Discussing the 2022 Mainframe Modernization Report
LEGACY TO CLOUD
The selected cloud destination will ultimately depend on the customer’s desired short and long-term goals.
Advanced has the unique ability and experience to migrate legacy workloads to any cloud destination: cloud ready, cloud optimized, or cloud native. The below graphic provides an overview of the three different cloud destination options:
LEGACY TO CLOUD
The starting point of any modernization journey should be a comprehensive assessment – encompassing applications, operations, and the supporting infrastructure. Assessment results should look to validate any pre-selected disposition strategies (sometimes referred to as modernization patterns), and ultimately assist in defining the overall modernization approach. Depending on the long term goals – the approach often includes a combination of disposition strategies. For example, a long term goal of re-engineering a large, complex mainframe monolith into cloud-native microservices can be broken into several incremental steps:
JOURNEY TO THE CLOUD
A proven, mature approach based on an environment that runs on distributed platforms and emulates the legacy operating environment. The emulation capability minimizes the amount of change that occurs when migrating legacy systems to a distributed platform. Source code is recompiled where possible, and customized to support the specific Rehost technology. Data is migrated – with the structure of some original data types retained, including Relational, VSAM, Sequential, GDGs, among others. Operational functionality provided by third party solutions such as job schedulers, print and output management, security, and systems management solutions are replaced in order to support the same processing capabilities as the original legacy environment.
Our Automated Refactoring approach retains functional equivalence while converting core legacy applications to fully maintainable, refactored object-oriented Java or C# code. Once the legacy application and database is refactored, developers can extend application functionality directly without the need to navigate the original legacy code. Critical business logic from the legacy system is preserved, while enabling deeper integration with other Java or C# workloads and additional customization to meet evolving business requirements.
Various levels of optimization can be applied during or following an Automated Refactoring project. Code is analyzed during the assessment to determine application cloud-readiness and the required optimization effort to obtain the desired level of elasticity (i.e. horizontal scalability [scale out/in] and vertical scalability [scale up/down]) required by the application workloads being migrated.
Because mainframe-based applications are stateful by nature, they require modifications in order to take advantage of the dynamic scaling abilities provided in a cloud-optimized environment. If scaling is desired, the assessment phase will allow for identification of areas where state is being stored on the application tier, such as the use of shared memory (e.g. CICS TS Queues, TD Queues, CWA, TWA if applicable) in addition to anywhere the applications are reading/writing local files, logs, and configuration scripts. At this point Advanced can provide customers with options that weigh the pros and cons for addressing each state-specific issue. Examples include leveraging a distributed cache to support state, and moving any local file access to a scalable shared file system.
Sometimes referred to as rewrite, re-engineering captures original application specifications, and then redesigns and develops the new solution using the latest application frameworks. In addition, re-engineering incorporates any required new functionality, which is a common driver for selecting this approach. Re-engineering delivers a completely customized solution that meets exact requirements, leveraging the latest application frameworks, architectures and practices such as cloud-native microservices and DevOps. The primary business outcome for re-engineering is increased application agility to more quickly meet evolving market demands.
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