Category: Microsoft
Category Archives: Microsoft
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Optimize your Azure costs
Author introduction
Hi, I am Saira Shaik, Working Principal customer success account manager at Microsoft India.
This article will provide guidance to the customers who wants to Optimize their Azure costs by providing tools and resources to help customers to save cost, Understand and forecast your costs, Cost optimize workloads and Control costs.
Explore tools and resources to help you save
Find out about the tools, offers, and guidance designed to help you manage and optimize your Azure costs. Learn how to understand and forecast your bill, optimize workload costs, and control your spending.
8 ways to optimize the cost
1. Shut down unused resources.
Identify idle virtual machines (VMs), ExpressRoute circuits, and other resources with Azure Advisor. Get recommendations on which resources to shut down and see how much you would save.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
2. Right-size underused resources
Find underutilized resources with Azure Advisor—and get recommendations on how to reduce your spend by reconfiguring or consolidating them.
Useful Links
Reduce service costs using Azure Advisor – Azure Advisor | Microsoft Learn
3. Add an Azure savings plan for compute for dynamic workloads
Save up to 65 percent off pay-as-you-go pricing when you commit to spend a fixed hourly amount on compute services for one or three years.
Useful Links
Azure Savings Plan Savings – youtube.com/playlist?list=PLlrxD0HtieHjd-zn7u09YoGJY18ZrN1Hq
Introduction to Azure savings plan for compute (youtube.com)
Understanding your Azure savings plan recommendations (youtube.com)
How Azure savings plan is applied to a customer’s compute environment (youtube.com)
Azure Savings Plan for Compute | Microsoft Azure
4. Reserve instances for consistent workloads
Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.Get a discount of up to 72 percent over pay-as-you-go pricing on Azure services when you prepay for a one- or three-year term with reservation pricing.
Useful Links
Reservations | Microsoft Azure
Advisor Clinic: Lower costs with Azure Virtual Machine reservations (youtube.com)
Model virtual machine costs with the Azure Cost Estimator Power BI Template (youtube.com)
5. Take advantage of the Azure Hybrid Benefit
AWS is up to five times more expensive than Azure for Windows Server and SQL Server. Save when you migrate your on-premises workloads to Azure.
Useful Links
Azure Hybrid Benefit—hybrid cloud | Microsoft Azure
Reduce costs and increase SQL license utilization using Azure Hybrid Benefit (youtube.com)
Managing and Optimizing Your Azure Hybrid Benefit Usage (With Tools!) – Microsoft Community Hub
6. Configure autoscaling
Save by dynamically allocating and de-allocating resources to match your performance needs.
Useful Links
Autoscaling guidance – Best practices for cloud applications | Microsoft Learn
7. Choose the right Azure compute service
Azure offers many ways to host your code. Operate more cost efficiently by selecting the right compute service for your application.
Useful Links
Choose an Azure compute service – Azure Architecture Center | Microsoft Learn
Armchair Architects: Exploring the relationship between Cost and Architecture (youtube.com)
8. Set up budgets and allocate costs to teams and projects
Create and manage budgets for the Azure services you use or subscribe to—and monitor your organization’s cloud spending—with Microsoft Cost Management.
Useful Links
Tutorial – Create and manage budgets – Microsoft Cost Management | Microsoft Learn
The Cloud Clinic: Use tagging and cost management tools to keep your org accountable (youtube.com)
Understand and forecast your costs
Monitor and analyze your Azure bill with Microsoft Cost Management. Set budgets and allocate spending to your teams and projects.
Estimate the costs for your next Azure projects using the Azure pricing calculator and the Total Cost of Ownership (TCO) calculator.
Successfully build your cloud business case with key financial and technical guidance from Azure.
Useful Links
FinOps toolkit – Kick start your FinOps efforts (microsoft.github.io)
Azure Savings Dashboard – Microsoft Community Hub
Azure Cost Management Dashboard – Microsoft Community Hub
Cost optimize your workloads
Follow your Azure Advisor best practice recommendations for cost savings.
Review your workload architecture for cost optimization using the Microsoft Azure Well-Architected Review assessment and the Microsoft Azure Well-Architected Framework design documentation, well architected cost optimization implementation – Customer Offerings: Well-Architected Cost Optimization Implementation – Microsoft Community Hub
Save with Azure offers and licensing terms such as the Azure Hybrid Benefit, paying in advance for predictable workloads with reservations, Azure Spot Virtual Machines, Azure savings plan for compute, and Azure dev/test pricing.
Control your costs
Mitigate cloud spending risks by implementing cost management governance best practices at your company using the Microsoft Cloud Adoption Framework for Azure.
Implement cost controls and guardrails for your environment with Azure Policy.
Microsoft Tech Community – Latest Blogs –Read More
Azure SQL MI premium-series memory optimized hw is now available in all regions with up to 40 vCores
Recently, we announced a number of Azure SQL Managed Instance improvements in Business Critical tier. In this article, we would like to highlight that the premium-series memory optimized hardware is now available in all Azure regions, up to 40 vCores!
What is new?
Having the latest and greatest hardware generation available for the Azure SQL Managed Instance Business Critical service tier can be crucial for the critical customer workloads. Until recently, premium-series memory optimized hardware generation was available only in a subset of Azure regions. Now you can have a SQL MI BC instance with premium-series memory optimized hardware in any Azure region up to 40 vCores.
This means that the new state for premium-series memory optimized hardware availability is:
Up to 40 vCores: available in every Azure region.
48, 56, 64, 80, 96 and 128 vCore options: for now, available in a subset of Azure regions.
Improve performance of your database workload with more memory per vCore
Increasing memory can improve the performance of applications and databases by reducing the need to read from disk and instead storing more data in memory, which is faster to access. You might want to consider upgrading to memory-optimized premium-series for several reasons:
Buffering and Caching: More memory can be utilized for caching frequently accessed data or buffering I/O operations, leading to faster response times and improved overall system performance.
Handling Larger Datasets: If the user is dealing with larger datasets or increasing workload demands, more memory can accommodate the additional data and processing requirements without experiencing slowdowns or performance bottlenecks.
Concurrency and Scalability: Higher memory capacity can support more concurrent users or processes, allowing the system to handle increased workload and scale effectively without sacrificing performance.
