Azure VMWare (AVS) Cost Optimization Using Azure Migrate Tool
What is AVS? Azure VMware Solution provides private clouds that contain VMware vSphere clusters built from dedicated bare-metal Azure infrastructure. Azure VMware Solution is available in Azure Commercial and Azure Government. The minimum initial deployment is three hosts, with the option to add more hosts, up to a maximum of 16 hosts per cluster. All provisioned private clouds have VMware vCenter Server, VMware vSAN, VMware vSphere, and VMware NSX. As a result, you can migrate workloads from your on-premises environments, deploy new virtual machines (VMs), and consume Azure services from your private clouds. Learn More: https://learn.microsoft.com/en-us/azure/azure-vmware/introduction What is Azure Migrate Tool? Azure Migrate is a comprehensive service designed to help you plan and execute your migration to Azure. It provides a unified platform to discover, assess, and migrate your on-premises resources, including servers, databases, web apps, and virtual desktops, to Azure. The tool offers features like dependency analysis, cost estimation, and readiness assessments to ensure a smooth and efficient migration process. Learn More: https://learn.microsoft.com/en-us/azure/migrate/migrate-services-overview How Azure Migrate can be used to Discover and Assess AVS? Azure Migrate enables the discovery and assessment of Azure VMware Solution (AVS) environments by collecting inventory and performance data from on-premises VMware environments, either through direct integration with vCenter (via Appliance) or by importing data from tools like RVTools. Using Azure Migrate, organizations can analyze the compatibility of their VMware workloads for migration to AVS, assess costs, and evaluate performance requirements. The process involves creating an Azure Migrate project, discovering VMware VMs, and generating assessments that provide insights into resource utilization, right-sizing recommendations, and estimated costs in AVS. This streamlined approach helps plan and execute migrations effectively while ensuring workloads are optimized for the target AVS environment. Note: We will be narrating the RVtools Import method in this article. What Is RVTools? RVTools is a lightweight, free utility designed for VMware administrators to collect, analyze, and export detailed inventory and performance data from VMware vSphere environments. Developed by Rob de Veij, RVTools connects to vCenter or ESXi hosts using VMware's vSphere Management SDK to retrieve comprehensive information about the virtual infrastructure. Key Features of RVTools: Inventory Management: Provides detailed information about virtual machines (VMs), hosts, clusters, datastores, networks, and snapshots. Includes details like VM names, operating systems, IP addresses, resource allocations (CPU, memory, storage), and more. Performance Insights: Offers visibility into resource utilization, including CPU and memory usage, disk space, and VM states (e.g., powered on/off). Snapshot Analysis: Identifies unused or orphaned snapshots, helping to optimize storage and reduce overhead. Export to Excel: Allows users to export all collected data into an Excel spreadsheet (.xlsx) for analysis, reporting, and integration with tools like Azure Migrate. Health Checks: Identifies configuration issues, such as disconnected hosts, orphaned VMs, or outdated VMware Tools versions. User-Friendly Interface: Displays information in tabular form across multiple tabs, making it easy to navigate and analyze specific components of the VMware environment. Hand-on LAB Disclaimer: The data used for this LAB has no relationship with real world scenarios. This sample data is self-created by the author and purely for understanding the concept. To discover and assess your Azure VMware Solution (AVS) environment using an RVTools extract report in the Azure Migrate tool, follow these steps: Prerequisites RVTools Setup: Download and install RVTools from the RVTools Download Ensure connectivity to your vCenter server. Extract the data by running RVTools and saving the output as an Excel (.xlsx) file Permissions: You need at least the Contributor role on the Azure Migrate project. Ensure that you have appropriate permissions in your vCenter environment to collect inventory and performance data. File Requirements: The RVTools file must be saved in .xlsx format without renaming or modifying the tabs or column headers. Note: Sample Sheet: Please check the attachment included with this article. Note that this is not the complete format; some tabs and columns have been removed for simplicity. During the actual discovery and assessment process, please do not modify the tabs or columns. Procedure Step 1: Export Data from RVTools Follow the steps provided in official website to get RVTools Extract Sample Sheet: Please check the attachment included with this article. Note that this is not the complete format; some tabs and columns have been removed for simplicity. During the actual discovery and assessment process, please do not modify the tabs or columns. Step 2: Discover Log in to the Azure portal. Navigate to Azure Migrate and select your project or create new project. Under Migration goals, select Servers, databases and web apps. On Azure Migrate | Servers, databases and web apps page, under Assessment tools, select Discover and then select Using import. In Discover page, in File type, select VMware inventory (RVTools XLSX). In the Step 1: Import the file section, select the RVTools XLSX file and then select Import. Wait for some time to Import Once import completed check for Error Messages if any and rectify those and re upload, otherwise wait 10-15 minutes to reflect imported VMs in the discovery. Post discovery Reference Link: https://learn.microsoft.com/en-us/azure/migrate/vmware/tutorial-import-vmware-using-rvtools-xlsx?context=%2Fazure%2Fmigrate%2Fcontext%2Fvmware-context Step 3: Assess After the upload is complete, navigate to the Servers tab. Click on Assess -->Azure VMware Solution to assess the discovered machines. Edit assessment settings based on your requirements and Save Target region: Select the Azure region for the migration. Node Type: Specify the Azure VMware Solution series (e.g., AV36, AV36P). Pricing