When recommending a virtual machine-based solution in Azure, a Solutions Architect must evaluate several critical factors to ensure optimal performance, cost-efficiency, and reliability. First, assess the workload requirements including CPU, memory, storage, and network needs. Azure offers various …When recommending a virtual machine-based solution in Azure, a Solutions Architect must evaluate several critical factors to ensure optimal performance, cost-efficiency, and reliability. First, assess the workload requirements including CPU, memory, storage, and network needs. Azure offers various VM series: D-series for general-purpose workloads, E-series for memory-intensive applications, F-series for compute-heavy tasks, and N-series for GPU-accelerated scenarios. Consider the application architecture and determine if single VMs or VM Scale Sets are appropriate. Scale Sets provide automatic scaling capabilities, distributing instances across fault domains and update domains for high availability. For mission-critical applications, implement Availability Zones to protect against datacenter failures, achieving 99.99% SLA. Evaluate storage requirements carefully. Premium SSDs offer high IOPS for database workloads, while Standard HDDs suit archival storage. Ultra Disks provide the highest performance tier for demanding transactional databases. Network configuration is essential - plan virtual networks, subnets, and Network Security Groups to control traffic flow. Consider using Accelerated Networking for reduced latency and Azure Load Balancer or Application Gateway for traffic distribution. Cost optimization strategies include Reserved Instances for predictable workloads, offering up to 72% savings over pay-as-go pricing. Azure Spot VMs provide significant discounts for interruptible workloads like batch processing. Implement Azure Hybrid Benefit if you have existing Windows Server or SQL Server licenses. Security considerations include enabling Azure Disk Encryption, implementing Just-In-Time VM access, and using Azure Bastion for secure remote management. Regular patching through Update Management ensures systems remain protected. Finally, establish monitoring using Azure Monitor and configure diagnostic settings to collect performance metrics and logs. Set up alerts for critical thresholds and use VM Insights for comprehensive visibility into VM health and dependencies. This holistic approach ensures a robust, scalable, and cost-effective virtual machine solution.
Recommend a Virtual Machine-Based Solution
Why It Is Important
Understanding when and how to recommend virtual machine (VM)-based solutions is crucial for Azure Solutions Architects. VMs remain the backbone of many enterprise workloads, offering flexibility, control, and compatibility with legacy applications. The AZ-305 exam tests your ability to select appropriate compute solutions, and VMs are often the right choice for lift-and-shift migrations, custom configurations, and workloads requiring specific OS or software requirements.
What It Is
A VM-based solution involves deploying Azure Virtual Machines to host applications, services, or workloads. Azure VMs provide Infrastructure as a Service (IaaS), giving you full control over the operating system, installed software, and network configuration. Key components include:
• VM Series and Sizes: General purpose (B, D series), Compute optimized (F series), Memory optimized (E, M series), Storage optimized (L series), GPU (N series), and High-performance compute (H series) • Availability Sets: Protect against hardware failures within a datacenter • Availability Zones: Protect against entire datacenter failures • Virtual Machine Scale Sets (VMSS): Enable auto-scaling of identical VMs • Azure Dedicated Hosts: Physical servers dedicated to your organization
How It Works
When designing VM-based solutions, consider these factors:
1. Sizing and Performance: Match VM size to workload requirements. Consider CPU, memory, storage IOPS, and network bandwidth. Use Azure Advisor recommendations for right-sizing.
2. High Availability: Deploy VMs across Availability Zones for 99.99% SLA, or use Availability Sets for 99.95% SLA. For mission-critical workloads, combine with Azure Site Recovery for disaster recovery.
3. Scalability: Use Virtual Machine Scale Sets for automatic horizontal scaling based on demand metrics like CPU utilization or custom metrics.
4. Cost Optimization: Leverage Azure Reserved Instances for predictable workloads (up to 72% savings), Spot VMs for interruptible workloads (up to 90% savings), and Azure Hybrid Benefit for existing Windows Server or SQL Server licenses.
5. Security: Implement Azure Bastion for secure RDP/SSH access, use managed identities, enable Azure Disk Encryption, and apply Network Security Groups.
Exam Tips: Answering Questions on Recommend a Virtual Machine-Based Solution
• Know when VMs are preferred: Choose VMs when you need full OS control, specific software installations, lift-and-shift scenarios, or legacy application support
• Understand VM series: Memory-intensive workloads need E or M series; compute-intensive need F series; GPU workloads need N series
• Cost scenarios: Look for keywords like predictable workload (Reserved Instances), batch processing or fault-tolerant (Spot VMs), or existing licenses (Hybrid Benefit)
• Scaling requirements: When questions mention variable demand or auto-scaling, think Virtual Machine Scale Sets
• Compliance and isolation: Questions about regulatory requirements or dedicated hardware point to Azure Dedicated Hosts
• Read carefully for constraints: Pay attention to whether the scenario requires Windows or Linux, specific regions, or network latency requirements
• Eliminate container or PaaS options: If the question emphasizes OS-level access, custom drivers, or legacy dependencies, VM solutions are typically correct over App Service or containers