Category: Migration & Transfer Services

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.

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 AWS Blu Age solutions to peel off AWS microservices from a mainframe monolith, and how to solve data challenges associated with such a migration.

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.

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.

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.

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.

While modernizing customer mainframes, the team at AWS Blu Age discovered that Batch can be a complex aspect of a mainframe migration to AWS. It’s critical to design your AWS architecture to account for the key Batch stringent performance requirements such as intensive I/Os, large datasets, and short durations. Let’s explore how to migrate mainframe Batch to AWS microservices using AWS Blu Age automated transformation technology.

VMware Cloud on AWS enables customers to extend their on-premises data centers and easily migrate application workloads without having to convert machine image formats or undergo a re-platforming process. Customers no longer have to over-provision hardware resources to accommodate for host failures. Instead, they can increase utilization of the cluster resources, as host failure replacement takes minutes, not days or weeks. In this post, we dive deeper into the foundational blocks that make up this service.

As the move towards cloud accelerates, unsubstantiated fears about security are inhibiting the use of cloud services by some enterprises. A vital element of a successful cloud migration is understanding shared responsibilities between the organization and cloud service provider. Ixia’s CloudLens has a serverless architecture that scales with distributed software systems built for cloud scale, which delivers intelligent, resilient, and proactive cloud visibility.

With the recent launch of VMware Cloud on AWS, you can now run workloads on VMware-managed SDDC clusters installed on special bare metal hardware provided by Amazon Amazon EC2 services. This post describes a solution for securing workloads on VMware Cloud on AWS that we demonstrated at VMworld 2017. VMware workloads that run in the SDDC cluster can leverage different levels of AWS network and application protection capabilities with minimum to no changes to their application settings.