Data is valuable currency in the eyes of most organizations across the globe. Although it is similar in value to Wall Street shares, a 2021 Accenture report notes that data is not traded on Wall Street. Instead, “data is traded on and through the cloud; tethering your ability to leverage your data to your cloud capabilities.”
Statistics show that 92% of all organizations are already somewhat attached to the cloud. As a result, let’s look at some of the more significant trends that are the latest in cloud computing technology.
1. Cost-effective, scalable data storage
Returning to the information in the 2021 Accenture report cited above, figures show that the total data generated across the globe by the end of 2020 was 44 zettabytes. This data must be stored somewhere. Before the onset of the cloud age in 2006, persistent storage was costly; thus, data owners had to work carefully with their data, deciding what to keep and discard.
Reasonably priced, public cloud storage became increasingly available and popular early in the twenty-first century, culminating with the launch of Amazon S3 or Amazon Simple Storage Service in March 2006. Succinctly stated, it provides object storage via a web service interface.
On 25 August 2006, AWS (Amazon Web Services) launched its EC2 (Elastic Compute Cloud) service, separating compute from storage and enabling organizations to move their applications and workloads to the cloud by renting virtual server instances out to these organizations.
As the world has moved further into the twenty-first century, one of the continuing trends in cloud computing technology is the ever-increasing availability of cost-effective, scalable data storage in public and private cloud Infrastructure-as-a-Service.
2. Economic value generated by the cloud reaches $120 billion
Forrester Research has forecast that the global public cloud market will increase by 35% in 2021 to $120 billion.
The global COVID-19 pandemic has fueled this growth and will continue to play a role in driving the adoption of cloud technologies for the foreseeable future. The 2021 Forrester Predictions report justifies this statement:
“The aggressive move to the cloud, already proceeding at a healthy clip before the pandemic, will spike in 2021, yielding even greater enterprise adoption, cloud provider revenue and business value.”
Additionally, the blog post titled “Predictions 2021: Cloud Computing Powers Pandemic Recovery,” by Dave Bartoletti, principal analyst at Forrester, describes how cloud technology will support organizations to recover from the pandemic. It will help companies adapt to the new normal that is still so variable and unstable.
As a result, the percentage of global cloud-based IT infrastructure spending will continue to accelerate in 2021. Gartner predicts that the global IT spend on cloud-based infrastructure by organizations or end-users will grow by 18% in 2021 to $304.9 billion, up from $257.5 billion in 2020.
Briefly stated, as Sid Nag, research VP at Gartner, notes, the pandemic has validated the cloud’s value proposition. Consequently, organizations are utilizing on-demand, scalable cloud models to reduce costs and achieve business continuity in a world that requires the majority of the workforce to work from home (WFH) or remotely.
The World Economic Forum’s Future of Jobs Report 2020 notes that cloud computing is the highest priority for business leaders, and by 2025, cloud computing will be adopted by most organizations worldwide.
3. Edge computing combined with cloud computing
The article titled “10 Future Cloud Computing Trends to Watch in 2021” describes the Forrester prediction that, in 2021, new business models, the use cases combining edge computing and cloud computing will substantially increase. This is primarily due to the developments in Artificial Intelligence and 5G technologies.
As an aside, the infographic contained in the blog post titled “IT Outsourcing Industry in Singapore – Statistics & Facts” notes that the “growth in IoT and 5g networks will generate the demand for edge computing data centers in Singapore.”
What is edge computing?
Unlike cloud computing, where data is uploaded, stored, and processed in a central location (the cloud), edge computing is where the data is processed at its source. However, this does not mean that the cloud computing model will become obsolete. All it means is that the edge computing model and the cloud computing model will be combined.
A really good example of this combined model is the self-driving car or autonomous vehicle. On the one hand, the data generated by all of the car’s sensors must be processed locally or onboard the vehicle during a trip. This model’s bandwidth, latency, and privacy elements do not allow for all of this data to be uploaded and processed during the journey. Therefore, it must be processed at the edge.
On the other hand, a self-driving car must be centrally managed or managed from the cloud. Software must be automatically updated, and the processed data must be uploaded to the cloud for multiple reasons, including improving the self-driving algorithms.
4. The role of cloud computing in Artificial Intelligence and machine learning
Over the last decade, AI, machine learning, and deep learning have increased in importance and prominence. Based on current market research, multiple organizations across different industries are investing in technologies and infrastructure that will power Artificial Intelligence, machine learning, and deep learning algorithms and models.
However, for these algorithms and models to run successfully and produce meaningful, insightful results, they require extremely high volumes of raw data. Because these data volumes are typically stored in the cloud, cloud computing has been an effective catalyst for running AI workloads.
Note: Machine learning and deep learning are subsets of Artificial Intelligence. Therefore, when the phrase “Artificial Intelligence” is used, it covers the overarching AI paradigm, including machine learning and deep learning.
Cloud computing has also advanced and enriched the Artificial Intelligence paradigm. Cloud delivery models such as IaaS (Infrastructure-as-a-Service), PaaS (Platform-as-a-Service), and SaaS (Software-as-a-Service) all consume or offer AI services to the end-user.
IaaS provides AI practitioners with an instant, stable, replicable, scalable infrastructure environment, including CPU, RAM, persistent disk storage, network, and operating system. On the other hand, PaaS provides data scientists and AI practitioners with access to AI and data science services, including Jupyter notebooks and data catalog services to develop and train AI models. Lastly, SaaS allows users to consume AI services within an application.
Final thoughts
Data is only going to increase in value in the future, and with the ever-increasing reliance on cloud computing technology, it is clear that the cloud is the future. Not only is it a cost-effective, reliable storage solution, but it is also a competitive imperative. Understanding the latest trends and implementing those that are relevant to your organization will improve your data accessibility, data management, and cybersecurity, which in turn will make it easier to gain meaningful insights from your data, resulting in the ability to take advantage of new income generation opportunities while ensuring that your organization remains competitive over time.
Leveraging cloud computing technologies in the future demands a commitment to agility and change. The one thing that is certain of cloud computing is that it will continue evolving. As the world continues to embrace the cloud, to remain up to date with these ever-evolving trends, it is essential to take note of these trends as they continue to develop over time.
