Issa Walid, the Senior Manager for PreSales and Solutions Engineering – Middle East Region at NetApp, says we’ve reached a time when it’s no longer possible to distinguish between in the cloud and on-premises
What trends do you foresee for Cloud Computing in 2022?
Hybrid cloud is clearly becoming and will continue to be the default configuration for most organizations, combining growing public cloud usage, including off-premises hosting, with existing on-premises workloads. Organizations will continue to keep workloads on-premises for the foreseeable future, but increasingly recognize the importance of being able to integrate them with cloud workloads. Cloud will not be an either/or choice for most organizations for many years, and as a result, there has been significant growth in commitment to a hybrid cloud strategy.
However, most organizations still view on-premises as important. In fact, nearly nine of ten organizations expect to have a significant or measurable on-premises environment in three years. Organizations may be early in their cloud journey and still deciding what migration to the cloud will look like for their enterprise, or they may have already begun development and design. Either way, the journey is not finished. Hybrid cloud and its impact on businesses is fast-tracking growth by modernizing data management and optimizing workloads. It’s never been easier to unleash the power of the cloud.
What sort of benefits does cloud computing bring to eCommerce stores and e-tailers?
The eCommerce and e-tailers industry has changed profoundly over the past decade. They are not only measured by the merchandise they sell, but also by how well they can meet the emerging habits of the online shoppers and consumers. For example, consumers expect to have a seamless shopping experience that is available 24/7 across channels, all the way from the mobile application until the product reaches their home.
And therefore, they are under mounting pressure to evolve with changing demand, constantly coming up with new features and technologies. And in this new digital reality, it’s becoming increasingly clear that the cloud will offer them capabilities that are essential to thrive in the market. The cloud will help them overcome the constraints of their physical and geographical environments, providing infrastructure that can easily scale up and down to meet their needs, and also provide the insights needed to analyze important metrics, such as customer buying behavior, to drive innovation even further.
Is edge computing helping shape up the cloud computing industry as a whole?
With the growth of IoT applications and consumer devices, a constant and significant amount of data is being generated and ingested at the edge. As an example, the edge can consist of a massive number of sensors that gather raw data, ranging from a few gigabytes to a few terabytes a day, depending on the application.
Moving this volume of raw data from thousands of edge locations over the network at scale is impractical and is prone to performance issues. Shifting analytics processing and inference at the edge is an ideal way to reduce data movement and provide faster results. In such advanced solution cases, the data that is fed into the data lake is being operated upon from analytics and an AI/DL perspective, and the trained AI/DL models are pushed back to the edge for real-time inferencing.
From a Cloud perspective, public and private clouds complement the on-premises AI/DL infrastructure with commoditized storage and computing as a service. Depending on the deployment and application requirements, the cloud can play either a central role or a supporting role in the workflow.
Will combining AI with cloud services enable organizations to get the most out of both applications in a cost-effective way?
The benefits of the cloud can be leveraged in several ways. We can use GPU instances for computation, and we can use the cloud for cold storage tiering and for archives and backups. In many AI/DL applications, the data might span across the edge and/or the core and/or the cloud. As a result, we must be able to orchestrate data across these environments.
In addition, the solution ecosystem in the cloud offers an ideal environment to begin the development of AI workflows, to run proofs of concept, and to form a foundation to expand upon. Organizations that expect to scale their investments in AI leverage on-premises solutions to be more cost-effective while using the cloud for test/dev and data lifecycle management. Data backups and archives are key components in managing the lifecycle of data management in AI applications, for which petabyte-scale datasets are common.
In such cases, the data must be moved between the cloud and the on-premises data center, and it is vital to account for data egress costs from the cloud. The benefits of AI on the other hand have become more apparent, and an increasing number of organizations seek to deploy solutions to collect and gather tangible insights from the large amounts of data that they generate. Infrastructure plays an important role in defining success for AI/DL applications. Therefore, It is crucial to take a holistic approach to cover all deployment scenarios without compromising on the agility to expand as we need to and while keeping costs in check.
Do you believe serverless functions have a big part to play in creating new user experiences?
When Serverless came into the mix it seemed to address the complexity that came with running containers. With Serverless we just hand over our code to somebody and let them run it for us. While this removes some complexity, we lose control over the underlying layers. When we attempt to control things like dependencies, cold starts, custom libraries, and limit resource consumption, it requires many vendor-specific custom tools and tactics which takes the focus away from the applications themselves.
In this sense, serverless becomes more and more like containers as it becomes just as complex after a certain point. This led to a hybrid approach of implementing containers as serverless. The biggest takeaway from serverless for containers is ‘how can we make containers as simple as possible to run?’ However, we still cannot compromise on control.
We still need access to the best hardware, networking, storage, and more, and this is closer to what containers offer than serverless. In my opinion, Kubernetes brings the best of both worlds that is simplicity and control. Kubernetes has become the de facto container orchestrator in the cloud and thanks to its vibrant community, it has become much simpler to manage. Kubernetes can deliver the ease of use that serverless promises but without compromising on control.
With Metaverse becoming the “keyword” for 2022, do you believe the cloud has a major role to play here? What opportunities exist for both vendors and channel partners?
I think we’ve reached a time when it’s no longer possible to distinguish between in the cloud and on-premises, and hybrid cloud is driving digital transformation. If companies were not digitizing before, they are now. Keeping up with the changing times demands fast, accessible, and affordable data management. A united approach to data management takes customers seamlessly from the data center to cloud, saving time and money and eliminating data silos. In a service model where data centers are no longer the center for data, storage needs to be without boundaries.
Administrated everywhere, it really is anytime, anywhere data. NetApp is helping our partners extend their customers’ business data to the cloud by accelerating migration easily and securely. We accomplish this thanks to our strong partnerships and long-time relationships with hyperscalers. And while working with our partners during the pandemic, we have witnessed a pandemic-driven push to the cloud. Optimization is top of mind for all customers as they experience challenges around managing costs. Using more cloud at less cost, driving innovation, and offering solutions that are trusted by leading hyperscale’s are a few of the ways in which we are helping our customers and partners to tackle this challenge.
For example, CloudOps and Spot by NetApp are hot topics right now with partners, and they are key components of our cloud strategy. We’re having exciting conversations and mapping out journeys to help guide optimization by using a programmatic approach, delivering savings of up to 90% on digital estates. We’re moving beyond the development and design of cloud migration to optimize for the best experience with the greatest value.