Complex Queries and Analytics: Memory-intensive operations such as complex queries, data analytics, and reporting often benefit from having more memory available to store intermediate results and perform calculations efficiently.
In-Memory Processing: Some databases and applications offer in-memory processing capabilities, where data is stored and manipulated entirely in memory for faster processing. Increasing memory allows for more data to be processed in-memory, resulting in faster query execution and data manipulation.
How to upgrade your instance to premium-series memory optimized hardware
You can scale your existing managed instance from Azure portal, PowerShell, Azure CLI or ARM templates. You can also utilize ‘online scaling’ with minimal downtime. See Scale resources – Azure SQL Database & Azure SQL Managed Instance | Microsoft Learn.
Summary
More memory for a managed instance can lead to improved performance, scalability, and efficiency in handling larger workloads, complex operations, and data processing tasks. This improvement in Azure SQL Managed Instance Business Critical makes premium-series memory optimized hardware available in all regions, up to 40 vCores.
If you’re still new to Azure SQL Managed Instance, now is a great time to get started and take Azure SQL Managed Instance for a spin!
Next steps:
Learn more about the latest innovation in Azure SQL Managed Instance.
Try SQL MI free of charge for the first 12 months.
Microsoft Tech Community – Latest Blogs –Read More
Improving Threat Hunting Efficiency using Copilot for Security
Setting the Stage
I have a severe case of OCD. For me, I can’t stand doing anything in an inefficient way. For work, as you can imagine, it has its benefits, but there are some drawbacks. These drawbacks can affect work negatively but also can affect my personal life. My wife knows. It bothers me a lot, but even something as simple as the routine of getting out of bed and the steps I take from that point to getting my coffee and sitting down at my desk – if I find a better and more efficient way of doing it, I’ll spend the whole morning fixing it. It can be debilitating.
Threat hunting is the proactive process of proactively searching for hidden cyber threats in a network. Unlike traditional security methods that rely on alerts or signatures, threat hunting involves actively looking for signs of compromise or malicious activity using various tools, techniques, and hypotheses. Threat hunting is an essential practice for enhancing the security posture and resilience of any organization. However, good threat hunting requires experienced personnel. Many Security Operation Centers (SOC) are short staffed and under skilled which leads to deprioritizing threat hunting. Copilot for Security helps immediately upskill staff by using natural language to query disparate tools in the SOC, which would otherwise require specific technical expertise.
Benefits of Threat Hunting
Threat hunting enhances cybersecurity by offering proactive defense against hidden threats, reducing the attack surface through vulnerability discovery, and improving incident response with insights into attack methods. It bolsters the overall security posture by increasing threat awareness and enabling adaptive defenses. Additionally, it aids in compliance and risk management, while also boosting stakeholder confidence through a demonstrated commitment to proactive and mature cybersecurity practices.
Threat hunting can provide many benefits for cybersecurity, such as:
Proactive Defense: Identifies hidden threats that evade existing security solutions.
Reduced Attack Surface: Uncovers vulnerabilities and misconfigurations for remediation.
Improved Incident Response: Speeds up detection and response to incidents by understanding attack techniques and tactics.
Enhanced Security Posture: Increases awareness of the threat landscape and adapts defenses accordingly.
Compliance and Risk Management: Helps meet regulatory requirements by demonstrating proactive efforts to detect and mitigate threats.
Stakeholder Confidence: Improving the trust of the stakeholders, customers, and partners, by demonstrating a proactive and mature approach to cybersecurity.
Challenges of Threat Hunting
Threat hunting faces challenges such as being resource-intensive, requiring costly skilled personnel and tools. The vast data to analyze can lead to overload, and the ever-evolving nature of threats necessitates constant strategy updates. A skill gap exists in the market, making it hard to find professionals for effective threat hunting. Integrating different security tools can be problematic, and measuring the effectiveness and ROI of threat hunting is difficult. Additionally, keeping pace with rapid technological advancements requires ongoing learning and adaptation.
Threat hunting is not without its challenges, such as:
Resource Intensive: Requires skilled personnel and advanced tools, which can be costly.
Data Overload: Massive amounts of data to monitor and analyze can be overwhelming.
Evolving Threats: Constantly changing tactics, techniques, and procedures (TTPs) of attackers require continuous updates to threat hunting strategies.
Skill Gap: Shortage of skilled professionals capable of conducting effective threat hunting.
Integration Issues: Difficulty in integrating various security tools and platforms to streamline threat hunting processes.
Measuring Effectiveness: Challenges in quantifying the success and ROI of threat hunting efforts.
Keeping Up with Technology: Rapid advancements in technology require continuous learning and adaptation.
The Case for Efficiency in Security
Let’s pause for a moment and ask the correct questions to establish the context. What is the reason for efficiency in security? Will efficiency weaken security or enhance it? Have you considered these questions? Are you as troubled about it as I am? And is there really a solution that can fulfill the promise of better security through improved efficiency without any compromise?
I think we can agree that we need to develop a modern response to security threats based on efficiency. As a security analyst or security team, when you are actively hunting or investigating threats in your environment – you are on the clock. Things must happen quickly. You must get to the point of remediation as soon as possible because one intrusion could lead to the next. One compromised account could lead to another – and like a pandemic, exposure can spread uncontrollably unless contained. You’ve probably heard the phrase “superspreader event” in relation to pandemics. If you don’t control an identified threat quickly, it can become a superspreader in a matter of minutes. And, based on the metrics for so many security teams, Mean Time to Acknowledge (MMTA) and Mean Time to Response (MTTR) are critical to evaluating incident management performance and to identify areas for improvement.
Based on surveys and reports, it’s been determined that the average company – listen to this – needs 162 hours to detect, triage, and contain a breach. To me, knowing what I know about Microsoft’s own tools and how efficiency is designed into them, that’s a ridiculous number. But it still rings true for a lot of organizations.
Let’s analyze this number more closely, so we can comprehend what it really means.
The average organization takes…
120 hours to detect an attack.
5 hours to triage.
6 hours to investigate.
31 hours to contain.
Total = 162 hours per incident!
Security Efficiency Goals
If you’ve worked in security for any length of time you have probably heard of the 1-10-60 Rule for cybersecurity, but if not…
About a decade ago, the 1-10-60 rule was proposed as a goal. Not originally a hard-and-fast, set-in-stone rule, but otherwise a goal that we should be able to attain sometime in the future when the tools and technologies have improved enough to get us there. Or, when technology has caught up with our intent.
