Azure AZ-900 Fundamentals Exam

Understanding Pay-As-You-Go Pricing

Pay-As-You-Go (PAYG) pricing is a flexible cloud pricing model where users are billed based on their actual usage of resources. This model is particularly advantageous for those who need to manage costs effectively and avoid upfront commitments. With PAYG, you only pay for what you use, which can help optimize expenditure, especially in scenarios where resource demand is unpredictable or varies over time. When using virtual machines (VMs) in Azure, several associated resources might incur additional costs. These include virtual networks, network interface cards (NICs), IP addresses, network security groups (NSGs), and disks. While some of these resources, like NICs and NSGs, do not incur costs by themselves, others, such as additional disks and bandwidth, do. It’s important to monitor these resources to avoid unexpected charges, especially after deleting VMs, as some resources might continue to accrue costs until they are also deleted. Azure offers tools to help manage and estimate costs. For instance, the Azure portal provides a summary of estimated costs when creating resources. Users can adjust settings to see how different configurations affect pricing. Additionally, Azure’s Cost Management features allow users to set budgets, monitor costs, and create alerts for spending anomalies. This helps in maintaining control over expenses and ensuring that spending stays within budget. To further optimize costs, Azure provides options like savings plans and reserved instances. Savings plans allow users to commit to a fixed hourly amount for VMs, unlocking lower prices. Reserved instances offer significant discounts for one- or three-year commitments. These options are beneficial for users with predictable workloads, as they can lead to substantial cost savings compared to PAYG pricing.

In summary, the PAYG pricing model in Azure offers flexibility and cost management benefits, making it suitable for various scenarios. By understanding the associated costs of resources, using Azure’s cost management tools, and exploring savings options, users can effectively manage and optimize their cloud expenditure.

Explore Reserved Instances

Reserved Instances in Azure are a pricing model where you commit to using a specific amount of resources for a one- or three-year term. This model can offer significant cost savings compared to pay-as-you-go pricing. By committing to a longer-term usage, you can save up to 72% over the standard pricing. This makes Reserved Instances ideal for predictable, long-term workloads. One of the main benefits of Reserved Instances is cost predictability. Since you are committing to a set amount of resources, you can better forecast your expenses and avoid unexpected costs. This is particularly useful for businesses with steady-state or predictable workloads, as it allows for more accurate budgeting and financial planning. Reserved Instances also provide flexibility. Azure allows you to exchange or cancel Reserved Instances if your needs change. For example, if you need to switch to a different instance type or region, you can do so with minimal hassle. This flexibility ensures that you can adapt to changing business requirements without losing the benefits of reserved pricing.

In summary, Reserved Instances are a cost-effective and predictable pricing model for long-term Azure resource usage. They offer significant savings and flexibility, making them a valuable option for businesses with stable and predictable workloads. By understanding and utilizing Reserved Instances, you can optimize your cloud expenditure and ensure more predictable financial planning.

Investigate Spot Pricing

Azure Spot Virtual Machines (VMs) offer a cost-effective way to utilize unused Azure capacity at significantly reduced rates. Spot VMs are ideal for workloads that can tolerate interruptions, such as batch processing jobs, development and testing environments, and large compute workloads. The pricing for Spot VMs is variable and depends on the region and SKU. You can set a maximum price you are willing to pay per hour for the VM, which can be specified up to five decimal places in US dollars. One of the key aspects of Spot VMs is the potential for eviction. When Azure needs the capacity back, Spot VMs can be evicted at any time. This means there is no Service Level Agreement (SLA) for Spot VMs, making them unsuitable for critical workloads that require guaranteed uptime. However, you can choose the eviction policy for your Spot VM, either to deallocate (default) or delete the VM when it is evicted. Deallocating allows the VM to be restarted later, while deleting removes the VM and its underlying disk. To manage costs effectively, you can use the Azure CLI, PowerShell, or the Azure portal to deploy Spot VMs. For example, when creating a Spot VM using the Azure CLI, you can specify the --priority Spot parameter and set the --eviction-policy to either Deallocate or Delete. Additionally, you can simulate an eviction to test how your application responds to sudden interruptions, ensuring your workload can handle the potential disruptions. Azure Spot VMs have a separate quota pool, and you can request additional quota if needed. The quota is shared between VMs and scale-set instances. For more detailed information on pricing and setting the max price, you can refer to the Azure Spot Virtual Machines - Pricing documentation. This flexibility allows you to optimize your cloud expenditure by leveraging unused capacity at a lower cost, making Spot VMs a valuable option for non-critical or flexible workloads.

Evaluate Hybrid Use Benefit

Azure Hybrid Use Benefit allows organizations to use their existing on-premises licenses to reduce costs when moving to the cloud. This benefit is particularly useful for those who already have Windows Server or SQL Server licenses with Software Assurance. By leveraging these existing licenses, organizations can save significantly on Azure Virtual Machines (VMs) and other services. Cost Savings: The primary advantage of the Azure Hybrid Use Benefit is the potential for substantial cost savings. Organizations can save up to 40% on Windows Server VMs and up to 55% on SQL Server VMs. These savings are achieved by applying the on-premises licenses to the cloud environment, reducing the need to purchase new licenses. Licensing Requirements: To take advantage of the Azure Hybrid Use Benefit, organizations must have active Software Assurance or subscription licenses. This ensures that the licenses are eligible for use in the cloud. It’s important to verify that the licenses are compliant and meet the necessary criteria to avoid any potential issues. Scenarios for Use: The Azure Hybrid Use Benefit is beneficial in various scenarios, such as migrating existing workloads to the cloud, setting up disaster recovery solutions, or creating hybrid environments that span on-premises and cloud resources. By using this benefit, organizations can optimize their cloud expenditure and make more efficient use of their existing investments.

In summary, the Azure Hybrid Use Benefit is a valuable tool for organizations looking to reduce costs and maximize the value of their existing licenses when moving to the cloud. By understanding the cost savings, licensing requirements, and appropriate scenarios for use, organizations can effectively leverage this benefit to optimize their cloud expenditure.

Analyze Total Cost of Ownership (TCO)

When analyzing the Total Cost of Ownership (TCO) for Azure SQL Database, it’s important to understand the two main purchasing models: vCore-based and DTU-based. The vCore-based model offers flexibility by allowing you to choose compute, memory, and storage resources independently, making it suitable for workloads that require specific configurations. This model also supports Azure Hybrid Benefit, which can help reduce costs. On the other hand, the DTU-based model provides preconfigured bundles of compute, storage, and I/O resources, making it simpler but less flexible. Compute costs differ between the two models. In the vCore-based model, costs are based on the chosen compute tier (provisioned or serverless) and the specific resources used. The provisioned tier charges for the total compute capacity, while the serverless tier charges based on actual usage, which can be more cost-effective for variable workloads. In contrast, the DTU-based model charges a fixed rate based on the number of DTUs allocated, which can be easier to predict but may not always be the most cost-efficient. Storage costs also vary. In the vCore-based model, data storage costs depend on the maximum database size selected, and backup storage is billed separately based on usage. The DTU-based model includes storage in the price, with additional storage available for a fee in higher tiers. Long-term retention is billed separately in both models, but the vCore-based model offers more granular control over storage costs. Using tools like the Azure pricing calculator can help estimate costs for different configurations and scenarios, aiding in TCO analysis. This analysis is crucial for making informed decisions about which purchasing model to use, considering factors like initial investment, operational costs, and potential long-term savings.

By comparing these models, organizations can optimize their cloud expenditure and choose the best fit for their specific needs.