AWS Partner Network (APN) Blog

Category: Migration and Transfer

Turbonomic_AWS Solutions

Save on Your AWS Spend with Enterprise Cloud Migration and Infrastructure Management from Turbonomic

Migrating workloads to the cloud and adopting infrastructure management allows businesses to leverage the scalability and rapid innovation of AWS. Turbonomic’s autonomic platform collects usage data from applications and processes it using AI, making full stack aware decisions across available compute, storage, and database resources without user intervention. In this post, learn how a Fortune 500 company achieved migration milestones and reduced their AWS spend by 40 percent using Turbonomic.

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How Cloud Backup for Mainframes Cuts Costs with Model9 and AWS

Mainframe cold storage based on disks and tapes is typically expensive and rigid. Model9 improves the economics and flexibility by leveraging AWS storage for archival, backup, and recovery of mainframe data. Model9 enables mainframe customers to leverage modern cloud technologies and economics to reduce data recovery risks and improve application availability by providing a software-defined solution for archive, backup, and recovery directly from AWS.

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AWS Big Data

Reinventing Relational Data Management Using AWS Big Data Services

Today’s businesses deal with many different varieties of data, including structured datasets stored in various repositories like a relational databse management system (RDBMS) or enterprise resource planning (ERP); semi-structured datasets like web logs and click-stream datasets; and unstructured datasets like images and videos. AWS provides a secure, scalable, comprehensive, and cost-effective portfolio of services that enable customers to build their data lake in the cloud.

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Ippon_AWS Solutions

Re-Writing a Mainframe Software Package to Java on AWS with Ippon Technologies

Ippon Technologies has successfully re-written a large mainframe third-party software package to Java Angular Spring Boot microservices. The package supported 130 TPS and 1,800 MIPS, catered to over 5,000 users, and housed more than 5 TB of business-critical data. Ippon helped the customer define the approach and architecture, and then developed the microservices along with the CI/CD pipeline on AWS. Learn about the project’s technical aspects, methodologies, and lessons learned.

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AWS Competency_featured

Tips for Becoming an AWS Migration Consulting and Delivery Competency Partner

All across the world, APN Partners are helping customers realize their digital transformation by migrating datacenter infrastructure and applications to AWS. To highlight our APN Partners that have demonstrated technical proficiency and proven customer success in the migration area, we established the AWS Migration Competency. Explore the key elements of the AWS Migration Competency Validation Checklist for APN Consulting and Delivery Partners, and understand the principles and rationales behind the requirements.

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How to Peel Mainframe Monoliths for AWS Microservices with Blu Age

Mainframe monoliths have grown over the years with overwhelming complexity. They often mix different languages and data stores with various interfaces, evolving coding standards, online and batch, and millions of lines of code. With AWS, customers use microservices for agility, elasticity, and pay-as-you-go cloud technology. In this post, we explore Blu Age solutions to peel off AWS microservices from a mainframe monolith, and how to solve data challenges associated with such a migration.

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Patterns and Best Practices for Mainframe Modernization with AWS

There is no one-size-fits-all for mainframe modernization to AWS. Depending on the business and IT strategy, customers select the most suitable pattern for them. If the mainframe is large enough to process multiple workloads, the characteristics can favor different patterns. Fortunately, based on our experience from successful customer modernization projects to AWS, we have identified patterns, lessons learned, and best practices that facilitate new mainframe-to-AWS initiatives.

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High-Performance Mainframe Workloads on AWS with Cloud-Native Heirloom

Heirloom automatically refactors mainframe applications’ code, data, job control definitions, user interfaces, and security rules to a cloud-native platform on AWS. Using an industry-standard TPC-C benchmark, we demonstrated the elasticity of Heirloom on AWS, delivering 1,018 transactions per second—equivalent to the processing capacity of a large mainframe. Heirloom Computing is an APN Standard Technology Partner.

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Re-Hosting Mainframe Applications to AWS with NTT DATA Services

NTT DATA Services provides a mainframe re-host solution that minimizes application code change while benefiting from the agility AWS offers. NTT DATA’s re-hosting reference architecture, migration best practices, and extensive technology feature set streamline mainframe migrations to AWS. NTT DATA is an APN Advanced Consulting Partner that helps clients navigate and simplify the modern complexities of business and technology, delivering the insights, solutions, and outcomes that matter most to their objectives.

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Migrating a Mainframe to AWS in 5 Steps with Astadia

When carefully planned, managed, and executed, the rewards of moving Mainframe workloads to AWS are numerous. Besides the cost savings of the pay-as-you-go model, once your Mainframe application set has been fully deployed on AWS, you will have the freedom to integrate proven business logic with modern technologies for data analytics or mobile enablement. With that in mind, migrating Mainframe applications to the cloud seems more like a necessity than a luxury.

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