When it comes to data, many organizations are trying to solve one or more of the following data modernization issues: 

• How to make application integration more efficient
• How to utilize data from multiple systems that don’t necessarily communicate with each other
• How to expose their data via micro-services for use by applications 

To assist organizations that are facing one or more of these challenges, I recently joined Danna Bethlehem, Director of Product Marketing at GigaSpaces for a discussion of these issues. You can view the full webinar here, or read on for a synopsis of our discussion. 

Undertaking Legacy Modernization Initiatives

The main drivers for legacy systems modernization usually arise to support new or evolving business needs. Outdated technology, poor operational efficiency, challenging security policies and compliance regulations, and scalability and agility requirements are some of the reasons why organizations choose to initiate legacy modernization processes. We will view these initiatives through four aspects: 

• User experience
• Access to data
• Data driven services
• Hybrid IT environments

User experience

A superb user experience is the culmination of a key business driver coupled with digital modernization. The following are the main drivers for organizations to offer a superb user experience:

• Consumerization: with the convergence between consumer and enterprise experiences, all users expect the same ease of use across all services
• COVID-19: the pandemic greatly accelerated the need for digital services, and hence the need for a superb user experience; enterprises operating remotely had to catch up quickly and many are still catching up
• Revenue: a positive online experience drives business and revenue 

Access to data

Modern applications and operational analytics usually require and rely on fresh current data, frequently required in real time. However, existing systems may hinder efficient data access due to outdated technology, data silos, challenging integration, performance bottlenecks, complex security measures, and inadequate scalability. These factors result in slow response times, difficulties in accessing and consolidating data from various sources, limited connectivity, and inefficient processes, impacting productivity, decision-making, and collaboration. 

Data-driven services

What we see in the field is that many data teams, specifically application integration teams, are looking for ways to respond to increasing demands for data availability and data services – without impacting their underlying systems. Applications rely on data – think of a retail app that requires data from inventory, shipping, payments, customer care and other systems. The app is constantly receiving requests for API access to existing legacy systems where the data is stored. These apps require quick, accurate responses so that organizations can develop modern digital applications without disrupting their existing environments. Yet many legacy systems are not able to keep up with these demands, due to the coupled nature of their architecture. 

To address the challenge of streamlining access to enterprise data, and making it easier to consume, a few design concepts have evolved, including data mesh, data fabric and digital integration hubs. These architectures promote a data centric mindset that creates the foundation for delivering business value. They address the problem of siloed data – the ability to utilize data that resides in multiple existing systems. 

Data Mesh

Data Mesh is a process-driven approach that emphasizes domain-oriented ownership and autonomy of data. Data-driven services are designed to be self-contained, specialized, and autonomous, enabling domain experts to leverage data as a product, and develop services that cater to their specific needs.

Data Fabric

Data Fabric is a technology-driven approach to architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems in a self-service manner. Data fabrics utilize various data and metadata management technologies which may include data catalogs, data integration, data virtualization, orchestration and semantic knowledge graph tools.

With both Data Fabric and Data Mesh, data-driven services promote a data-centric mindset, where data is treated as a first-class citizen and forms the foundation for delivering business value. These services enable organizations to leverage data assets effectively, provide self-service access to data, foster data collaboration, and empower domain experts to derive insights and make data-driven decisions within their respective areas of expertise.

Hybrid IT environments

A hybrid approach allows organizations to maintain some of their computing resources on-premises, while also leveraging cloud services from public cloud providers, such as developing cloud native services, or during burst into the cloud scenarios. These environments also permit organizations to retain sensitive data locally, to comply with strict regulations in certain sectors, while still benefiting from the flexibility and scalability of the public cloud. Hybrid approaches can be used in conjunction with digital integration hubs, data mesh and data fabric. 

Ensuring business continuity and scalability 

Many organizations have existing legacy systems that are difficult to migrate entirely to the cloud or to modernize. Since enterprises must ensure business continuity at all times, also throughout a legacy modernization initiative, an incremental approach that avoids a drastic ‘rip and replace’ is an excellent way to gradually modernize while maintaining continuous business operations. 

What we see in the field is that many data teams, specifically application integration teams, are looking for ways to respond to increasing demands for data availability and data services without impacting their underlying systems. They require quick responses for API access to their existing systems of record (SoRs). 

Modernizing Incrementally with IBM and GigaSpaces

At IBM, we strongly believe that hybrid environments offer organizations the most effective path to modernization. Most enterprises are heavily invested in existing systems. Lift and shift approaches are not viable options. Modernizing over existing systems offers enterprises the benefits of maintaining their existing systems, while still being able to gain the best of modern cloud and web native environments. IBM works closely with GigaSpaces, an IBM Silver Business Partner, to help organizations modernize without disruption.

The GigaSpaces Smart DIH platform is designed to allow IT teams to preserve their underlying systems, while still being able to build modern data services. By decoupling SoRs from digital apps, utilizing low code, CDCs such as IBM IIDR, and event-based architecture, this solution allows data to be easily accessed from any underlying systems and exposed through APIs to consuming services. This approach helps protect SoRs and avoid business disruption, while allowing organizations to effectively modernize their environments in an incremental way, enabling business continuity and business growth. 

View the full discussion on how IBM and GigaSpaces offer a viable path to modernization without disruption HERE.