The hybrid cloud landscape is rapidly evolving, and some companies struggle to keep up with the new innovations. By 2028, Gartner forecasts that modernization efforts will culminate in 70% of workloads running in a cloud environment, up from 25% in 2023. To date, moving workloads to the cloud has primarily involved tackling the relatively easy data and workloads running on-premises—the low-hanging fruit. The next wave of data migration to the cloud will not be as easy and will require a greater understanding of transactional data and applications, many of which run on mainframes today.
From evaluating the business case for migration to navigating the complexities of data governance and compliance, each facet of the migration journey presents unique considerations that demand careful deliberation. For companies navigating the next era of hybrid cloud adoption, several strategies and considerations must be considered to best uncover the untapped potential of migrating the remaining 45% of workloads.
Exploring the Uncharted Territory
As companies embark on the journey toward hybrid cloud, they must delineate the purpose of their data migration endeavors. Whether leveraging advanced AI tools or developing innovative customer-facing applications, accessibility to data is paramount for driving transformative initiatives. By articulating clear objectives, businesses can align their migration investments with their overarching business strategy, maximizing the value derived from cloud adoption.
Every successful journey begins with a map. Likewise, a comprehensive inventory of existing data assets is essential for effective migration to the cloud. Particularly for established enterprises, legacy data may be scattered across various repositories, rendering it challenging to assess comprehensively. Identifying these data silos and understanding where they fit into various modernization efforts is critical to identifying whether they are a priority for data migration, helping organizations allocate resources effectively.
This discovery process not only enhances visibility into the entirety of the data landscape but also facilitates the identification of redundant or obsolete datasets that can be archived or decommissioned, thereby optimizing storage and operational costs. Additionally, by mapping data dependencies and interrelationships, businesses can mitigate the risk of data fragmentation and ensure trust and seamless integration into hybrid cloud environments. This also enables a more thorough analysis of data residency requirements and regulatory constraints, enabling organizations to proactively address compliance considerations and minimize potential legal and reputational risks associated with data migration.
Overall, a systematic approach to data discovery and classification serves as a cornerstone for successful hybrid cloud adoption, laying the groundwork for robust data governance and future scalability.
See also: Hybrid Cloud Leads The Way, But Few Have Holistic Strategy
Strategically Deciding What Workloads Should Migrate to the Cloud
Not all workloads are destined for cloud migration. While the allure of cloud-native solutions is undeniable, specific applications may remain best suited for mainframe environments due to various factors.
One critical consideration is performance requirements; some transactional workloads may require consistent high processing speeds, low latency, and high availability provided by mainframe systems, making them unsuitable for migration to the cloud. Additionally, regulatory compliance plays a significant role in determining the suitability of cloud migration for specific workloads. Industries such as finance and healthcare, which handle sensitive customer data, must navigate stringent regulatory frameworks that may limit the feasibility of cloud migration. Moreover, cost considerations must be carefully weighed when evaluating the migration of workloads to the cloud.
While cloud solutions offer scalability and cost-efficiency benefits, certain workloads may incur higher operational costs or require significant rearchitecting to function optimally in the cloud environment. Hence, organizations must discern the optimal deployment model for each workload, striking a delicate balance between innovation and pragmatism. Organizations can maximize the value derived from hybrid cloud adoption while mitigating potential risks and optimizing resource utilization by conducting thorough assessments of workload characteristics and aligning migration strategies with overarching business objectives.
However, even when workloads remain in place, data can often be made available to cloud applications and analytics and AI initiatives, either by providing access through virtualized queries or by replicating and synchronizing data between platforms on an ongoing basis.
Embracing a phased approach to workload transfer facilitates a smooth transition to the hybrid cloud. An incremental strategy not only minimizes disruption but also enables iterative optimization of cloud deployments, fostering continuous innovation and agility. Breaking down the migration process into manageable stages allows for targeted resource allocation and risk management, ensuring that each workload transition is executed with precision and minimal impact on day-to-day operations.
Additionally, adopting a phased approach provides feedback and course correction opportunities, enabling organizations to refine their migration strategies based on real-time insights and evolving business requirements. By prioritizing high-impact data that offer immediate business value, organizations can demonstrate tangible benefits early in the migration journey, garnering support and buy-in from stakeholders across the enterprise. As data and workloads are progressively migrated to the cloud, organizations can leverage the flexibility of hybrid architectures to optimize resource utilization and swiftly adapt to changing market dynamics. Ultimately, a phased approach to data and workload transfer accelerates the pace of cloud adoption and lays the foundation for long-term innovation and competitive advantage in an increasingly digital world.
Seeing Hybrid Cloud Adoption in Action
Companies who embark on the journey to hybrid cloud often experience enormous benefits. Liberty Mutual Insurance, a leading global insurer, migrated to the cloud to provide the flexibility and connectivity needed to modernize its content management operations. With more than 30 million customer profiles, 40 billion records, and over 45,000 employees, Liberty Mutual needed to modernize operations through fast, secure data migration from mainframe repositories to cloud systems to remain competitive and provide the best service—all without disrupting business operations.
By migrating to the cloud, not only was Liberty Mutual able to implement innovative cloud and open-source software, but the organization could harness data-driven insights to enhance customer experiences and drive competitive differentiation. By migrating select workloads to the cloud, Liberty Mutual gained unprecedented agility in deploying AI-powered analytics solutions, enabling personalized offerings and predictive decision-making.
This strategic migration positioned Liberty Mutual as a frontrunner in the fiercely competitive insurance landscape and underscored the transformative potential of hybrid cloud architectures in driving business agility and resilience. As organizations across all industries embark on their own journeys toward hybrid cloud adoption, the successful ones will improve business insights and customer satisfaction. In an era of rapid technological advancement and digital disruption, embracing hybrid cloud solutions is not merely a choice but a strategic imperative for those poised to thrive in the digital age.
As the landscape continues to evolve, the next era of hybrid cloud adoption presents unparalleled opportunities for organizations to unlock the full potential of their data assets. It is imperative that businesses effectively and strategically migrate the critical but harder-to-access data that resides on the mainframe. By embracing a strategic approach to data and workload migration and leveraging the inherent flexibility of hybrid cloud architectures, businesses can navigate the complexities of modernization while driving innovation and resilience. The journey towards optimal cloud delivery is well underway – and the future promises boundless possibilities for those willing to embrace change.
Michael Curry is the President of the Data Modernization Business Unit at Rocket Software. He joined the company in 2023, bringing with him extensive knowledge of building business software products, defining and executing software product strategy, and implementing large-scale systems within Fortune 500 companies. As president, he oversees worldwide strategy, development, and product management for the Data Modernization business unit. Prior to Rocket Software, he served as an executive in residence for Great Hill Partners, a Growth Private Equity firm in Boston, where he led a detailed market assessment of the Data and AI markets. His background also includes leadership positions in multiple software companies, including 17 years at IBM, leading strategy and execution in business lines across integration, artificial intelligence, data governance and analytics, and SaaS business applications. He has served as a member of the IBM Technology Team, the IBM AI Ethics Board, and the IBM Distinguished Industry Leader Board. This deep experience underscores his track record across all facets of building software businesses.