The idea is that the most cyber-prepared organizations should aim to detect an intrusion in under a minute, perform a full investigation in under 10 minutes, and eradicate the adversary from the environment in under an hour in order to effectively combat sophisticated cyber threats.
Hence: 1-10-60
That’s quite a difference. 162 hours versus 1 hour and 11 minutes? If that’s our goal, we’ve been way off for far too long.
Making it Real
My approach to discussion topics like this one is always based on working with customers. I glean a lot of knowledge working with a large number of customers and based on – admittedly – my OCD, I want to solve their complaints, particularly when it comes to the topic of efficiency. It literally pains me when things aren’t done from an efficient standpoint and I MUST FIX THEM.
These (the following list) are some of the complaints I’ve heard and captured from working with our customers. This list was developed based on their knowledge of working within the confines of their legacy tools. Most organizations have security tools have been historically on-premises software and services and are a mixture of applications that don’t talk to each other.
The list:
Preparedness and hunting are too time consuming.
Continual Tuning and Evolution of SOC is difficult.
Adding Investigative Context Requires Rare Skillsets and Manual Interaction with External APIs.
Locating and Maintaining Trusted Threat Intelligence Sources.
Bottom line: Too much time spent on inefficient processes.
Making it Unreal but Relatable
You might think – hey, let’s just forget about this manual stuff. Let’s let it slide for a while. Or, like some customers have determined as I stated prior (incorrectly, I might add), let’s just stop doing it.
Here’s a great example of this preparedness exercise…
I love Sci-Fi. Michael Crichton is one of the best authors in this genre. He wrote famous stories like Jurassic Park, Westworld, Congo, Timeline, Andromeda Strain, and many more. But the story I like most from Crichton is Sphere. They made a movie out of it with big Hollywood actors like Dustin Hoffman, Sharon Stone, Samuel L. Jackson, and others, but of course the story – the book – is better than the movie.
Here’s how this breaks down…
The government hired a scientist (Dustin Hoffman played the character in the movie) to design a simulation and write a report. The simulation was meant to show what the government should do if we ever encountered aliens or alien technology. The scientist wrote the report and gave it to them – never thinking that the simulation would be useful. He didn’t even believe in aliens himself. He thought he was simply making up a story and getting paid with taxpayer money. But guess what??? It turned out that the Navy was exploring the ocean depths and found alien technology. They wondered – OK what do we do? Oh, yeah…we have instructions for this. So, they dug out that old, hidden, dusty file from whatever neglected storeroom it was in and started following the steps that were written. Suddenly, those suggested as possible team members – based on their different skills – were pulled out of normal life, put on this team, and sent to the bottom of the ocean. Of course, if you remember, the story didn’t end well. If this is your first time hearing this story, it’s a great book – you should read it.
But here’s the lesson: They had a plan. They weren’t caught completely unaware. They – were – (sorta) prepared.
Our preparedness exercise for security is, thankfully, a bit simpler these days. Still important. And it is still critical to security operations. It’s necessary.
Applying Process
The first thing we do is develop a “theory” of what to hunt for. General vertical and targeted company threat intelligence typically influences the theory. It might also be driven from recent information from the information security community, partners, or vendors.
And, ultimately, based on our research and what we learn, we need to answer these questions:
Does it exist? (Are we under active attack?)
Where does it exist? (I need to locate the occurrence in my data – and I need to do it quickly.)
Why does it exist? (Even today, our biggest security threat remains – sadly enough – end-user habits. We can win awards and kudos for securing our devices and software and services – but something a single end-user does can throw a wrench into all of that.)
And, then ultimately, how – of course – will we react? (Very similar to our Sphere story, i.e, what approach will we take?)
Making it Real Again
Here’s a good real-world example of exactly what I’m talking about. Granted, it’s not malware, or ransomware – but it’s guidance from Microsoft on how to stay compliant against a potential threat.
A couple years back, Microsoft released guidance about a series of stage updates to solve an unsecure protocol. We could’ve released a massive update that would solve it immediately, but doing so wouldn’t give customers and partners enough time to get their software and services in a supportable, compatible state. Releasing the full update would break things and people would hate us. Despite what you might think – we care whether people like us or not.
But guess what? Immediately after this announcement a zero-day (called ZeroLogon) was reported that took advantage of this flaw. If the customer had installed the initial update from, they would be fine – but delaying updating the systems – which a lot of customers still do – would open their environment up to compromise.
So, as part of this preparedness exercise, using Microsoft as a trusted source, I used the guidance and indicators provided to work with customers to develop a way in Microsoft Sentinel to monitor for compliant and non-compliant systems.
//Choose which to track (compliance or non-compliance) and remove the comment
//Based on https://support.microsoft.com/en-us/help/4557222/how-to-manage-the-changes-in-netlogon-secure-channel-connections-assoc
SecurityEvent
| join Heartbeat on Computer
//| where EventID == “5829” //Tracking NetLogon Non-Compliance
//| where EventID == “5827” or EventID == “5828” //Tracking NetLogon Compliance
| distinct Computer, OSType, OSMajorVersion, Version
Copilot for Security as a Threat Hunting Tool (or let’s fix my OCD)
Our old methods involved sourcing knowledge for our theory, then generating the correct queries and running them, and then building the response. Our response could be no response at all because the theory (fortunately), didn’t pan out. But no response is still a response that takes active time.
One of the ways to overcome the challenges and improve the threat hunting process is to use Copilot for Security, an artificial intelligence platform that aims to change the way security is done. It addresses the issue of tool fragmentation in the SOC by providing a natural language interface that can reason across an infinite number of first and third party tools. For example, Copilot for Security can leverage data from Microsoft Defender Threat Intelligence (MDTI), Microsoft Sentinel, and ServiceNow, to name a few.
MDTI is a comprehensive platform designed to enhance cybersecurity operations. It streamlines processes such as triage, incident response, threat hunting, vulnerability management, and cyber threat intelligence analysis. MDTI helps security professionals by aggregating and enriching critical data sources, providing an innovative interface for correlating indicators of compromise (IOCs) with vulnerabilities and cyber threats.
