Federal agencies are racing to modernize their data storage infrastructure to keep pace with next-generation applications and workloads. According to a recent survey, 57% of Federal IT leaders anticipate the adoption of modern data storage solutions will support faster data access and retrieval for real-time applications in their organizations.
However, many agencies still rely on legacy storage systems that struggle to meet the performance and scalability demands of advanced workloads from artificial intelligence (AI), machine learning (ML), big data analytics, and real-time operational data processing. Agencies risk falling behind if they don’t modernize their data infrastructure.
Hybrid Cloud Object Storage’s Role in Modernization
Modern data storage architectures such as high-performance all-flash, software-defined storage, and hybrid cloud object storage offer significant advancements over legacy systems. Hybrid cloud object storage seamlessly integrates on-premises infrastructure with public and private cloud resources. This approach allows agencies to take advantage of cloud scalability and cost-efficiency without compromising on data control, governance, and security. Agencies can store sensitive data on-premises while utilizing the cloud for less critical data or for burst workloads, ensuring optimal resource utilization and cost savings. This architecture provides the foundation needed for modern data workloads, ensuring that Federal agencies can meet the increasing demands of their missions.
Developing a Data Infrastructure Modernization Strategy
A successful data infrastructure modernization strategy should be centered on agile, scale-out storage designed for data analytics and AI/ML workloads. This involves integrating storage solutions that can scale horizontally, allowing for seamless expansion as data volumes grow. An agile storage infrastructure can adapt to evolving requirements, ensuring that agencies can rapidly respond to new challenges and opportunities. By focusing on scalability and flexibility, Federal agencies can future-proof their storage infrastructure, making it capable of handling the diverse and complex data sets generated by modern applications.
Implementing AI-Driven Storage Management
AI-driven management can optimize storage performance, predict potential issues before they occur, and automate routine tasks, reducing the burden on IT staff and improving overall efficiency. Predictive analytics can provide insights into usage patterns and future storage needs, allowing agencies to plan and allocate resources more effectively. This proactive approach ensures that storage systems are always operating at peak performance, supporting the fast-paced and data-intensive nature of modern federal applications.
Modernizing data storage infrastructure is critical for Federal agencies to keep pace with next-generation applications and workloads. By evaluating and adopting high-performance all-flash, software-defined storage, and hybrid cloud object storage, developing a scalable and agile data infrastructure strategy, and implementing AI-driven storage management, agencies can ensure they are well-equipped to meet current and future demands.
Learn More:
- eBook: Anything is Possible with the Right Data Foundation
- Research: Federal Data Maturity Report
- On Demand Webinar: Anything is Possible with the Right Data Foundation