In today’s rapidly evolving business landscape, organizations across industries are striving to remain competitive and relevant. As new and powerful technologies emerge, it’s now critical to effectively manage and update outdated technology systems. If these systems are not modernized effectively and at the right time, despite once being robust and efficient, they can easily become bottlenecks hindering growth and agility.

To address this need for a transformative solution, many forward-thinking organizations are now turning to Amazon Web Services (AWS), the leading cloud platform, that offers powerful services and tools tailored for modernizing legacy IT infrastructure. 

In this first part of this blog series, we explore the complexities organizations face during the modernization journey and discuss a few effective strategies to transform outdated systems into dynamic, future-proof assets that drive growth.

Navigating the complexities of legacy technology modernization

Some of the complexities and risks associated with legacy technology modernization and how organizations can navigate them are: 

  1. Integration Complexity and Security Risks: Governance, compliance, security, and funding are typical challenges that slow down cloud adoption efforts within organizations. Thorough consideration of these factors is vital for a successful and seamless transformation when modernizing an organization’s IT infrastructure with modern technologies and cloud computing. One critical factor that can influence this process is the choice of compute, which depends on the organization’s existing AWS journey and its use of microservices and containerization.

Additionally, while transitioning to modern and secure solutions, there must be a close vigil in place for safeguarding sensitive data and intellectual property. Legacy systems used in organizations may have outdated security protocols and vulnerabilities that can pose huge security risks, especially in today’s ever-changing and sophisticated cyber threat landscape. 

  1. Lack of Agility and Innovation: The legacy systems often fail to provide the necessary flexibility and agility to keep pace with today’s ever-changing business demands, impeding organizations from embracing innovation, developing new offerings, and capitalizing on market opportunities. Let’s consider Kubernetes as an example to highlight this challenge. Kubernetes, a powerful orchestrator, enables efficient compute and patch management. Its adoption empowers developers with flexible containerized deployments and maintain seamless exit strategies, fostering agility to adapt quickly to emerging technologies and customer demands.
  2. Overcoming Security and Integration Challenges: Effective data governance presents another challenge in the modernization process. Organizations must ensure that their data is well-organized, accessible, cost-optimized, and adaptable to different structures. Achieving this requires a comprehensive approach, including data migration to centralized data lakes or warehouses for streamlined management. Moreover, harnessing the power of artificial intelligence (AI) and machine learning (ML) initiatives further automates data processing and analysis, boosting productivity and unlocking valuable insights.

Having a clear, well-thought-out transformation strategy right from the start, helps tackle these challenges easily. Also, focusing on a use case that is broad enough to test the application, data, and compute limits while not being mission-critical or overly complicated can come quite handy. 

Driving an agile and innovative modernization journey 

In today’s business landscape, numerous organizations are modernizing their processes with scalable, flexible, and cost-effective services. To ensure a smooth and successful transition, a well-defined roadmap is crucial, considering four key elements: current technology posture, economic model, practitioner readiness, and clear desired outcomes. 

Modernizing legacy technology and processes enables organizations to support multiple channels, enhance staff productivity, and respond swiftly to today’s changing business environments. Also, with other key technologies like AI, ML and data analytics, it is now possible to re-imagine digital businesses. However, it is essential to have a robust and flexible data architecture to fully leverage these technologies and achieve digital transformation goals.    

To harness this, the establishment or improvement of data architecture is vital. It starts with creating a data taxonomy and classification system to determine access pattern, ownership rights, and retention models. Once these foundations are in place, tagging can be used to monitor data throughout its lifecycle enabling effective management and governance. Organizations can then focus on managing data flow or the data continuum from ingestion through various channels to their analysis and driving automated outcomes. This way, clear classification and taxonomy ensures that data structure follows the intended usage patterns and moves effectively.

AWS empowers organizations in this modernization journey, providing performance optimization, scalability, secure data integration, cost-effectiveness, minimum downtime, and business continuity through its comprehensive services and tools.

In the second part of this blog series, read more about how Trimac Transportation leveraged the scalability, reliability, and agility of AWS to transform its outdated legacy systems, enabling benefits like improved operational efficiency, proactive transportation services, and an exceptional customer experience.

Note: This blog highlights key points from a webinar discussion hosted by Accolite in which the experts discussed modernizing legacy technology using AWS to bridge business drivers with technology-based solutions. 

You can watch the webinar recording here: [Webinar]To learn more about modernizing legacy technology using AWS, download Trimac Transportation’s featured case study here: [Trimac’s Case Study]