The platform is built upon a vast repository of threat intelligence, which is derived from over 65 trillion signals and the expertise of more than 10,000 multidisciplinary security experts worldwide. The Microsoft Threat Intelligence Center (MSTIC) team is a group of experts, security researchers, analysts, and threat hunters at Microsoft. MSTIC tracks over 70 code-named government-sponsored threat groups, including Russian hackers (code-named Strontium), North Korean hackers (code-named Zinc), and Iranian hackers (code-named Holmium)1. Their mission is to stay ahead of threat actors and defend against cyberattacks.
This work and intelligence enable security teams to identify vulnerabilities more effectively and stay ahead of cyber threats. Additionally, Microsoft MDTI integrates with Microsoft Copilot for Security, allowing the use of natural language queries to summarize investigations and explore built-in threat intelligence.
Microsoft Security Copilot can significantly enhance the efficiency of threat hunting in several ways:
Assists in building hunting theories through its ability to reason over MDTI. Copilot for Security provides expertise at the user’s fingertips to quickly build impactful hunting theories.
Improves the speed and efficiency for security teams, allowing them to respond to threats faster. In a randomized control trial, using Copilot for Security improved security response time by up to 26%.
Enhances the quality of responses through the connection of endpoints, cloud services, and external threat intelligence feeds, and enriching it with contextual and behavioral information. Security novices and analysts using Copilot for Security performed better and expressed more confidence in their work compared to those who didn’t use it. A high percentage of participants noted that it helped improve the quality of their work.
Reduces resistance or skepticism by providing clear and actionable insights into the value and impact of threat hunting, such as the number and severity of threats detected, and the risk reduction achieved.
Offers considerable time savings in capturing and consolidating attack data, reducing the time spent on these tasks by 90%, as reported by a Principal Research Lead for Microsoft Defender Experts. 1
Enables organizations to add threat hunting to their security processes by offering a user-friendly and intuitive interface that guides security analysts through the different stages of threat hunting, from defining hypotheses, to querying and analyzing data, to validating threats.
Empowers security teams to perform proactive threat hunting by using artificial intelligence and automation to generate smart hypotheses, suggest relevant queries, prioritize and score threats, and recommend remediation actions.
Alleviating tedious tasks and it empowers senior staff to focus on strategic priorities and strengthens the expertise of junior staff through step-by-step guidance.
Quickly upskill junior staff on otherwise technically involved processes such as building KQL queries.
Copilot for Security can help organizations to transform their security posture from reactive to proactive, and to achieve higher levels of security maturity and resilience. Organizations can benefit from the advantages of threat hunting without the drawbacks, and gain more visibility, control, and confidence over their network and system security. Overall, Microsoft Copilot for Security represents a leap forward in the realm of cybersecurity, enabling teams to protect their systems with greater precision and at machine speed.
Bottom line: Copilot for Security is the next level in the ongoing story to resolve efficiency in security and help eliminate my OCD in this area.
TLDR
Threat hunting is the process of proactively searching for hidden cyber threats that evade traditional security solutions. It is a vital activity for any organization that wants to protect its data and assets from sophisticated attackers. However, threat hunting is also a challenging and time-consuming task that requires a high level of skill and expertise. Many security teams struggle with the problem of inefficiency in threat hunting, which can result in missed or delayed detection of threats, wasted resources, and increased risk.
Copilot for Security is the next level in the ongoing story to resolve efficiency in security. It is a solution that can help organizations overcome the challenges of threat hunting and achieve better security outcomes.
EXTRA: Learning to develop good prompts is also a very important aspect of building better efficiency using Copilot for Security. See: Get the most out of Microsoft Copilot for Security with good prompt engineering
1 Microsoft Copilot for Security provides immediate impact for the Microsoft Defender Experts team https://www.microsoft.com/en-us/security/blog/2024/02/08/microsoft-copilot-for-security-provides-immediate-impact-for-the-microsoft-defender-experts-team/
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The AI Study Guide: #MarchResponsibly with AI
Hi! It’s me, Natalie, your Azure AI Skilling Guru. Want to learn something about Azure AI or ML? We’ve got something for that!
Welcome to the March edition of the Azure AI Study Guide. Every month I’ll bring you the best and newest tools when it comes to skilling up on Azure AI. This month, I’m partnering with my friend and Microsoft Cloud Advocate Ruth Yakubu for a #MarchResponsibly campaign – educating AI and Machine Learning enthusiasts about responsible AI.
Join us for this month-long celebration of data science, machine learning and artificial intelligence. You will see a series of blog posts that will cover the tools, technologies, and social impact, of responsible AI. Let’s #MarchResponsibly together. As part of this blog series, we’ve curated the best of Microsoft’s learning resources so you can build and test fair AI solutions.
I’ve brought in a mix of videos, learning modules and tutorials that will give you a great foundation for deploying AI solutions responsibly.
Let’s get started!
What is responsible AI and why is it important?
Responsible AI is an approach to developing, assessing, and deploying AI systems in a safe, trustworthy, and ethical way. This means putting values such as fairness, reliability, and transparency in the middle of our system design decisions. Responsible AI technology ensures that your AI systems are designed, developed, and deployed in a responsible and fair manner. If you’re interested in learning more about Microsoft’s responsible AI practices, see the home page here.
The Basics
Before we dive into technical skills, I suggest starting with these overviews:
Embrace responsible AI principles and practices module: In this quick module (50 minutes) you’ll get an overview that’s fit for anyone, whether you’re a developer or a business leader (or both!).
Fundamentals of Responsible Generative AI: This module is a hot item – in under an hour you’ll get prepared to deploy and operate a generative AI solution responsibly.
I also really enjoyed this three-part blog series that dives into the basics and the tools you need to get started:
Responsible AI in action, Part 1: Get started
Responsible AI in action, Part 2: Complete an impact assessment
Responsible AI in action, Part 3: Tools to help
The HAX Toolkit is an awesome resource for teams building user-facing AI products. It’s all about creating human-centered AI experiences and testing your protypes early on.
Responsible AI tools to debug models on Azure Machine Learning
Module: In this FREE 60 minutes hands on lab module, you’ll learn how to use the Responsible AI Dashboard (one of the tools reviewed above) with Azure Machine Learning to debug models and make data-driven decisions. Here’s a quick video to give you an idea of the capabilities and functionality of the dashboard.
