India is among NetApp’s top four markets in Asia, accounting for 15% to 18% of the company’s overall revenue. Ravi Chhabria, managing director, NetApp India, spoke to Alokananda Chakraborty about NetApp’s AI roadmap and how it is working to develop applications that let companies “talk” to their data. Edited excerpts:
When you talk of data management, are the customers’ pain points different today, from, say, two years ago?
Data management has become even more critical in recent years. Previously, businesses primarily concentrated their efforts on challenges pertaining to data storage, retrieval, protection, archival and security. However, the contemporary landscape has evolved significantly. Governance, privacy, sovereignty of data are equally important. This evolution is driven by the proliferation of data from multiple sources, structured and unstructured, in data centres, cloud, and hybrid multi-cloud environments. The flow of the same data across use cases, with different service level needs, and different cost and performance needs adds to the challenge. The emergence of advanced technologies like artificial intelligence and machine learning and the opportunities they bring make intelligent data management all the more important.
Businesses need to build IT infrastructures that are not only robust but also intelligent.
Which elements of storage have made the fastest migration to the cloud rather than staying on-premises? How does an organisation decide what is right for it — hybrid or super cloud?
Initially this acceleration is particularly notable for non-critical or less sensitive data types such as archival, backup, and development environments. These data types benefit from the scalability, cost-effectiveness, and flexibility offered by cloud storage solutions, allowing organisations to reduce infrastructure costs and enhance agility. Today every organisation has a hybrid multi-cloud infrastructure and it is very dynamic. Data moves from being a transactional record to a source of intelligence to an enabler of deep learning, or a cold archive as business needs change.
When deciding on the cloud strategy, organisations should assess their specific requirements, priorities, and objectives. A hybrid approach provides the flexibility to integrate on-premises infrastructure with multiple cloud environments, offering greater control over sensitive data and compliance requirements. This approach is well-suited for organisations with rigorous data privacy regulations or those requiring localised data storage for regulatory compliance.
While cloud storage may seem cheaper and easier than local storage, it also involves hidden or variable costs and complexities, resulting in wasted budget and over-provisioning. What’s your advice for organisations when they go about optimising cloud pricing and resources?
Optimising infrastructure is critical to operating it. This applies to data centers, cloud, and multi-hybrid cloud. NetApp’s uniqueness is a comprehensive approach to optimise storage infrastructure through a coordinated, well integrated set of technologies that operate in all three major hyperscaler clouds and the most demanding data centers.
For instance, our BlueXP provides a unified control plane to simplify the management of storage and data services across on-premises, private, and public cloud environments. It offers a single user interface for configuring, monitoring, and data protection across a wide range of environments, including highly secured government sites.
Our CloudOps product portfolio helps organisations effectively manage their increasingly complex cloud computing environments as they build and deploy cloud-native applications alongside legacy applications running on virtual machines. CloudOps provides tools to streamline cloud operations, optimising costs and resource utilisation while enabling consistent governance and security.
Organisations could look at a comprehensive approach to storage infrastructure optimisation and a unified control plane to simplify management, increase efficiency, and reduce costs across their hybrid cloud environments.
Coming to the hottest topic today … AI… which brings a whole new level of intelligence and automation to data storage systems. Will it end up expanding or curtailing the strategic role of CIOs in an organisation?
The integration of AI into data storage systems brings notable considerations for CIOs within organisations. The findings from the NetApp 2023 Data Complexity Report underscore this, indicating that AI adoption is accelerating cloud migration and reshaping approaches to data security. With the majority of organisations transitioning to cloud environments and leveraging AI for analytics, the strategic responsibilities of CIOs are evolving to encompass these transformative technologies.
The growing importance of data security, particularly in the face of rising ransomware threats, highlights the pivotal role of CIOs in implementing robust security measures. The report emphasises the imperative for CIOs to prioritise data security to mitigate potential business risks. Sustainability considerations have become a key factor in technology decision-making, with CIOs playing a crucial role in aligning storage solutions with organisational sustainability goals.
Amid these changes, flash storage emerges as a cornerstone for innovation and security, further emphasising the vital role of CIOs in driving technological advancements and ensuring data integrity. As organisations navigate the complexities of AI-driven transformations, CIOs will organise cohesive strategies that integrate AI into existing infrastructure while safeguarding against cybersecurity threats and addressing sustainability imperatives. While AI adoption presents both challenges and opportunities, it ultimately amplifies the strategic importance of CIOs in shaping technological landscapes and driving organisational success.
What are the crucial considerations as companies transition AI projects from research to production?
Transitioning AI projects from research to production involves several important factors. First, companies need to ensure they have good quality and enough data to train their AI models effectively. This data should be relevant and representative of real-world situations to get accurate results. Secondly, it’s crucial to make sure that AI models can handle the workload in production smoothly. This means optimising them for performance and scalability, which involves investing in the right infrastructure and techniques. Companies must also test their models rigorously to make sure they work well in real-world scenarios, identifying and fixing any problems like biases or errors that might creep in.
Choosing the right infrastructure for deploying AI models is essential. This includes considering factors like cost, scalability, and how well the infrastructure fits with existing systems. Companies also need to keep a close eye on their AI models once they’re in production, monitoring them regularly and fixing any issues promptly. Another important aspect is following regulations and ethical guidelines, ensuring that the AI projects comply with data privacy laws and ethical standards. Last, collaboration among different teams, including data scientists, engineers, and IT professionals, is vital for a successful transition. By considering these factors carefully, companies can smoothly transition their AI projects from research to production, ensuring that they deliver value to the organisation.
What’s the roadmap for NetApp’s AI strategy and investments?
We are witnessing the emergence of generative AI, signifying a pivotal juncture in our AI endeavors. Globally, NetApp’s investments in AI underscore our commitment to innovation and meeting the evolving needs of our customers. This includes obtaining accreditations from industry leaders such as NVIDIA, bolstering our capacity to support enterprise AI deployments. Our recent collaboration directly connects the just-announced NVIDIA NeMo Retriever microservices—coming to the NVIDIA AI Enterprise software platform for the development and deployment of production-grade AI applications, including generative AI—to exabytes of data on NetApp’s intelligent data infrastructure. Every NetApp ONTAP customer will now be able to seamlessly ‘talk to their data’ to access proprietary business insights without compromising the security or privacy of their data. Such strategic partnerships have strengthened our position as a key player in the AI domain.
India is among NetApp’s top three markets in Asia and also one of the fastest-growing storage markets in the region. When do you see it becoming your top market in Asia?
India is among NetApp’s top four markets in Asia, accounting for 15% to 18% of the company’s overall revenue. Given the current growth trajectory, we expect India to become the leading contributor in the Asian region over the next five years. NetApp is committed to doubling our business in India in the next couple of years, which is seen as a significant milestone. We have established all functions and processes in India, and this momentum is expected to continue as the business grows.