployment and simplifies scaling and management while reducing operational overhead. However, its limited control over infrastructure may not be suitable for applications with unique or complex requirements.The benefits of the SaaS model include the minimal or no maintenance or management required, the easy access from anywhere via internet, and the simple, fast adoption. However, the SaaS model offers limited customization and flexibility and is dependent on the provider’s feature set and roadmap.
Azure vs GCP vs AWS
AWS vs Azure vs Google cloud are all competitor platforms. Here is a very high-level AWS vs Azure vs GCP comparison:
Service offerings. These vary notably by provider:
- Azure. Azure focuses on enterprises and offers existing integrations with Microsoft products and services such as Windows Server, SQL Server, and Active Directory.
- AWS. AWS offers low-latency access to the most mature cloud platform and extensive global data center network.
- GCP. GCP is known for data analytics and a strong set of data and AI-related services. It is considered a good choice for data-intensive workloads and ML.
Global reach. Azure has data centers in over 60 regions worldwide, while AWS has the most extensive global network, with data centers in over 70 Availability Zones across 25 geographic regions. GCP has data centers in over 20 regions.
Pricing. While pricing can be complex and varies based on the specific services used, regions, and usage patterns, pricing models are relatively similar across the three cloud providers.Enterprise focus. There is more variation here, as with service offerings:
- Azure. Azure is well-suited for enterprises, offering deep integration with Microsoft products and services and a range of compliance certifications and security features.
- AWS. AWS has a strong enterprise presence and offers scalability and flexibility.
- GCP. GCP offers data and analytics capabilities and a strong focus on open-source technologies.
Developer and DevOps tools. All three providers offer a number of tools. Azure offers strong support for .NET and Windows-based development, while GCP is known for its support for open-source languages and tools.
ML and AI. All three offer a suite of strong choices of ML and AI tools and services.
Containers and Kubernetes. All three offer managed Kubernetes services.
Serverless computing. All three offer serverless computing options (Azure Functions, AWS Lambda, and Cloud Functions).
Hybrid and edge computing. All three offer solutions for extending cloud capabilities to on-premises and edge environments (Azure Arc, AWS Outposts, and Google Anthos).
Ecosystem and community. AWS has the largest community and ecosystem, as it was the first major cloud provider. However, Azure benefits from its strong integration with existing Microsoft products and their many users. And due to GCP’s expertise in open-source technologies, the platform benefits from an active, albeit smaller, core group of users.
Azure vs AWS
A high-level comparison of Microsoft Azure vs AWS offers an interesting view of some of the benefits of the Microsoft Azure cloud server:
- Strong integration with Microsoft products and services is preferable for organizations that rely on Windows Server, SQL Server, and Active Directory
- Robust hybrid cloud capabilities, including Azure Arc for managing on-premises and multi-cloud environments
- Licensing flexibility with options like Azure Hybrid Benefit
- Extensive geographic reach with data centers in over 60 regions
- Strong support for AI and ML
- Versatile support for various programming languages
- Azure DevOps for application development
- Azure Virtual Desktop for virtual desktop and application delivery
However, although there are several advantages of Azure over AWS, there are also many reasons to choose AWS:
- Extensive global network with data centers in over 70 availability zones
- Strong support for scalability and flexibility
- Widely used for developer and DevOps tools
- Extensive community and ecosystem
- Robust machine learning and AI services
- Strong cloud computing and data analytics presence
- A variety of managed Kubernetes servicesAWS Outposts for hybrid cloud deployments
Azure vs GCP
Obviously, Microsoft Azure is as described above. Here is what GCP offers in comparison:
- Expertise in data analytics for data-intensive workloads, support for AI and ML with services like TensorFlow and BigQuery ML
- Open-source technologies and tools
- Google Kubernetes Engine (GKE) for managed service and other support
- Google’s high-speed global networking infrastructureA growing ecosystem for cloud-native development
What is Azure Hybrid Cloud
The Microsoft hybrid cloud Azure model allows organizations to seamlessly integrate and manage public cloud resources. The primary goal of the Azure Hybrid Cloud model is to serve as a consistent, unified platform for securing and deploying applications across environments.
The Azure Hybrid Cloud benefits organizations that want the flexibility of cloud computing but need some level of control over their data from an on-premises or edge environment. By extending the management, security, and services from Azure to on-premises and edge environments, Azure Hybrid Cloud simplifies operations and enables consistent application deployment and management across the entire infrastructure. An Azure IoT hub that monitors data from an organization’s devices for a project and integrates it with on-premises systems for analysis and processing is a good Azure Hybrid Cloud example.
Azure Hybrid Cloud Architecture
There are a few key components of Microsoft Azure architecture for hybrid clouds:
Azure Arc. Azure Arc is a central piece of Azure Hybrid Cloud, allowing you to extend Azure management and services to on-premises servers, edge devices, and other cloud environments. With Azure Arc, you can centrally manage and monitor resources, apply policies, and deploy Azure services on any infrastructure, regardless of location.
