This article is the latest in “Mainframe to Distributed SQL”, an original series from Cockroach Labs. Please visit here for the previous installments:
An Introduction: What is a Mainframe?
Understanding Mainframe Database Architecture
Distributed Database Architecture
Legacy mainframe systems have long been the backbone of critical finance, healthcare, and government operations. However, as technology evolves, these aging systems often become costly to maintain, challenging to integrate with modern applications, and inefficient in meeting today’s digital demands. Migrating mainframe databases and applications to modern platforms is increasingly seen as a strategic imperative, offering enhanced scalability, flexibility, and cost savings.
However, legacy migration comes with its complexities: It involves a technical transition and preserving critical business logic and data integrity. Organizations must meticulously plan, execute, and validate the migration process to minimize disruptions and ensure the system operates smoothly.
This article explores the essential steps and best practices in preparing for a successful legacy mainframe database and application migration, from assessing system readiness to ensuring a seamless transition to modern infrastructure.
Assessment and Analysis
Before embarking on the migration of legacy mainframe systems, it is essential to conduct a thorough evaluation of the existing databases. This process helps identify the scope of the migration, the challenges involved, and the best strategy to ensure a seamless transition. Below are the critical components of a comprehensive evaluation:
1. Overall Assessment
Conduct detailed assessments of your existing applications and databases to gain valuable insights into your current setup. This will make the migration process smoother and more predictable.
Analyzing the source code is crucial for uncovering hidden complexities, dependencies, and potential issues within applications and their associated databases. This analysis helps to reveal how each application interacts with the database, highlighting any tightly coupled components or outdated dependencies that could hinder the migration process.
Similarly, assessing the application architecture is essential for identifying areas of technical debt and structural weaknesses that may need addressing before migration. By generating comprehensive reports on code quality, data flows, and interdependencies, organizations can effectively plan remediation, refactoring, or even re-architecting of specific components to ensure better alignment with the target environment.
2. Analyzing Data Structures, Schema Alignment
Mainframe databases often rely on hierarchical or network models such as Information Management Systems (IMS) or Integrated Database Management Systems (IDMS), which differ significantly from modern relational databases like SQL or NoSQL. Understanding the underlying structure of the current database is critical for identifying compatibility gaps between the source and target database schemas. Key considerations during this phase include:
Data model assessment: Examine the logical and physical structure of the databases, including tables, indexes, and relationships between data entities.
Volume and complexity: Determine the size of the databases, the complexity of queries, and the nature of the data (structured, unstructured, or semi-structured) to plan for storage and performance requirements in the target system.
Data normalization: Identify any redundancy or inefficiencies in the data structure that could be optimized during migration.
A complete assessment should cover the target database environment with the same importance as the source one. It is crucial to uncover architectural discrepancies. This is particularly important when migrating databases from premises to the cloud. Such an assessment should include:
analysis of data types
data mapping
data transformation technologies
data security
storage formats
3. Identifying Dependencies
Legacy mainframe systems are often intertwined with other applications, subsystems, or external services. A successful migration requires a deep understanding of these dependencies to avoid breaking integrations or workflows. Please take note of the following information:
Application dependencies: It is important to outline which applications depend on the mainframe database and how they interact. Some applications may utilize direct database connections, while others may rely on batch processing or messaging systems.
Dataflow and usage patterns: Analyzing how data is read, written, or updated across systems is essential. This analysis helps prioritize high-frequency transactions and identify critical data pathways that must remain operational during the migration.
External interfaces: Identifying any external systems or third-party services that the mainframe interacts with is crucial, such as financial processing services or supply chain platforms. These integration points will need to be carefully re-architected or reconnected post-migration.
4. Assessing Integration Points
Integration is critical to mainframe environments, as they often serve as central hubs for processing and distributing data across different platforms. A successful migration hinges on the ability to preserve or replicate these integration points in the new environment. Areas of focus include:
Middleware and messaging systems: Evaluate the role of middleware (such as IBM MQ or other messaging brokers) in the current setup. These systems often facilitate communication between the mainframe and external services or applications, and their configurations must be replicated in the target architecture.
API endpoints: Identify APIs that provide access to mainframe data for other systems. Modernizing these APIs or creating new ones may be necessary to ensure compatibility with modern platforms.
Batch processing schedules: Assess batch jobs that rely on the mainframe for data processing. These jobs may need to be redesigned for the new platform to ensure their timing and dependencies are accounted for during migration.