GitHub Repository: This repo feeds into the module above and includes even more learning opportunities to explore multiple datasets and debug them.
Responsible AI Mitigation and Tracker. This toolkit helps AI Engineers explore mitigation steps needed to interactively track and compare mitigation experiments. It enables data scientists to see where the model has improved and whether there are variations in performance for different data cohorts (subgroups).
Responsible AI Toolbox: Finally, a suite of tools just for AI and ML practitioners! In this toolbox you’ll get a review of 4 different tools (including the Responsible AI Dashboard) for model assessment and decision making resulting in a customized, end to end responsible AI experience. For a nice review plus a knowledge check, I recommend the toolbox landing page.
SmartNoise SDK Toolkit: This toolkit is new to me and I’m so glad my colleagues shared it. This differential privacy toolkit is for analytics and machine learning. It injects noise into data to prevent disclosure of sensitive information. How cool is that? Click “Get Started” on the home page to access the GitHub page.
Responsible AI and Azure AI Studio
First, review the fundamentals of responsible generative AI module linked above.
I also recommend the Introduction to Azure AI Studio module (less than 1 hour) to get oriented in Azure AI Studio since we are going to be focusing here a lot.
Next, let’s check out this awesome blog series by our own Sarah Bird. She gives an amazing overview of Azure AI Content Safety and how it can be used within the new Azure AI Studio.
Sarah Bird also joined Seth Juarez on his AI Show – check out their quick 25 minute video visual overview and demo of Azure AI Content Safety.
The next video in the series dives into the how to use Azure AI Studio to evaluate your app’s performance.
This tutorial will give you a guided experience in trying your hand at the prompt flow Content Safety tool in Azure AI Studio.
You can also always check out my friend Ruth’s Microsoft Learn collection for more tips and tricks on responsible AI.
And as always, keep an eye on the Microsoft Learn AI Hub for the latest learning opportunities for teams and individuals.
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How to Build Trustworthy AI Systems with Responsible AI
AI is transforming the world in many ways, but it also comes with many challenges and risks. How can we ensure that our AI systems are safe, reliable, and ethical? How can we debug and mitigate issues such as biases, errors, and unfairness? How can we communicate the impact and limitations of our AI solutions to our stakeholders and customers?
If you are a technical student who wants to learn how to build trustworthy AI systems, you should check out this upcoming series of events hosted by Microsoft Reactor: Building trustworthy AI systems with Responsible AI Toolbox.
This series will introduce you to the Responsible AI Toolbox, a suite of tools and functionalities that help you operationalize responsible AI in practice. You will learn how to use various tools to identify, diagnose, and mitigate issues associated with your AI models. You will also learn how to create visual executable flows that link language models, vector embeddings, prompts, and Python tools. Moreover, you will learn how to use the Responsible AI Dashboard, a single pane of glass that brings together several mature Responsible AI tools for a holistic responsible assessment and debugging of models and making informed business decisions.
The series consists of two events, each lasting one hour:
Azure ML prompt flow on Thursday, March 7, 2024 at 3:30 PM UTC
Responsible AI dashboard on Wednesday, March 13, 2024 at 3:30 PM UTC
The events will be livestreamed and delivered in English. The speakers are Ruth Yakubu, Principal Cloud Advocate at Microsoft, and Vinayak Hegde, CTO-in-Residence at Microsoft for Startups.
To register for this series, you need to sign in with your Microsoft Account or enter your email address here. By registering, you agree to abide by the Microsoft Reactor Code of Conduct.
Don’t miss this opportunity to gain a strategic advantage by minimizing risks associated with your AI services, earning the trust of investors, B2B customers, and end users. This series will equip you to address regulatory compliance concerns and showcase responsible AI practices crucial for success in the evolving AI landscape.
Learn more about responsible AI principles and practices:
Embrace responsible AI principles and practices – Training | Microsoft Learn
Skill up on Responsible AI Developer Hub | Responsible AI Developer Hub
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Enrich your Data Estate with Fabric Pipelines and Azure OpenAI
The benefits of Generative AI is of huge interest for many organisations and the possibilities seem endless. One such interesting use case is the ability to leverage Azure OpenAI models in data pipelines to create or enrich existing data assets.
The ability to integrate Azure OpenAI into Fabric data processing pipelines enables numerous integration scenarios to either create new datasets or augment existing datasets to support downstream analytics. As a simple example, a generative AI natural language model could be used to gather additional information about zip codes such as demographics (population, occupations etc) and this could in turn be ingested and conditioned to enrich the data.
The following example demonstrates how Fabric pipelines can be integrated with Azure OpenAI using the pipeline Web activity whilst also leveraging Azure API Management to provide an additional management and security layer. I am a big fan of API Management in front of any internal or external API services due to capabilities such as authentication, throttling, header manipulation and versioning. Further guidance on Azure OpenAI and API Management is described here Build an enterprise-ready Azure OpenAI solution with Azure API Management – Microsoft Community Hub.
The Fabric pipeline and Azure OpenAI flow is as follows:
Extract data element from Fabric data warehouse (in this case, this is ‘zip code’)
Pass the value into an Azure OpenAI natural language model (GPT 3.5 Turbo) via Azure API Management
The GPT 3.5 Turbo model (which understands and generates natural language and code) returns information, back to the Fabric pipeline, based on the zip code; in this example population information is returned to the Fabric pipeline where the data can either be further processed and persisted to storage.
Fabric pipelines provide excellent range of integration options. The Web activity, coupled with dynamic processing in Fabric, is extremely powerful Web activity – Microsoft Fabric | Microsoft Learn and enables a range of API calls (GET, POST, PUT, DELETE and PATCH) to web services. Please note, the same functionality can be achieved in Azure Data Factory pipelines.
The diagram below illustrates the simple Fabric pipeline flow and activities.
Figure 1.0 Microsoft Fabric Pipeline integrating Azure OpenAI
The initial Script activity extracts a source data attribute, in this case a zip code, from the Fabric OneLake data warehouse. The output is persisted in a parameter varQuestionParameter. In this example, an intermediate variable is used for debugging purposes and can be removed later if needed.
The pipeline Web activity is easily configured using a POST method (to the Azure OpenAI natural language model) via API Management using an APIM subscription key, API key and Content-Type as shown below.
