Pure Storage CTO Discusses Effective Strategies for Managing Storage Complexities

Storage management is undergoing rapid evolution, driven by the dual forces of artificial intelligence (AI) and digital transformation. Data centers are now tasked with managing massive data growth, unprecedented demands for application agility, increasing complexity, and challenges such as skills shortages and rising energy costs. This confluence of challenges has created what can be described as a perfect storm, yet it also presents significant opportunities for organizations to modernize their IT infrastructure and operations.

At the heart of storage management lies our relationship with data. According to Statista, the average annual rate of data growth has been around 38% since 2010. This trend includes peaks during significant events, such as the pandemic, which saw a surge in data creation. Projections indicate that global data volume will reach a staggering 181 zettabytes by 2025, with deployed storage also increasing to keep pace—6.7 zettabytes were installed in 2020, with an annual growth rate of 19% anticipated through 2025.

Such explosive growth poses substantial planning challenges for enterprises, especially when considering traditional investment and depreciation cycles. In the past, organizations would often keep extra hardware on hand to accommodate unplanned requirements. However, soaring electricity costs necessitate improved energy efficiency in data centers, compelling IT organizations to focus on sustainable infrastructure practices.

The process of storage provisioning has historically been time-consuming and labor-intensive, often requiring extensive coordination between various departments within organizations. Requests for storage deployment would traverse a lengthy route from the requesting units to storage administrators, leading to delays and requiring numerous admins with diverse skills to manage multiple storage environments from different vendors. This fragmented approach could stretch the provisioning timeline to several weeks.

Faced with soaring data volumes and increasing application complexity, organizations have traditionally responded by adding more storage administrators. However, this approach is increasingly seen as inefficient and impractical given the current IT landscape, where the skills required to manage multiple legacy storage arrays are scarce and costly to acquire. Moreover, modern organizations aim to prioritize innovation and enhance customer experiences rather than be bogged down by day-to-day provisioning tasks.

The shift away from labor-intensive storage management practices is driven by digital transformation, which is steering organizations towards new IT architectures that incorporate cloud operating models and infrastructure-as-code principles. In this new paradigm, agility and speed of delivery have become paramount, with organizations expected to adapt to evolving requirements with greater efficiency.

To meet these demands, organizations are increasingly looking to empower their internal teams through self-service capabilities. Where dedicated storage resources are available, there is a strong desire to significantly increase the amount of storage managed per full-time equivalent (FTE). Self-service storage provisioning allows development teams to select storage performance profiles or code requirements directly via APIs, streamlining the process.

Modern application deployment models, such as containerization, enable storage resources to be defined as part of the application configuration file, allowing for automated deployment by orchestration platforms. This means applications can scale rapidly, with storage requirements integrated into their lifecycles at a pace often beyond human management. In this context, storage management must pivot to pre-set policies, auto-provisioning, and auto-scaling mechanisms to keep up with the demands of the digital landscape.

The future of storage management lies in adopting customer-defined storage performance profiles, either through self-service interfaces or fully automated processes within application environments. Organizations that successfully adapt will see storage administrators transition into roles resembling product managers. These professionals will define storage “products” using abstraction concepts like storage classes and policies, focusing on empowering internal customers and orchestration platforms rather than merely provisioning storage objects.

To support this cloud operating model, some storage vendors offer platforms that enable administrators to non-disruptively manage and add capacity to their fleets of storage devices while defining classes of storage, policies, and availability zones. Furthermore, developers can leverage infrastructure-as-code platforms to specify the required class of storage for applications, incorporating this directly into templates for testing and deployment.

For fully automated, containerized environments, businesses should seek enterprise-grade Kubernetes data platforms that facilitate automated deployment and scaling of persistent storage, along with robust data protection capabilities. Many of these solutions come with additional data services, such as curated databases designed for Kubernetes, allowing developers to deploy with a single click and dramatically reduce time-to-market.

However, organizations must be cautious; enabling self-service while still relying on lengthy purchasing and delivery cycles exposes them to risks. Fully embracing modern storage management concepts necessitates consuming storage platforms as a service, enabling rapid scaling and flexibility without premature investments in hardware.

To realize the vision of seamless storage management, organizations should seek storage vendors that can offer comprehensive solutions. Collaborating with a single vendor can streamline integrated product sets, enhancing efficiency across the IT stack. Implementing all-flash storage arrays within a unified operating environment allows for workload management at scale from a single viewpoint, alongside a Kubernetes data platform that incorporates essential self-service storage functionality.

The benefits extend to energy utilization and operational efficiency, with some all-flash vendors achieving up to 85% greater energy efficiency compared to competitors, coupled with a smaller footprint to optimize data center performance. Ultimately, working with a vendor that offers a flexible, SLA-backed storage-as-a-service model—complete with guarantees on energy usage, zero data migrations, and non-disruptive upgrades—is key to achieving modern storage management.

In conclusion, as the landscape of storage management continues to evolve, organizations have the opportunity to embrace new technologies and methodologies that not only address current challenges but also set the stage for future growth and innovation. By adopting self-service models, automating processes, and leveraging cloud solutions, businesses can enhance their agility, efficiency, and overall competitiveness in an increasingly data-driven world.