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Modernizing Legacy Applications to Microsoft Azure

Modernizing Legacy Applications to Microsoft Azure

By : Steve Read, Larry Mead
5 (3)
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Modernizing Legacy Applications to Microsoft Azure

Modernizing Legacy Applications to Microsoft Azure

5 (3)
By: Steve Read, Larry Mead

Overview of this book

Organizations have varying circumstances, objectives, and prerequisites when contemplating a hyper-scale cloud solution transformation to a platform such as Azure. Modernizing Legacy Applications to Microsoft Azure uncovers potential scenarios and provides choices, methodologies, techniques, and prospective possibilities for transitioning from legacy applications to the Microsoft Azure environment. You’ll start by understanding the legacy systems and the main concerns regarding migration. Then, you’ll investigate why distributed architectures are compelling and the various components of the Azure platform needed during migration. After that, you’ll explore the approaches to modernizing legacy applications and the Rs of modernizing (i.e., rehost, refactor, rearchitect, and retire). You’ll also learn about integration approaches and potential pitfalls. By the end of this book, you’ll be well equipped to modernize your legacy workloads while being aware of pitfalls and best practices.
Table of Contents (18 chapters)
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1
Part 1: Legacy Estate Options
3
Chapter 2: Strategies for Modernizing IBM and Unisys Mainframes
6
Part 2: Architecture Options
10
Part 3: Azure Deployment and Future Considerations

Why are born-in-the-cloud applications not typically monoliths?

Azure can support both monolithic and cloud-native architectures. This section will look at both approaches, keeping in mind that cloud native is the preferred approach if possible.

Can you migrate a monolith to Azure?

The simple answer is yes. Azure provides VMs with the following capabilities that can handle monoliths in a scale-up architecture:

  • Over 400 vCPUs for applications that can take advantage of multiple CPUs
  • Compute-optimized VMs to provide fast clock speed or memory
  • High input/output operations per second (IOPS) and data throughput for batch applications
  • Proximity placement groups that allow minimal latency between VMs

With these capabilities, Azure can handle most mainframe workloads easily for both scalability and performance without taking advantage of Azure cloud-native features.

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