Figure 2.0 Microsoft Fabric Pipeline Web Activity configuration
The body of the API POST is dynamically constructed using parameters as shown below.
Figure 3.0 Microsoft Fabric Pipeline Web Activity dynamic content
Dynamic expressions in Fabric pipelines are incredibly powerful and allow run-time configuration of activities, connections and datasets.
In the example shown above, max_tokens is a configurable parameter which specifies the maximum number of tokens (segmented text strings) that can be generated in the chat completion. Occasionally it is necessary to increase the value. For example, consider setting the max_token value higher to ensure that the model does not stop generating text before it reaches the end of the message.
In contrast, (sampling) temperature is used to control model creativity. A higher temperature (e.g., 0.7) results in more diverse and creative output, while a lower temperature (e.g., 0.2) makes the output more deterministic and focused. Examples of values and definitions can be found here Cheat Sheet: Mastering Temperature and Top_p in ChatGPT API – API – OpenAI Developer Forum.
The output of the model is passed back to the Fabric Web Activity which can then be persisted in the Fabric OneLake or other storage destination. This is just a simple example demonstrating how easy it is to introduce Generative AI scenarios into data integration pipelines.
Please post if you have questions/comments, or if you are exploring data pipeline and generative AI integration scenarios to enable new insights.
References
Fabric Pipelines Ingest data into your Warehouse using data pipelines – Microsoft Fabric | Microsoft Learn
Fabric Pipelines vs. Azure Data Factory Differences between Data Factory in Fabric and Azure – Microsoft Fabric | Microsoft Learn
Azure OpenAI Service Models Azure OpenAI Service models – Azure OpenAI | Microsoft Learn
Azure OpenAI and API Management Build an enterprise-ready Azure OpenAI solution with Azure API Management – Microsoft Community Hub.
Azure Architecture Center Azure Architecture Center – Azure Architecture Center | Microsoft Learn
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RAG techniques: Cleaning user questions with an LLM
When I introduce app developers to the concept of RAG (Retrieval Augmented Generation), I often present a diagram like this:
The app receives a user question, uses the user question to search a knowledge base, then sends the question and matching bits of information to the LLM, instructing the LLM to adhere to the sources.
That’s the most straightforward RAG approach, but as it turns out, it’s not what quite what we do in our most popular open-source RAG solution, azure-search-openai-demo.
The flow instead looks like this:
After the app receives a user question, it makes an initial call to an LLM to turn that user question into a more appropriate search query for Azure AI search. More generally, you can think of this step as turning the user query into a datastore-aware query. This additional step tends to improve the search results, and is a (relatively) quick task for an LLM. It also cheap in terms of output token usage.
I’ll break down the particular approach our solution uses for this step, but I encourage you to think more generally about how you might make your user queries more datastore-aware for whatever datastore you may be using in your RAG chat apps.
Converting user questions for Azure AI search
Here is our system prompt:
Below is a history of the conversation so far, and a new question asked by
the user that needs to be answered by searching in a knowledge base.
You have access to Azure AI Search index with 100’s of documents.
Generate a search query based on the conversation and the new question.
Do not include cited source filenames and document names e.g info.txt or doc.pdf in the search query terms.
Do not include any text inside [] or <<>> in the search query terms.
Do not include any special characters like ‘+’.
If the question is not in English, translate the question to English
before generating the search query.
If you cannot generate a search query, return just the number 0.
Notice that it describes the kind of data source, indicates that the conversation history should be considered, and describes a lot of things that the LLM should not do.
We also provide a few examples (also known as “few-shot prompting”):
query_prompt_few_shots = [
{“role”: “user”, “content”: “How did crypto do last year?”},
{“role”: “assistant”, “content”: “Summarize Cryptocurrency Market Dynamics from last year”},
{“role”: “user”, “content”: “What are my health plans?”},
{“role”: “assistant”, “content”: “Show available health plans”},
]
Developers use our RAG solution for many domains, so we encourage them to customize few-shots like this to improve results for their domain.
We then combine the system prompts, few shots, and user question with as much conversation history as we can fit inside the context window.
messages = self.get_messages_from_history(
system_prompt=self.query_prompt_template,
few_shots=self.query_prompt_few_shots,
history=history,
user_content=”Generate search query for: ” + original_user_query,
model_id=self.chatgpt_model,
max_tokens=self.chatgpt_token_limit – len(user_query_request),
)
We send all of that off to GPT-3.5 in a chat completion request, specifying a temperature of 0 to reduce creativity and a max tokens of 100 to avoid overly long queries:
chat_completion = await self.openai_client.chat.completions.create(
messages=messages,
model=self.chatgpt_model,
temperature=0.0,
max_tokens=100,
n=1
)
Once the search query comes back, we use that to search Azure AI search, doing a hybrid search using both the text version of the query and the embedding of the query, in order to optimize the relevance of the results.
Using chat completion tools to request the query conversion
What I just described is actually the approach we used months ago. Once the OpenAI chat completion API added support for tools (also known as “function calling”), we decided to use that feature in order to further increase the reliability of the query conversion result.
We define our tool, a single function search_sources that takes a search_query parameter:
tools = [
{
“type”: “function”,
“function”: {
“name”: “search_sources”,
“description”: “Retrieve sources from the Azure AI Search index”,
“parameters”: {
“type”: “object”,
“properties”: {
“search_query”: {
“type”: “string”,
“description”: “Query string to retrieve documents from
Azure search eg: ‘Health care plan'”,
}
},
“required”: [“search_query”],
},
},
}
]
Then, when we make the call (using the same messages as described earlier), we also tell the OpenAI model that it can use that tool:
chat_completion = await self.openai_client.chat.completions.create(
messages=messages,
model=self.chatgpt_model,
temperature=0.0,
max_tokens=100,
n=1,
tools=tools,
tool_choice=”auto”,
)
Now the response that comes back may contain a function_call with a name of search_sources and an argument called search_query. We parse back the response to look for that call, and extract the value of the query parameter if so. If not provided, then we fallback to assuming the converted query is in the usual content field. That extraction looks like:
def get_search_query(self, chat_completion: ChatCompletion, user_query: str):
response_message = chat_completion.choices[0].message
if response_message.tool_calls:
for tool in response_message.tool_calls:
if tool.type != “function”:
continue
function = tool.function
if function.name == “search_sources”:
arg = json.loads(function.arguments)
search_query = arg.get(“search_query”, self.NO_RESPONSE)
if search_query != self.NO_RESPONSE:
return search_query
elif query_text := response_message.content:
if query_text.strip() != self.NO_RESPONSE:
return query_text
return user_query
This is admittedly a lot of work, but we have seen much improved results in result relevance since making the change. It’s also very helpful to have an initial step that uses tools, since that’s a place where we could also bring in other tools, such as escalating the conversation to a human operator or retrieving data from other data sources.