Organizations can build a solid foundation for their migration efforts by conducting this comprehensive evaluation of the mainframe database. It ensures that critical elements such as data integrity, dependencies, and integration points are thoroughly understood and addressed, minimizing the risk of disruption and maximizing the success of the migration process. However, this exercise is only valid if associated with a scope definition for the migration, which we explain further in the next section.
Identifying Modernization Targets
A critical step in a successful legacy migration is identifying and prioritizing which applications and databases to be modernized first. Given the complexity and scope of many mainframe environments, migrating everything at once is impractical. Based on a set of considerations, organizations can prioritize systems based on their business impact, technical complexity, and alignment with long-term strategic goals.
1. Assessing Business Criticality
The business value of an application or database is one of the most important factors in determining its migration priority. Systems essential to daily operations or customer-facing processes should often be at the forefront of any modernization effort. At this step, you should ask, "Why do I need to change the status quo ?” Is this migration for making money? Saving money? Mitigating risks? Or all of the above?
Prioritizing critical systems ensures that the business continues to operate smoothly while leveraging the benefits of the new environment. Key considerations include:
Revenue impact: Systems directly tied to revenue generation, such as financial transaction platforms, should be high on the priority list for early migration.
Customer engagement: Applications that interact with customers, such as online portals or support systems, must be modernized early to maintain a competitive edge.
Operational dependence: To minimize disruptions, core systems that affect the business's ability to function, such as supply chain management or payroll systems, should also be prioritized in the migration process.
2. Evaluating Technical Complexity
The technical complexity of an application or database influences the level of effort required for migration. More complex systems may require extensive refactoring, rearchitecting, or re-platforming to ensure compatibility with modern environments. Organizations can develop realistic timelines and allocate resources effectively by evaluating technical challenges upfront. Consider the following:
Codebase complexity: Applications with large, monolithic codebases or intricate customizations may be more challenging to migrate and require significant effort to decouple and modernize.
Legacy dependencies: Systems that rely on outdated or proprietary technologies, such as COBOL or PL/I, often require extra attention during migration, including potential code rewriting or replacement.
Integration complexity: Applications deeply integrated with multiple subsystems or external services may require additional work to ensure smooth integration post-migration.
3. Aligning with Strategic Goals & Roadmap
The business strategy must be “THE DRIVER” for your modernization project. A successful migration strategy should reinforce your overall business strategy and first address the business needs to generate accurate and discernable value.
Modernization efforts should align with the broader strategic objectives of the organization. Organizations can ensure their migration investments drive meaningful outcomes by focusing on systems that are central to achieving business growth or digital transformation goals. This involves aligning application migration with the company’s future vision and technology roadmaps:
Move to cloud strategy: If the organization is moving toward a cloud-first or hybrid architecture, prioritize applications and databases that are well-suited for cloud environments or require scalability and elasticity.
Agility and innovation: Applications that support innovation, such as those enabling data analytics, machine learning, or mobile platforms, should be prioritized to drive digital transformation initiatives.
Regulatory compliance and security: Systems requiring enhanced security features or compliance with evolving regulations may need to migrate sooner to meet governance requirements in modern architectures.
Notice that any misalignment with a business strategy might result in prioritizing the wrong projects, generating false or useless insights, or wasting time and money by allocating scarce resources to unprofitable activities. Even worse, it could lead to losing interest and confidence in any migration initiative throughout the organization!
The second important element of building a migration strategy is defining measurable goals. When constructing a modernization strategy, it is essential to set quantifiable short-term and long-term objectives. As a migration initiative leader, you are tasked with achieving success in three key areas: revenue growth, operational efficiency, and security/privacy risk management. By establishing success metrics, you prioritize based on what matters most to your organization at this moment.
Don’t forget to include the following constraints in your modernization strategy roadmap:
staff availability and needed external resources
budgeting process with capital investment considerations
competing and simultaneous projects that could limit available resources
major company milestones and crossroads like new product releases or mergers & acquisitions
4. Balancing Quick Wins and Long-Term Value
Every goal you set should have an actionable plan for accomplishing it. Plans should be specific and include key considerations such as:
who owns the goal
which technology and process they will use
the cost of reaching the objective
the time needed to achieve the goal
the intended outcome upon completing the objective
Plans should also remain flexible to account for unforeseen circumstances or unexpected changes.
