Many businesses have questions about how to optimize Microsoft Azure. Microsoft IT is moving the bulk of our computing resources to Azure, and the environment requires constant evaluation and optimization. We’ve set standards to manage resources, identify underutilized and noncompliant workloads, and to retire those that are unused. We employ a few tools—some analytic, and some automated—to implement changes to our environment that help us reduce our costs and our utilization footprint.
To better manage and secure our Microsoft Azure resources, Microsoft IT created an Azure asset inventory that provides a consolidated view of all the Azure subscriptions and resources at Microsoft. Key data in the inventory helps us analyze Azure resources and configurations to optimize the environment and ensure compliance. Having the ability to analyze the Azure resource inventory for resource and configuration data has helped reduce costs, improve security, reduce risk, and manage resource ownership.
For Microsoft IT, conventional processes for managing Microsoft Azure resources weren’t providing good visibility into self-provisioned cloud usage. To overcome this challenge, we created and maintain an inventory of the Azure subscriptions and resources across the enterprise. It includes detailed resource and usage records for resource management and auditing. With the inventory, we developed a system for Azure usage management that helps us realize efficiency and value from our Azure resources.
Meeting company sales targets and accurately forecasting sales revenue are critical to the success of Microsoft and our customers. To help sales teams make informed decisions and accelerate opportunities, Microsoft IT uses predictive analytics models, Azure Machine Learning, and algorithms like latent semantic analysis and regression analysis. These models don’t replace human judgment—they augment it with seller feedback and ongoing model retraining, which result in analytics-based insights.
For workplace comfort, the equipment in cooling and heating facilities needs to work properly. Accurately predicting when this expensive equipment is likely to fail helps lower operational costs and increase efficiency. It’s also important to reduce the carbon footprint and save energy. The Real Estate and Facilities organization in Microsoft and Microsoft IT use data analytics, smart buildings, the Internet of Things, and Azure Machine Learning for predictive maintenance, climate control, and HVAC optimization.
With migration to Azure, it’s important that Microsoft IT ensure network connectivity between on-premises and virtual resources across our environment. To do so, we’ve been using Azure ExpressRoute circuits as part of our network topology. For management of ExpressRoute, we’ve moved to a shared circuit model—business groups access some networking components, but we provision and manage ExpressRoute networking services in a simplified and centralized way. As a result, we’ve reduced overhead and optimized bandwidth.
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