Why We're Calling The 2010s The Decade Of The Cloud
It was the best of times, and it was the most disruptive of times.
We're talking about the 2010s—the period we've officially dubbed "the decade of the cloud."
That's because the 2010s is when the cloud truly hit its stride, making it clear that this transformational technology would soon disrupt the world as we know it. After all, it was the decade when many of the most famous brands in just about every industry moved their business to the cloud. The Central Intelligence Agency made a $6 million investment in cloud technology in 2014. And tech start-ups that would later become the largest disrupters of their industries—such as Netflix, Facebook, Amazon, and Uber—were not only cloud-native but were so successful because they were cloud-native.
In other words, the cloud totally dominated the 2010s. That’s why we dipped back into the archives to resurface some of the biggest news and advancements in cloud history from the past decade. So sit back, relax, and take a moment to relish in how far cloud technology has come—because this is just the beginning.
Hybrids helped make the cloud more accessible.
The proliferation of cloud technology throughout the 2010s helped organizations realize they have a lot of choices when it comes to actually building their cloud infrastructure. Teams could choose to migrate all of their organization’s data to the cloud at once. Or, they could also select what parts of their infrastructure remained on-premises versus in the cloud. That made moving to the cloud feel less like a cannonball into unknown water, and more like stepping in, one foot at a time.
Today, the hybrid approach is an essential building block for companies just starting out in the cloud. In fact, Gartner predicted that 90% of organizations will eventually adopt hybrid infrastructure by 2020.
Multicloud gave companies more flexibility.
Unlike hybrid cloud, which focuses on a blend of private and public clouds, multicloud is the mixing and matching of cloud services and technologies.
Multicloud came with its benefits—it allowed organizations to avoid vendor lock-in and enjoy the flexibility that comes with leveraging different features across providers.
A 2019 Gartner survey indicated that 81% of respondents said their organization was working with at least two cloud providers, proving that multicloud architectures gained serious momentum in the 2010s.
Edge computing helped accelerate The Internet of Things.
At a basic level, edge computing brings computation and data storage closer to the devices where it’s being gathered, rather than relying on a central location that can be thousands of miles away. This is done so that data, especially real-time data, does not suffer latency issues that can affect an application’s performance.
Edge computing was developed due to the exponential growth of IoT devices, which connect to the internet for either receiving information from the cloud or delivering data back to the cloud. And many IoT devices generate reams of data during the course of their operations.
Now, edge computing is transforming the way all of this data is being processed and delivered from the millions of devices around the world. Faster networking technologies, such as 5G wireless, are allowing edge computing systems to accelerate the support of real-time applications, such as video processing and analytics, and artificial intelligence and robotics.
The formation of Microsoft-AT&T and AWS-Verizon alliances was a big moment for edge computing in the 2010s. These two partnerships are centered on integrating 5G infrastructure with cloud applications and services at specific edge locations.
Today’s three biggest cloud providers were born.
By 2010, the three cloud giants—Amazon Web Services, Microsoft, and Google—all launched their cloud businesses. It was also the year we saw the birth of OpenStack, the leading open-source cloud software platform.
We saw the rise of serverless computing.
Serverless computing as we know it today was born at the 2014 AWS re:Invent conference, with Amazon Web Services’ announcement of Lambda. Serverless isn’t really serverless, but it does enable a developer to set event triggers and leave the infrastructure requirements completely to the cloud provider. This means the vendor can deliver exactly the right amount of compute, storage, and memory—and the developer doesn’t even have to lift a finger.
Why does severless computing matter? Well, for years, organizations have developed applications and deployed them on servers. Now, with the growth of serverless computing, a cloud provider manages the code execution, executes it only when needed, and charges only when the code is running. In this model, enterprises no longer have to worry about provisioning and maintaining servers when putting code into production.
SaaS grew up from being an awkward teenager to a mature adult.
2010s was when SaaS officially hit its stride. This decade, we witnessed what can only be described as an explosion of SaaS offerings on the market. Just take a look at the sheer growth in revenue over the years: The worldwide public cloud services market is projected to grow 17.5% in 2019 to total $214.3 billion, up from $182.4 billion in 2018.
The fastest-growing market segment will be cloud system infrastructure services, or infrastructure as a service (IaaS), which is forecast to grow 27.5 percent in 2019 to reach $38.9 billion, up from $30.5 billion in 2018. The second-highest growth rate of 21.8 percent will be achieved by cloud application infrastructure services, or platform as a service (PaaS).
That kind of monumental growth throughout the 2010s was a big deal—it proved that not only could SaaS be widely available, but that it could scale, too. Today, SaaS has matured into a nearly ubiquitous part of any business.
Artificial Intelligence migrated to the cloud.
Whether it’s AI-enabled consumer-facing devices, products augmented with AI, or the delivery of AI as a platform, today, it’s not an exaggeration to say that AI is practically everywhere.
This rapid growth was made possible, in large part, by advancements in cloud technology. During the 2010s, we saw big enterprise software companies integrate AI capabilities into cloud-based enterprise software and bring them to the mass market. Salesforce, for example, integrated its AI-enabled business intelligence tool, Einstein, into its CRM software in September 2016. Now, the company delivers one billion predictions per day to users.
SAP also integrated AI into its cloud-based ERP system, S4/HANA, to support specific business processes such as sales, finance, procurement, and the supply chain. S4/HANA has around 8,000 enterprise users, and SAP is driving its adoption by announcing that the company will not support legacy SAP ERP systems past 2025.