To see the full code, check out chatreadretrieveread.py.
When to use query cleaning
We currently only use this technique for the multi-turn “Chat” tab, where it can be particularly helpful if the user is referencing terms from earlier in the chat. For example, consider the conversation below where the user’s first question specified the full name of the plan, and the follow-up question used a nickname – the cleanup process brings back the full term.
We do not use this for our single-turn “Ask” tab. It could still be useful, particularly for other datastores that benefit from additional formatting, but we opted to use the simpler RAG flow for that approach.
Depending on your app and datastore, your answer quality may benefit from this approach. Try it out, do some evaluations, and discover for yourself!
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Using Power Automate for Project Lifecycle Workflows in Project Online – Part 1
Background to the requirement to move to Power Automate
SharePoint 2013 Workflows, the workflow technology used in SharePoint and Project Online is being d (https://support.microsoft.com/en-us/office/sharepoint-2013-workflow-retirement-4613d9cf-69aa-40f7-b6bf-6e7831c9691e. ) At around the same time SharePoint Designer 2013, the only tool to easily manage Project Server workflows (they are called that, even in Project Online), is being deprecated(actually reaching end of life). Although this is a little way off – there is another date to be aware of and that is April 2024, when new tenants in M365 will not have SharePoint 2013 workflows available. This does not impact existing tenants who add a new PWA, or even add Project Online to an existing tenancy – just net new M365 customers. The expectation is that most of these would not be familiar with, and so not miss, the ‘current’ workflow technology.
This article describes ways customers can obtain similar functionality to the current workflows by using Power Automate and concentrates on the flow through the stages and a potential way to record workflow status. Although it may not give a 1 to 1 match in functionality – Power Automate can go way beyond what is possible in Project Online today.
Starting a workflow
The role of workflow in Project Online has always been to gather information about the project, usually populating some of this information into custom fields, then control the project lifecycle through its phases and stages, again gathering or displaying information along the way.
In Power Automate there are project related triggers for Project Creation and Project Publishing. (There are also Task and Resource related triggers – which could be used for functionality beyond what has previously been possible). In this article I will concentrate on the When a new project is created (V2) although it may be that the When a project is published (V2) trigger may also be useful at certain points in a larger workflow. An example I’m thinking of (untried) is using the publish trigger to enable an existing workflow that has become disabled due to exceeding a 30 day run period. It could be that a trigger totally outside project could also be used.
Companies could well have many EPTs, and many different workflows used across them – so an initial challenge would be to identify which workflow should run when a project is created. The most straightforward way, but inefficient, is to have all the workflows triggered on create then each look to see if the specific project needs that workflow to run – checking ‘is this for my EPT?’.
I will start with this approach, will enable the create trigger to check for a property value (EPT) before starting – which would be much more efficient.
of a skeleton workflow (that doesn’t really do anything) is shown first, then I’ll walk through the detail of each step, then look at how the stages might be driven. Most of the work is in the Condition action – I’ll open that up later.
Initializing Variables
In this example the create trigger then initializes a variable IsWorkflowCompleted to false. This variable can then be set to true when the workflow is complete (checked in the Do Until section).
Several other variables are also initialized that get used later. Power Automate needs all the initialize options at the top level.
Get the Enterprise Project Type (EPT)
After the initializations a SharePoint REST call is used to get the EPT details. This action is Send an HTTP request to SharePoint and isn’t a Premium action – so is used in favor of the HTTP Request action. The action uses the site address of the PWA site, a GET method and the Uri field adds _api/ProjectServer/Projects(‘@{triggerOutputs()?[‘body/ProjectId’]}’)/EnterpriseProjectType to the site – hence making a call to Project Online’s REST endpoint, with the GUID of the project inserted that is available from the trigger outputs.
This is then parsed to make the elements of the response available. To use the Generate from sample option to get the json schema – I simply ran a flow that performed the above action – then pulled the body from the output as my sample.
In the Parse JSON action click the Generate from sample and paste in the body json and click Done.
This then gives you a parsing action like this:
Now you have the parsed json, the name will be available to check if the project that triggered the flow was created using the EPT we are interested in.
Is this the EPT we were looking for?
A Condition action can then be used to compare the name of the EPT from the parsed json to our target EPT, in this case called FlowEPT. If it isn’t the same, then we are ending the workflow down the no path. Setting the IsWorkflowCompleted doesn’t really do anything in this case and could be left out.
If the name is FlowEPT then we take the ‘yes’ path, pull together some details from the workflow runtime by getting the runtime details and parsing it (not used for anything special in this case but could be useful for re-enabling later) then set some variables with key details from the runtime.
Set up our Project Status list
In this example a SharePoint list is used to keep status information of the workflow and progress. It might make more sense to use Dataverse in the real world, as the list could be manipulated more easily outside of the workflow. The list is already created, called WorkflowStatus, and has columns for Stage, Status, Additional and Project Name. The list items are initialized by the following flow actions, which are SharePoint Create item actions.
The idea would be to add this list also to the Project Detail Page, filtered for the specific project (TBD), so that workflow progress could be tracked as it is for the current Project Online workflows.
Stepping into the State Engine
Once these steps are completed, we are ready to roll, and enter a Do Until loop that completes when IsWorkflowCompleted is set to true, but will also become disabled after 30 days, which is a Power Automate limit. More on this later (might be much later, in a future part). The Switch handles what happens within each stage.
Looking at the first stage in the Switch, Propose, we first pull out the requester e-mail address, by making a SharePoint REST call to get the project’s owner’s properties.