model: Select pay-as-you-go or reserved instance pricing. Discount: Specify any available discounts. Note: We will be explaining all the parameters in optimize session. As of now just review and leave parameters as it is. In Assess Servers, select Next. In Select servers to assess > Assessment name > specify a name for the assessment. In Select or create a group > select Create New and specify a group name. Select the appliance and select the servers you want to add to the group. Then select Next. In Review + create assessment, review the assessment details, and select Create Assessment to create the group and run the assessment. Step 4: Review the Assessment View an assessment In Windows, Linux and SQL Server > Azure Migrate: Discovery and assessment, select the number next to Azure VMware Solution. In Assessments, select an assessment to open it. As an example (estimations and costs, for example, only): Review the assessment summary. You can select Sizing assumptions to understand the assumptions that went in node sizing and resource utilization calculations. You can also edit the assessment properties or recalculate the assessment. Step 5: Optimize We have received a report without any optimization in our previous steps. Now we can follow below steps to optimize the cost and node count even further High level steps: Find limiting factor Find which component in settings are mapped for optimization depending on limiting factor Try to adjust the mapped component according to Scenario and Comfort Find Limiting factor: First understand which component (CPU, memory and storage) is deciding your ESXI Node count. This will be highlighted in the report The limiting factor shown in assessments could be CPU or memory or storage resources based on the utilization on nodes. It is the resource, which is limiting or determining the number of hosts/nodes required to accommodate the resources. For example, in an assessment if it was found that after migrating 8 VMware VMs to Azure VMware Solution, 50% of CPU resources will be utilized, 14% of memory is utilized and 18% of storage will be utilized on the 3 Av36 nodes and thus CPU is the limiting factor. Find which option in the setting can be used to optimize: This is depending on the limiting factor. For eg: If Limiting factor is CPU, which means you have high CPU requirement and CPU oversubscription can be used to optimize ESXI Node. Likewise, if storage is the limiting factor editing FTT, RAID or introducing External storage like ANF will help you to reduce Node count. Even reducing one node count will create a huge impact in dollar value. Let's understand how over commitment or over subscription works with simple example. Let's suppose I have two VMs with below specification Name CPU Memory Storage VM1 9 vCPU 200 GB 500 GB VM2 4 vCPU 200 GB 500 GB Total 13 vCPU 400 GB 1000 GB We have EXSI Node which has below capacity: vCPU 10 Memory 500 GB storage 1024 GB Now without optimization I need two ESXI node to accommodate 13 vCPU of total requirement. But let's suppose VM1 and VM2 doesn't consume entire capacity all the time. The total capacity usage at a time will not go beyond 10. then I can accommodate both VM in same ESXI node, Hence I can reduce my node count and cost. Which means it is possible to share resources among both VMs. Without optimization With optimization Parameters effecting Sizing and Pricing CPU Oversubscription Specifies the ratio of number of virtual cores tied to one physical core in the Azure VMware Solution node. The default value in the calculations is 4 vCPU:1 physical core in Azure VMware Solution. API users can set this value as an integer. Note that vCPU Oversubscription > 4:1 may impact workloads depending on their CPU usage. Memory overcommit factor Specifies the ratio of memory overcommit on the cluster. A value of 1 represents 100% memory use, 0.5, for example is 50%, and 2 would be using 200% of available memory. You can only add values from 0.5 to 10 up to one decimal place. Deduplication and compression factor Specifies the anticipated deduplication and compression factor for your workloads. Actual value can be obtained from on-premises vSAN or storage configurations. These vary by workload. A value of 3 would mean 3x so for 300GB disk only 100GB storage would be used. A value of 1 would mean no deduplication or compression. You can only add values from 1 to 10 up to one decimal place. FTT : How many device failure can be tolerated for a VM RAID : RAID stands for Redundant Arrays of Independent Disks Explains how data should be stored for redundancy Mirroring : Data will be duplicated as it is to another disk E.g.: To protect a 100 GB VM object by using RAID-1 (Mirroring) with an FTT of 1, you consume 200 GB. Erasure Coding : Erasure coding divides data into chunks and calculates parity information (redundant data) across multiple storage devices. This allows data reconstruction even if some chunks are lost, similar to RAID, but typically more space-efficient E.g.: to protect a 100 GB VM object by using RAID-5 (Erasure Coding) with an FTT of 1, you consume 133.33 GB. Comfort Factor: Azure Migrate considers a buffer (comfort factor) during assessment. This buffer is applied on top of server utilization data for VMs (CPU, memory and disk). The comfort factor accounts for issues such as seasonal usage, short performance history, and likely increases in future usage. For example, a 10-core VM with 20% utilization normally results in a 2-core VM. However, with a comfort factor of 2.0x, the result is a 4-core VM instead. AVS SKU Sizes Optimization Result In this example we got to know that CPU is my limiting factor hence I have adjusted CPU over subscription value from 4:1 to 8:1 Reduced node count from 6 (3 AV36P+3 AV64) to 5 AV36P Reduced Cost by 31% Note: Over-provisioning or over-committing can put your VMs at risk. However, in Azure Cloud, you can create alarms to warn you of unexpected demand increases and add new ESXi nodes on demand. This is the beauty of the cloud: if your resources are under-provisioned, you can scale up or down at any time. Running your resources in an optimized environment not only saves your budget but also allows you to allocate funds for more innovative ideas.
