Cloud computing has quickly become the preferred platform for current and future data processing. For most organizations, the cloud offers compelling economics, the latest technologies, and the agility to adapt information systems to evolving business needs quickly and efficiently. A cloud-first mentality has taken hold in organizations of all types. Startups exploit its low entry price to launch their business without large capital investment in hardware.
Established organizations migrate existing systems to reduce costs and facilitate competitive innovation. Even governments have recognized the potential of cloud computing as an instrument for maximizing taxpayer dollars while improving services to their citizens.
But what about the large organizations burdened by the much older and expensive mainframe platforms? Is cloud computing a viable option for their tried-and-true core applications, or is their only path forward risky and costly rewrites or replacement projects?
Until fairly recently, I would have said that cloud computing doesn’t have the reliability, scalability, and security to handle the complex applications running on big iron workhorses. Even though mainframe applications have been successfully migrated to open systems since the early 90s, I didn’t feel the cloud was mature enough for mission-critical mainframe workload.
But cloud computing has evolved rapidly since its early days, and today’s cloud environments have matured enough to handle virtually any workload IT shops can throw at them, including bread-and-butter mainframe applications. The evidence for this conclusion can be found in one of the most ubiquitous activities performed every day by people around the globe — shopping on Amazon.com.
A lot goes on behind the scenes when consumers shop on Amazon. Searching its massive inventory of almost 400,000,000 products for the one item they desire is impressive enough. But there’s much more to it than that. Agents interrogate partner websites for matching products and scour the web for competitors’ pricing, and algorithms calculate prices to undercut other retailers and evaluate criteria to suggest related items of interest to maximize sales potential — all within subsecond response times.
Once a transaction is initiated, personal and payment information is collected and secured, shipping costs and delivery dates are calculated, and fulfillment processing is begun — with a few simple clicks. Furthermore, it’s only on extremely rare occasions that one cannot complete a purchase on Amazon. In fact, it’s unheard of — it seems Amazon is always available.
These integrated activities transpire reliably millions of times each second of each day, all without a mainframe in sight. So yes, I do believe the cloud is ready for mainframe workload.
As first published in DZone.
To help mainframe shops understand how they can exploit the benefits of cloud computing while leveraging their investments in legacy applications, Astadia has developed a series of mainframe-to-cloud white papers. Drawing on our experience of delivering mainframe to open-systems migrations and providing cloud managed services solutions, we’ve mapped legacy application components to the leading cloud environments. Take a look and contact our team if you need more information or guidance in designing your mainframe-to-cloud roadmap.
Companies running older mainframe technology with Adabas & Natural are faced with the daunting task of moving to RDBMS databases and object-oriented languages that can better support agile development and modern integration standards.
Using powerful conversion and testing tools, complex migration processes can be almost entirely automated, which results in minimal turnaround time for workflows, no errors or delays, and reduced project costs. Here's how.
Get in touch with our experts and find out how Astadia's range of tools and experience can support your team.contact us now