Azure Stack. Azure Stack extends Azure so users may run services on their own infrastructure. There are two main products within Azure Stack:
- Azure Stack Hub allows users to run Azure services on their own hardware, creating a consistent platform for hybrid and edge computing
- Azure Stack HCI is a hyper-converged, highly available, software-defined infrastructure solution that integrates with Windows Server technologies
Azure Site Recovery. Azure Site Recovery is a disaster recovery and business continuity service that replicates VMs and workloads from on-premises data centers to Azure to ensure data resilience and high availability.
Azure Active Directory (Azure AD). Azure AD identity and access management services enable single sign-on and centralized management across environments.
Azure ExpressRoute. This enables secure, private network connections between on-premises and Azure data centers, providing low-latency and reliable connectivity for hybrid clouds.
Azure Virtual WAN. This networking service simplifies connectivity between branches, remote offices, and data centers.
What is Azure NetApp
Microsoft Azure NetApp files is a cloud-native, high-performance file storage service collaboration with the data storage and management company NetApp. Azure NetApp is designed to meet the storage requirements of enterprise workloads that demand low latency, high throughput, and consistent performance, such as databases, virtual desktops, and analytics applications.
Key features and characteristics of NetApp Microsoft Azure include:
Azure NetApp Files performance. Azure NetApp Files offers Enterprise-grade performance, low-latency file storage that is suitable for a wide range of demanding workloads. It provides consistent and predictable IOPS (Input/Output Operations Per Second) and throughput.
Shared file storage. Microsoft Azure NetApp is compatible with both Linux and Windows-based applications because it supports both the Network File System (NFS) and Server Message Block (SMB) file protocols.
Scalability. Azure NetApp Files can scale dynamically to accommodate growing workloads and adjust capacity and performance levels as needed without application downtime.
Data management and protection. Azure NetApp files backup features include built-in data protection and disaster recovery options, helping to ensure data integrity and availability.
Advanced data services. Azure NetApp Files offers data management services such as cloning, snapshots, and replication.
Integration with Azure services. Seamless integration with other Windows Azure services and resources, enabling comprehensive solutions. For example, Azure NetApp Files supports Azure virtual machines and can host data for AI and analytics workloads.
Security and compliance. Azure NetApp Files provides encryption at rest and in transit, role-based access control, and support for Azure Private Link.
Use cases for NetApp Azure include:
- Running high performance, business-critical applications and databases
- Hosting enterprise file shares and home directories
- Supporting virtual desktop infrastructure (VDI) environments
- Storing data for analytics and ML workloadsMigrating on-premises applications to Azure without modifying code:
Microsoft Azure Pros and Cons
Why use Azure? There are many advantages and disadvantages of Microsoft Azure, but the application is outcome-determinative.
Here are the pros and cons of Microsoft Azure in a general sense and why Azure might be the right choice based on the particular use case:
Comprehensive services. Azure provides a vast selection of services, including computing resources, storage, databases, AI, ML, analytics, customer-facing, real-time applications, and more, making it a one-stop shop for diverse business needs.
Integration with Microsoft products. Seamless integration with Microsoft technologies such as Windows Server, SQL Server, Active Directory, and .NET, makes Azure an excellent choice for organizations already using these tools.
Hybrid cloud capabilities. Azure supports the hybrid cloud, enabling organizations to extend their on-premises environments seamlessly and securely.
Reach. Azure has a broad global presence, with data centers in over 60 regions, offering worldwide low-latency access and high availability.
Scalability. Azure allows organizations to scale resources up or down based on changing workloads and demand, helping control costs and ensure performance.
Considering some common use cases helps to flesh out the advantages and disadvantages of Azure:
Enterprise and corporate. Large and enterprise-sized organizations across industries use Azure to host applications, manage data, and enhance productivity with tools like Microsoft 365.
Healthcare. Healthcare organizations use Azure to store and analyze medical data, conduct research, and develop healthcare applications that require scalability and security.
Finance. The financial sector, including banks and insurance companies, often use Azure for its security, compliance features, and analytics capabilities that process vast amounts of financial data while meeting regulatory requirements.
Blockchain. Azure offers cloud-based services and solutions for building, managing, and deploying blockchain applications more easily. Azure Blockchain supports various protocols and frameworks, such as Ethereum, Hyperledger Fabric, and Corda, and offers features like smart contract management, identity and access management, and secure, scalable infrastructure for blockchain applications.
Enable Hybrid Cloud Workflows with WEKA on Azure
The WEKA Data Platform for Microsoft Azure WEKA Data Platform for Microsoft Azure is a cloud-native, software-defined storage solution for next-generation workloads like artificial intelligence and machine learning that supports large-scale data collection and processing on high-performance computing infrastructures. The platform provides a unified experience across on-premises and cloud deployment models in a single software code base, allowing organizations to configure storage to meet their specific requirements without forcing a choice between cloud and on-premises solutions. It offers performance, agility, and scalability, no matter where the workload runs, enabling organizations to deliver applications and data where they provide the best experience for their customers.
With WEKA, organizations avoid the trade-off between cloud economics and performance by breaking down data silos to unlock new levels of innovation and flexibility in a hybrid cloud environment.