2022 and Beyond – Technologies That Will Change the Dialogue
By John Roese, Global Chief Technology Officer, Dell Technologies
We are living in a do-anything-from-anywhere economy enabled by an exponentially expanding data ecosystem. It’s estimated 65% of Global GDP will be digital next year (2022). This influx of data presents both opportunities and challenges. After all, success in our digital present and future relies on our ability to secure and maintain increasingly complex IT systems. Here I’ll examine both near-term and long-term predictions that address the way the IT industry will deliver the platforms and capabilities to harness this data to transform our experiences at work, home and in the classroom.
What to look for in 2022:
The Edge discussion will separate into two focus areas – edge platforms that provide a stable pool of secure capacity for the diverse edge ecosystems and software defined edge workloads/software stacks that extend application and data systems into real world environments. This approach to Edge, where we separate the edge platforms from the edge workloads, is critical since, if each edge workload creates its own dedicated platform, we will have proliferation of edge infrastructure and unmanageable infrastructure sprawl.
Imagine an edge environment where you deploy an edge platform that presents compute, storage, I/O and other foundational IT capacities in a stable, secure, and operationally simple way. As you extend various public and private cloud data and applications pipelines to the edge along with local IoT and data management edges, they can be delivered as software-defined packages leveraging that common edge platform of IT capacity. This means that your edge workloads can evolve and change at software speed because the underlying platform is a common pool of stable capacity.
We are already seeing this shift today. Dell Technologies currently offers edge platforms for all the major cloud stacks, using common hardware and delivery mechanisms. As we move into 2022, we expect these platforms to become more capable and pervasive. We are already seeing most edge workloads – and even most public cloud edge architectures – shift to software-defined architectures using containerisation and assuming standard availably of capacities such as Kubernetes as the dial tone. This combination of modern edge platforms and software-defined edge systems will become the dominant way to build and deploy edge systems in the multi-cloud world.
The opening of the private mobility ecosystem will accelerate with more cloud and IT industries involved on the path to 5G. Enterprise use of 5G is still early. In fact, today 5G is not significantly different or better than WiFi in most enterprise use cases. This will change in 2022 as more modern, capable versions of 5G become available to enterprises. We will see higher performance and more scalable 5G along with new 5G features such as Ultra Reliability Low Latency Communications (UR-LLC) and Massive Machine Type Communicators (mMTC), with dialogue becoming much more dominant than traditional telecoms (think: open-source ecosystem, infrastructure companies, non-traditional telecom).
More importantly we expect the ecosystem, delivering new and more capable private mobility, will expand to include IT providers such as Dell Technologies but also public cloud providers and even new Open-Source ecosystems focused on acceleration of the Open 5G ecosystem.
Edge will become the new battleground for data management as data management becomes a new class of workload. The data management ecosystem needs an edge. The modern data management industry began its journey on public clouds processing and analysing non-real-time centralised data. As the digital transformation of the world accelerates, it has become clear that most of the data in the world will be created and acted on outside of centralised data centers. We expect that the entire data management ecosystem will become very active in developing and utilising edge IT capacity as the ingress and egress of their data pipelines but will also utilise edges to remotely process and digest data.
As the data management ecosystem extends to the edge this will dramatically increase the number of edge workloads and overall edge demand. This correlates to our first prediction on edge platforms as we expect these data management edges to be modern software-defined offerings. Data management and the edge will increasingly converge and reinforce each other. IT infrastructure companies, like Dell Technologies, have the unique opportunity to provide the orchestration layer for edge and multi-cloud by delivering an edge data management strategy.
The security industry is now moving from discussion of emerging security concerns to a bias toward action. Enterprises and governments are facing threats of greater sophistication and impact on revenue and services. At the same time, the attack surface that hackers can exploit is growing based on the accelerated trend in remote work and digital transformation. As a result, the security industry is responding with greater automation and integration. The industry is also pivoting from automated detection to prevention and response with a focus on applying AI and machine learning to speed remediation. This is evidenced by industry initiatives like SOAR (Security Orchestration Automation & Response), CSPM (Cloud Security Posture Management) and XDR (Extended, Detection and Response). Most importantly we are seeing new efforts such as the Open Secure Software Foundation in the Linux Foundation ramp up the coordination and active involvement of the IT, telecom and semiconductor industries.
Across all four of these areas – edge, private mobility, data management and security – there is a clear need for a broad ecosystem where both public cloud and traditional infrastructure are integrated. We are now clearly in a multi-cloud, distributed world where the big challenges can no longer be solved by a single data center, cloud, system or technology.
What to look for beyond 2022:
Quantum Computing – Hybrid quantum/classical compute will take center stage providing greater access to quantum. In 2022 we expect two major industry consensuses to emerge. First, we expect the industry will see the inevitable topology of a quantum system will be a hybrid quantum computer where the quantum hardware or quantum processing units (QPU) are specialised compute systems that look like accelerators and focus on specific quantum focused mathematics and functions. The QPUs will be surrounded by conventional compute systems to pre-process the data, run the overall process and even interpret the output of the QPUs.
Early real-world quantum systems are all following this hybrid quantum model and we see a clear path where the collaboration of classical and quantum compute is inevitable. The second major consensus is that quantum simulation using conventional computing will be the most cost effective and accessible way to get quantum systems into the hands of our universities, data science teams and researchers. In fact, Dell and IBM already announced significant work in making quantum simulation available to the world.
Automotive – The automotive ecosystem will rapidly shift focus from a mechanical ecosystem to a data and compute industry. The automotive industry is transforming at several levels. We are seeing a shift from Internal Combustion Engines to Electrified Vehicles resulting in radical simplification of the physical supply chain. We are also seeing a significant expansion of software and compute content within our automobiles via ADAS and autonomous vehicle efforts. Finally, we are seeing the automotive industry becoming data driven industries for everything from entertainment, to safety to major disruptions such as Car-as-a-Service and automated delivery.
All of this says that the automotive and transportation industries are beginning a rapid transition to be driven by software, compute and data. We have seen this in other industries such as telecom and retail and in every case the result is increased consumption of IT technology. Dell is actively engaged with most of the world’s major automotive companies in their early efforts, and we expect 2022 to continue their evolution towards digital transformation and deep interaction with IT ecosystems.
Digital Twins – Digital Twins will become easier to create and consume as the technology is more clearly defined with dedicated tools. While gaining in awareness, digital twins is still a nascent technology with few real examples in production. Over the next several years, we’ll see digital twins become easier to create and consume as we define standardised frameworks, solutions and platforms. Making digital twin ideas more accessible will enable enterprises to provide enhanced analytics and predictive models to accelerate digital transformation efforts. Digital twin adoption will become more mainstream with accelerated standardisation and availability of solutions and framework, bringing deployment and investment costs down. Digital twins will be the core driver of Digital transformation 3.0 combining measured and modeled/simulated worlds for direct business value across industry verticals.
As a technology optimist, I increasingly see a world where humans and technology work together to deliver impactful outcomes at an unprecedented speed. These near-term and long-term perspectives are based on the strides we’re making today. If we see even incremental improvement, there is enormous opportunity to positively transform the way we work, live and learn and 2022 will be another year of accelerated technology innovation and adoption.