Designing Microsoft Azure Infrastructure Solutions

Designing Microsoft Azure Infrastructure Solutions
This webinar teaches Azure Solution Architects how to design infrastructure solutions. Session topics cover governance, compute, application architecture, storage, data integration, authentication and identity, networks, high availability, business continuity, and migrations. The 1-hour session will combine lecture with case studies to demonstrate basic architect design principles.
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Spotlight

OTHER ON-DEMAND WEBINARS

The Role of AI Chatbots for Next-Generation E-commerce Users

E-commerce transactions are expected to hit around $112 billion in less than two years and given how the pandemic has been a catalyst in forcing businesses to find their online footing, brands need to better equip themselves when it comes to providing a delightful customer support experience.
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Stand Out With Video: Invest In These Technologies To Drive Growth and Revenue

Vidyard

It's also become a preferred way for buyers to learn about new products and services. That's why across industries, video is increasingly critical for engaging, inspiring, and building trust with prospects and customers. But video content on its own isn't a solution, you need the right technology to help you efficiently scale your use of video while optimizing your content for customer acquisition and revenue growth.
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Future-proofing IT for the Hybrid Workforce

"Good-enough" IT architecture for remote workers isn't good enough anymore. To support a permanently hybrid workforce, enterprise leaders need to ask themselves tough questions: Do you simply add "must have good broadband" to job listings, or can IT departments redesign their network architecture to accommodate talent wherever it resides? Are you using employee monitoring and productivity tools responsibly, or are they violating privacy? In this Interop event, learn the latest in hybrid work trends including new technologies to better observe, support and defend your users, wherever they choose to work.
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Take AI/ML models to production faster by bringing performance & productivity to your MLOps

According to industry analysts, more than 85% of artificial intelligence (AI) deployments never make it into production. Moving from research (using small data sets) to robust online production environments is far from trivial. Production environments need to process large amounts of real-world data and meet application performance and SLA goals. To bring AI projects from the lab to production, organizations need a production-first mindset. They also need underlying infrastructure built for scale and high performance.
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