The IT infrastructure that underpins practically all of our modern-day activities is continually going through a perpetual state of change.
Month by month, year by year, the technology that drives our digital lives only continues to evolve and mature, and that means organizations must stay ahead of the curve if they want to remain competitive.
As you might expect, much of the focus of IT infrastructure transformation is centered on leveraging data to its full potential while reducing costs and risk at the same time. After all, the amount of data we generate as a species is growing at an exponential rate.
In fact, the IDC (International Data Corporation) estimates that global data will more than double between 2022 and 2026. Clearly, the sheer volume of data calls for more intelligent and efficient ways of managing it. On that note, here are some of the most promising technologies that are revolutionizing IT infrastructure.
The cloud has enabled organizations to become more agile, reliable, and secure by shortening the time it takes to update their IT infrastructure and reducing the risks associated with managing complex on-premise systems.
Not only does this increase scalability and flexibility, but cloud computing also allows organizations to reduce operational costs by optimizing resource utilization and decreasing capital expenditure.
Moreover, adopting a multi-cloud architecture helps organizations offset vendor lock-in, ensuring that they have access to the best-of-breed solutions available on the market.
For example, using a data-intensive application like machine learning or artificial intelligence (AI) requires access to both compute and storage resources, which are generally sourced from different cloud services. In these cases, a multi-cloud strategy enables organizations to optimize their resources and costs across multiple vendors.
While cloud computing has its benefits, one of the major downsides of these solutions is the latency they create due to the distance between the cloud servers and the user. This can be a major issue when dealing with time-sensitive applications like autonomous vehicles or remote healthcare – or essentially any other application that requires real-time data processing.
That’s where edge computing comes in. Edge computing is a model that takes advantage of Internet of Things (IoT) devices located at the “edge” of a network to process data closer to the source, thereby reducing latency and improving response time.
This enables applications to run more effectively and efficiently, giving organizations a competitive edge in the market. Additionally, edge computing also helps to improve security as sensitive data is not transmitted over the network, reducing the risk of data breaches.
Artificial Intelligence (AI) and Machine Learning (ML)
AI and ML are two of the most exciting technologies emerging today. Both enable organizations to automate mundane tasks, glean insights from data in real time, and make more informed decisions.
For example, AI-enabled chatbots can help organizations deliver higher levels of customer service while ML algorithms can be used to detect fraud in financial transactions. By leveraging the power of AI and ML, organizations can optimize their operations, reduce costs, and open up new revenue streams.
However, implementing these technologies requires access to powerful computing resources, which is why cloud platforms and edge computing are essential for optimizing AI/ML workloads.
High-Performance Computing (HPC)
High-Performance Computing (HPC) is an incredibly powerful technology that allows businesses to process large amounts of data quickly and accurately.
It optimizes speed, efficiency, and scalability, making it an essential tool for complex applications such as 3D rendering, weather forecasting, machine learning, and artificial intelligence. HPC systems use powerful CPUs and GPUs to process tasks in parallel, providing faster results than traditional computing systems.
For organizations that need to solve complex computational problems to make predictions in industries like financial services or healthcare, HPC solutions are a must. However, setting up an on-premise HPC system can be costly and time-consuming – which is why leveraging cloud services makes so much sense.
Cloud providers offer cost-effective access to their high-performance computing resources which allows companies to easily obtain the power they need without needing to invest in dedicated hardware or expensive software licenses.
What Are Some of the Main Challenges?
Despite the many benefits of the emerging technologies discussed above, there are some major challenges that organizations need to consider. For one, the cost of deploying solutions like AI and HPC (even in the cloud) can be prohibitive for many organizations.
Additionally, the lack of standardization across providers and the complexity of multi-cloud solutions can create significant hurdles that need to be overcome.
Finally, and arguably most importantly, organizations need to make sure they have a comprehensive security strategy in place that accounts for use of these systems. As user data becomes more abundant, it is highly likely that cyber-attacks will become more frequent – so taking the necessary steps to protect data and applications is an absolute must.
It looks as though 2023 is going to be an exciting year for new technologies – and organizations need to be prepared for the changes that are coming. By leveraging solutions like cloud computing, edge computing, AI/ML, and HPC, businesses can gain a competitive edge over their rivals and build more agile, efficient, and secure operations.
While there are still plenty of challenges lying in wait, it will be interesting to see the impact of these technologies over the coming years and the applications that they enable.