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Security is being reengineered for the AI era—moving beyond static, rulebound controls and after-the-fact response toward platform-led, machine-speed defense. The challenge is clear: fragmented tools, sprawling signals, and legacy architectures that can’t match the velocity and scale of modern attacks. What’s needed is an AI-ready, data-first foundation—one that turns telemetry into a security graph, standardizes access for agents, and coordinates autonomous actions while keeping humans in command of strategy and high-impact investigations. Security teams already center operations on their SIEM for end-to-end visibility, and we’re advancing that foundation by evolving Microsoft Sentinel into both the SIEM and the platform for agentic defense—connecting analytics and context across ecosystems. 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With Sentinel graph, Defenders and AI can quickly reveal relationships, traversable digital paths to understand blast radius, privilege escalation, and anomalies across large, cloud-scale data sets, deriving deep contextual insight across their digital estate, SOC teams and their AI Agents can stay proactive and resilient. With Sentinel graph-powered experiences in Defender and Purview, defenders can now reason over assets, identities, activities, and threat intelligence to accelerate detection, hunting, investigation, and response. Incident graph in Defender. The incident graph in the Microsoft Defender portal is now enriched with ability to analyze blast radius of the active attack. During an incident investigation, the blast radius analysis quickly evaluates and visualizes the vulnerable paths an attacker could take from a compromise entity to a critical asset. This allows SOC teams to effectively prioritize and focus their attack mitigation and response saving critical time and limiting impact. Hunting graph in Defender. Threat hunting often requires connecting disparate pieces of data to uncover hidden paths that attackers exploit to reach your crown jewels. With the new hunting graph, analysts can visually traverse the complex web of relationships between users, devices, and other entities to reveal privileged access paths to critical assets. This graph-powered exploration transforms threat hunting into a proactive mission, enabling SOC teams to surface vulnerabilities and intercept attacks before they gain momentum. This approach shifts security operations from reactive alert handling to proactive threat hunting, enabling teams to identify vulnerabilities and stop attacks before they escalate. Data risk graph in Purview Insider Risk Management (IRM). Investigating data leaks and insider risks is challenging when information is scattered across multiple sources. The data risk graph in IRM offers a unified view across SharePoint and OneDrive, connecting users, assets, and activities. Investigators can see not just what data was leaked, but also the full blast radius of risky user activity. This context helps data security teams triage alerts, understand the impact of incidents, and take targeted actions to prevent future leaks. Data risk graph in Purview Data Security Investigation (DSI). To truly understand a data breach, you need to follow the trail—tracking files and their activities across every tool and source. The data risk graph does this by automatically combining unified audit logs, Entra audit logs, and threat intelligence, providing an invaluable insight. With the power of the data risk graph, data security teams can pinpoint sensitive data access and movement, map potential exfiltration paths, and visualize the users and activities linked to risky files, all in one view. Getting started Microsoft Defender If you already have the Sentinel data lake, the required graph will be auto provisioned when you login into the Defender portal; hunting graph and incident graph experience will appear in the Defender portal. New to data lake? Use the Sentinel data lake onboarding flow to provision the data lake and graph. Microsoft Purview Follow the Sentinel data lake onboarding flow to provision the data lake and graph. In Purview Insider Risk Management (IRM), follow the instructions here. In Purview Data Security Investigation (DSI), follow the instructions here. Reference links Watch Microsoft Secure Microsoft Secure news blog Data lake blog MCP server blog ISV blog Security Store blog Copilot blog Microsoft Sentinel—AI-Powered Cloud SIEM | Microsoft SecurityHow to Master GitHub Copilot: Build, Prompt, Deploy Smarter
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