While large-scale migration projects often focus on long-term value, it is beneficial to achieve early wins. Prioritizing low-complexity but high-impact applications or databases can provide quick, visible success that builds momentum for the overall migration initiative. These quick wins can help gain stakeholder buy-in and demonstrate the tangible benefits of modernization early in the process.
The data modernization prioritization matrix
Stakeholder Engagement
Any modernization and/or migration strategy will not succeed without executive support. Your organization’s executives will only support your initiative if there is clear alignment between your modernization strategy and the overall business strategy.
That means the first step of a successful modernization strategy is demonstrating how migration from mainframe databases can support their goals and plans. Then, identify and encourage business champions to view target databases, like CockroachDB, as valuable assets for their specific departments or functions. To that end, establish clear goals and measurable objectives for your data strategy that serve your larger business strategy.
The second step is to garner support and alignment from key organizational stakeholders for the modernization initiative. Aligning the modernization strategy with the business strategy is a good starting point, but it is not enough if you don't align your initiative with organizational capabilities.
Departments or teams should have their own local goals, which can be more or less aligned with your modernization initiative. For instance, each department/function needs to answer the question, “What do we want to accomplish by next year?” with an action plan outlining how they can be part of your migration plan to reach their desired outcome(s).
The roadmap results from all your hard work gathering short- and long-term objectives, identifying global and local goals, and negotiating priorities of such measurements, making it possible to put your plans into action. You know where you are and where you want to be. Still, activities must first be prioritized before beginning any design, build, or training process, or when changing a business procedure.
To ensure a unified approach, organizations must actively engage stakeholders and clearly communicate the value of modernization. Here are several strategies to achieve this:
Communicating the Strategic Value of Modernization: One of the most effective ways to gain stakeholder support is by clearly articulating the strategic value of modernization. This includes highlighting how the migration aligns with the organization’s long-term goals, such as improving agility, reducing operational costs, enhancing customer experiences, or enabling future innovations.
Engaging Stakeholders Early and Often: Involving stakeholders from the very beginning of the modernization initiative is key to fostering collaboration and ensuring alignment across the organization. Early engagement allows stakeholders to voice their concerns, provide input, and become active participants in the planning process.
Demonstrating Quick Wins and Early Successes: One way to gain momentum and build confidence in the modernization initiative is by demonstrating early wins. These quick successes provide tangible evidence of the value that modernization can deliver, which can motivate stakeholders to continue their support.
Highlighting Employee Impact and Upskilling Opportunities: A modernization initiative can often raise concerns about the impact on employees, particularly in IT departments. It’s important to address these concerns by highlighting employee growth and development opportunities.
Make Your Case
As you can see, early and comprehensive preparation is key for a successful modernization strategy! Migrating to a new database should be guided by a strong business case. A well-crafted business case is essential for securing buy-in from stakeholders. The business case should clearly outline the financial, operational, and strategic benefits of the modernization initiative and the risks of inaction.
You should present a detailed analysis of the costs involved in maintaining legacy systems compared to the investment required for modernization. Highlight any potential savings from decreased maintenance costs, improved operational efficiency, or reduced technical debt.
Address potential risks associated with the migration, such as downtime or disruptions, and outline mitigation strategies. Demonstrating a proactive risk management plan can reassure stakeholders and increase their confidence in the initiative. Examine use cases and assess key performance metrics such as query speed, latency, resource utilization, and budgetary factors like storage, licensing, and data ingestion costs for both the current and target environments.
A thorough evaluation also ensures that your data is ready for migration. This helps identify the most appropriate transformation technologies and encryption methods to protect data from potential security risks, both during transit and in the new environment.
Finally, show the projected ROI over time, illustrating how modernization will deliver value in both the short and long term. Include quantitative benefits such as increased productivity, reduced downtime, and lower infrastructure costs. Taking these steps will put your organization on the path to data modernization success.
Learn how the right cloud-native distributed database fits into your data modernization strategy: Visit here to speak with an expert.
Amine El Kouhen, Ph.D., is Sr. Partner Solutions Architect at Cockroach Labs.
References
“7 Elements of a Data Strategy”, Christina Salmi.
“What’s Your Data Strategy? The key is to balance offense and defense.” Leandro DalleMule and Thomas H. Davenport (HBR, May-June 2017).