Parsing the resulting body so we can pull out the e-mail address:
Updating the list item to say that the proposal is Waiting for Submission. This uses the SharePoint Update Item action, using the ID output from the Initialize_stage_Propose action made earlier)
Get Approval to submit the Proposal
The submission form itself is handled using a Start and wait for approval action, into which we put the e-mail it is going to and a link to the project itself:
This will put an Approval into the Power Automate Approvals page, like this example:
As well as sending an e-mail to the approver:
It can be approved in either place. Once approved, the list item is updated again, using the SharePoint Update Item action, to show the Propose stage has been completed – and the time of submission is also put into the list.
Switch to the next Stage
The final part of the Propose stage sets the WorkflowStage to Review using an Set variable action – so that the switch takes us to the next column of actions
The Review stage in total looks like this – with some updates to the status table and another approval check, which if the response is to revise the request is sent back to the Propose stage – otherwise the workflow moves to Finished and concludes.
Stage Status Updates
Let’s look deeper at the individual steps. The first it to update the stage status, using the now familiar SharePoint Update Item action – and we set the status to Waiting for Review.
Sending for Review
The review of the proposed project is sent out to a named user in this case, Megan, with options to Approve, Revise & Resubmit or Reject. An item link is again constructed to be a link to the project. As before, this uses a Start and wait for approval action, this time waiting for all responses (even if in this case there is just Megan):
Megan also sees the approvals both in her e-mail and the Approvals page in Power Automate, and can return the workflow to propose for revision, approve it or reject it:
Receive and format Review Response
Once the review is actioned, the next step formats the response from the approval step and adds to the Workflow Status list. In this case we take the Responses and format an HTML table, which the following step will put into our status list:
The Output from this step goes into the column called Additional in the Edit item step next:
An example of the Workflow status list, for a project that has been sent back for revision before finally being approved is below:
Are we there yet?
Finally in this stage, a condition action is used, to set the next appropriate stage – Propose, if the approval suggested revision was needed, or Finished if it was either Approve or Reject.
If it goes back to Propose it just goes around the loop again, if it goes to Finished then the IsWorkflowCompleted is set to true (which will break out of the Do Until at the end of the cycle) and the SharePoint Edit item is used again to update the status to Completed.
The Workflow Status list can be added to the Project Details PDP, so that it is available much the same as the existing workflow has its lists. Currently this list would contain all statuses for all projects so would need to be filtered. Feels like a new web part that can filter down to the project (by GUID) to make this easier.
Closing Statement
Wow, that’s a lot to take in, and more coming in a ‘Part 2’ soon, to talk over some ways of using Power Automate, Teams and Adaptive Cards to gather data for custom fields in Project Online, during the workflow. I’m sure there will be further parts after that too. What do you want to hear about?
We would also love to hear from you on how you feel this would work for you – or if you are a partner, your customers. Are you already doing something much better than this? We’d love to hear that too. As mentioned earlier, we do have some plans for investment on the engineering side to make some of these steps easier and more efficient – feedback from you will help focus this investment. Either comment here, or reach out to us at PJOQueries@microsoft.com and let us know
For customers who believe the above approach using Power Automate is not addressing their requirements, and are seeking extension of workflows for genuine scenarios, also please reach out to us on PJOQueries@microsoft.com
Thanks to Divya Tiwari for the original concepts for these workflows, and also to Ramesh Maruthupandiyan (both of whom will be eager to get your feedback at the above addresses) and Jason Rhoades for feeding in his real-world experiences.
Microsoft Tech Community – Latest Blogs –Read More
Marketplace Rewards: Your Key to Growing Sales and Scaling Impact
In a recent webinar with the Microsoft Marketplace Rewards team, Luxmi Naragaj – Senior Technical Program Manager, and Brady Bumgarner – Senior Business Program Manager, delved into the benefits and impact of participating in Marketplace Rewards and utilizing our new app advisor on the ISV Hub. These insights shed light on how these resources can significantly contribute to growing your sales and scaling your impact on the Microsoft commercial marketplace.
Let’s start with Marketplace Rewards. Marketplace Rewards provides marketing and sales benefits to ISVs who have published a transactable offer in the commercial marketplace. Our data shows partners can experience up to 5x higher billed sales when utilizing Marketplace Rewards benefits vs not using any program benefits. Partners who take advantage of the Azure Sponsorship benefit have seen up to 40% YoY growth vs partners who are not taking advantage of the Azure Sponsorship benefit.
ISVs participating in Marketplace Rewards take advantage of a tiered set of benefits which provide marketing and sales support to partners who have published a transactable offer on the Marketplace. Additional benefits are unlocked based on the ISVs marketplace performance measured by billed sales, for Teams App partners the tiering is based on monthly active usage, and for business application solution partners it is the total solution value. sales. The higher your performance, the more benefits you unlocked.
Some of the benefits Marketplace Rewards provides based on your tier are:
Dedicated engagement manger to help optimize your offer and execute marketing and sales benefits
Social and blog promotion
Listing optimization services
Guest blog posts and Solution spotlight
Seller webinars
Free Azure grants starting at $2,000 and up to $400,000 ISVs can use to fund trials, test drives, POCs and to close deals with customers
Additional benefits available Teams, Business Applications and MISA partners
And many more!
It is easy to get started
Join Microsoft AI Cloud Partner Program
Evaluate the marketplace options and publish your offer in Microsoft AppSource or Azure Marketplace
Within 3 weeks of publishing your offer, our team will email you to get started.
Email rewards@microsoft.com if invitations was missed or with questions on how to engage and start receiving sales & marketing benefits.
We are excited to announce that app advisor has launched on the ISV Hub. It is a self-serve web experience that gives ISVs tailored guidance, curated content, and actionable steps to build, publish and grow their apps on the Microsoft cloud and marketplace. App Advisor is designed to help you go to market faster and grow your business by giving you quick access to top tools, resources, and technical specialists to assist you throughout your app journey and it is available to ALL ISV’s.
Register to watch the Growing Sales and Scaling Impact with Marketplace Rewards webinar to learn more about Marketplace Rewards and see a demo of app advisor and start realizing the benefits of both today!
Have follow up questions about this presentation’s content? Comment below to continue the conversation with our subject matter experts!
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Additional Resources
App advisor | Microsoft ISV Hub
Marketplace Rewards | ISV Hub | Microsoft
Welcome to the Microsoft AI Cloud Partner Program
Microsoft AppSource – destination for business apps
Microsoft Tech Community – Latest Blogs –Read More