Marcela Marrugo is a Social Media Manager at Micro Focus, now OpenText, where she has embarked on a personal quest to tap into the potential of AI to deepen her understanding of IT topics that concern our customers. This is her first blog.
When I started at Micro Focus (now OpenText) a little over a year ago, I hadn’t so much as heard the words “mainframe” or “COBOL,” and I would have told you “modernization” meant getting rid of your DVDs because you have a subscription to every single streaming service. As someone with a communications background, learning about these technical topics wasn’t easy and it took quite a bit of repetition.
More than a year later, I’m still learning, which is why I decided to go back to the basics again and ask OpenAI’s ChatGPT about the topics I write on all the time for Micro Focus Application Modernization & Connectivity. I also asked Misty Decker, Worldwide Director of Product Marketing for the Application Modernization and Connectivity group at OpenText, to give her answers to the same questions to see how they compare.
Whether you’re an experienced programmer or someone with a non-technical background, I think there’s something new for everyone to learn.
ChatGPT:
A mainframe is a large, centralized, powerful computer system used for mission-critical applications, such as banking, airline reservation systems, and government records. Mainframes are known for their reliability, scalability, and security and are used for handling high volume transactions and large amounts of data.
Misty:
A mainframe is a large server designed to handle large scale transaction processing with high levels of reliability, availability and security.
ChatGPT:
Modernizing the mainframe can help organizations reduce costs, improve performance, scale computing resources, increase security, and enhance the user experience. This allows organizations to stay competitive and meet the changing needs of their business, while preserving the benefits of the mainframe platform.
Misty:
As the demands on the business change over time, the organization’s IT systems need to also evolve. Modernizing the mainframe is just one other thing that needs to adapt to the need for faster delivery of new features and integration with new technologies.
ChatGPT:
Organizations may choose to move their mainframe to the cloud for several reasons, including:
- Increased flexibility and scalability: The cloud offers the ability to scale resources up or down based on changing business needs, providing organizations with greater flexibility.
- Cost savings: By moving the mainframe to the cloud, organizations can lower their capital expenditures and operating costs, as they do not need to purchase and maintain expensive hardware.
- Improved disaster recovery and business continuity: With cloud-based mainframes, organizations can quickly recover from disasters or downtime by leveraging cloud resources.
- Enhanced security: The cloud provides organizations with a secure and highly-available environment for their mainframe systems and data.
- Access to innovative technologies: The cloud enables organizations to quickly access and utilize new technologies and tools, such as artificial intelligence and machine learning, to drive innovation and improve business processes.
Overall, moving the mainframe to the cloud can help organizations to achieve improved cost-effectiveness, scalability, security, and access to innovative technologies, while preserving the benefits of the mainframe platform.
Misty:
Cloud didn’t exist when many organizations built their IT systems on top of mainframe technology. Now that cloud is an option, leaders should review their IT landscape to identify which applications are better served with the scale out flexibility offered by public cloud and which applications should be retained within an on-prem data center.
Another consideration is ROI. The mainframe is a higher value system, so workloads that don’t really need the unique characteristics of a mainframe should be considered top candidates for moving to the cloud.
ChatGPT:
Here are some steps organizations can follow to prepare for moving their mainframe to the cloud:
- Assess the current environment: Assess the current mainframe infrastructure and applications to determine which ones are ready to move to the cloud and which ones require additional modernization or re-architecting.
- Develop a migration plan: Create a detailed migration plan that outlines the steps and timeline for moving the mainframe to the cloud, including testing, data migration, and cutover strategies.
- Evaluate cloud providers: Research and evaluate cloud providers that offer mainframe migration services and choose one that aligns with the organization’s requirements and budget.
- Test and validate: Perform thorough testing and validation of the mainframe applications in the cloud environment to ensure they are running optimally and that all dependencies are properly configured.
- Train personnel: Train personnel on the new cloud-based mainframe environment and provide them with the tools and support they need to be successful.
- Monitor and adjust: Continuously monitor the mainframe in the cloud and make adjustments as needed to ensure it is running optimally and meeting the needs of the business.
By following these steps, organizations can ensure a successful migration of their mainframe to the cloud, while minimizing the risk of downtime and data loss.
Misty:
As with any project, start with understanding where you are, determine where you want to be and then make a plan to get there. Understanding your current IT infrastructure and application estate can be assisted with a variety of tools. The future state should focus first on the business goals and how your IT needs to change to meet those goals. Only after those two steps should you start thinking about what specific changes are required. Since every organization’s current and future states are different, every journey is unique. It’s very important to get help from trusted advisors who have experience with large numbers of modernization journeys.
ChatGPT:
The Micro Focus Modernization Maturity Model is a framework for assessing an organization’s level of maturity in mainframe application modernization. The model provides organizations with a set of best practices and guidelines for modernizing their mainframe applications and infrastructure, and helps to identify areas for improvement.
The model consists of five stages of maturity, from Stage 1 (Initial) to Stage 5 (Optimized), and covers a range of areas, including application architecture, development practices, deployment processes, and overall infrastructure management.
By using the Micro Focus Modernization Maturity Model, organizations can gain a better understanding of their current state of mainframe modernization and develop a roadmap for improving their overall modernization maturity. This can help organizations to reduce costs, improve performance and security, and deliver better customer experiences.
Misty:
After thousands of successful modernization projects, the experts at Micro Focus learned what works and what doesn’t. We have captured that knowledge in a framework that is meant to help you identify your current state and plan your journey forward. Although shown in five stages, it’s important to note that not every application, process or infrastructure needs to get to level 5. It’s a fundamental tenet of the Modernization Maturity Model to always put the business needs before the technology used to achieve them.
Learning about the mainframe, modernization, and the cloud helped me understand why organizations might want to start their journey migrating to the cloud and even how Micro Focus can get them there. Not only am I a little more knowledgeable on these tricky topics, but I will be able to write about them better and help people understand the importance behind our messages. I hope you also learned something while reading through my basic questions about these not-so-basic ideas.
Did you know you can take steps to modernize your valuable COBOL and mainframe assets now? Learn more at Destination Cloud.
This post was first first published on Home | Micro Focus Blog website by Marcela Marrugo. You can view it by clicking here