With 2020 almost here, it’s amazing to think about how much cloud technologies and the cloud industry as a whole have transformed over the past decade. While cloud technologies will continue to bring transformative change to businesses well into the 2020s, we thought it was worth reflecting on 10 of the most important cloud developments this decade and predict how they might shape the future of the enterprise.
We watched SaaS grow up this decade
SaaS was not invented in the 2010s, but you’d be forgiven for thinking so. This decade, we witnessed what can only be described as an explosion of SaaS offerings hit the market — an observation borne out by growth in the revenue of the SaaS industry. The 2010s proved that not only could SaaS be widely available, but that it could scale as well, with large players like Microsoft and Google expanding their offerings. Today, SaaS has matured into a nearly ubiquitous part of the enterprise, but it’s easy to forget how different the cloud landscape looked just 10 years ago.
Hybrid cloud changed the design of IT infrastructure
One development that emerged from the cloud revolution was the realization that organizations have a lot of flexibility in how they implement cloud infrastructure. Operations teams could choose to go all in, migrating all of their organization’s data to the cloud, or they could strategically select what parts of their infrastructure remained on-premise. As a result, hybrid cloud was born and it shows no signs of going away any time soon. Experts see hybrid environments as important footholds for companies expanding into the cloud, and Gartner predicted that 90 percent of organizations will adopt hybrid infrastructure in some capacity. The benefits of hybrid cloud go beyond letting companies ease their transition to cloud services, though. A Nutanix survey found that 85% of respondents preferred hybrid architectures, with over a quarter of them saying that hybrid cloud is more secure than public or private cloud architecture.
Multicloud allowed companies to deliver at scale
Like hybrid cloud, multicloud is unique in that it’s not a technological development but rather a practice that organizations and enterprises have adopted in the past decade. Unlike hybrid cloud, which focuses on the integration of private and public clouds, multicloud adoption involves the mixing and matching of cloud services and technologies. One example of a multicloud strategy might involve duplicating your organization’s data architecture across AWS and Alibaba to serve clients in different regions more effectively. In other cases, a multicloud strategy might arise by accident as a result of Shadow IT. Regardless of how it comes about, the evidence is clear: organizations that can secure and strategically lean into multicloud benefit greatly from it. Multicloud organizations can avoid vendor lock-in, have improved uptime and redundancy, can easily serve multiple geographies, 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, making multicloud architectures fairly common.
Cloud containers made software development, deployment, and migration easy
Cloud containers are yet another development that arrived onto the scene this decade. This is no surprise, though, given the utility of containers. Containers can help development teams ensure the consistent performance of software across different systems and help organizations migrate existing applications into their cloud architecture. This mixed usage is essential to the popularity of cloud containers as DevOps, IT operations, and other parts of the enterprise find reasons to adopt this technology. Cloud container usage will only continue to grow, as the market is expected to reach $8.2 billion by 2025.
Microservices replaced big monolithic applications and encouraged some organizations to go “serverless”
In tandem with containerization, the rise of microservices is a trend that began this decade. Enabled by the growth of cloud systems, microservices, which break up applications into modular services, are in many cases better suited to take advantage of cloud architecture than traditional monolithic applications. This is also true in the case of “serverless” computing. Although the two trends are somewhat separate, they synergize very well. It’s no surprise then that the microservices market is poised to see substantial growth in the next few years
Service mesh created order within microservice architectures
While microservices allowed for applications to be efficiently broken up into functional components, one lesson that some organizations learned was that the microservices architecture could quickly become messy. Microservices weren’t easily capable of communicating directly with one another and gaining visibility into a service’s traffic could be hard. Service meshes rectified this by providing an infrastructure layer between microservices, allowing for communication, traffic routing, visibility, and encryption across services. Although the market for service meshes is still maturing, it’s proving to be a necessity in most microservice setups.
Edge Computing helped networks become optimized for The Internet of Things (IoT)
The rise of IoT and 5G has led to the proliferation of massive amounts of data as always connected devices communicate across networks. Edge computing has emerged as a potential solution to this problem, resulting in the rise of computing occurring at “edge” locations. This allows for data to be processed locally in real-time. Edge computing isn’t new but it’s now entering its prime, exemplified by the recent formation of Microsoft-AT&T and AWS-Verizon alliances. These two partnerships are centered on integrating 5G infrastructure with cloud applications and services at specific “edge” locations and are likely a sign of what’s to come for the future of edge computing.
We saw experimentation with blockchain in the cloud
For many people, blockchain is synonymous with Bitcoin and cryptocurrency. Although it’s true that the first documented use of blockchain is Satoshi Nakamoto’s Bitcoin, the past decade has seen startups and enterprises experiment with usages for blockchain beyond the realm of cryptocurrency. Although the obvious use case for blockchain is in financial services, companies like Walmart are experimenting with using blockchain for supply chain management. Startups in industries as varied as travel and healthcare have shown interest in blockchain as well. Preliminary evidence suggests that well-conceived and strategic implementations of blockchain in the cloud could solve long-standing problems across a variety of industries.
AI migrated to the cloud
It’s not an exaggeration to say that AI is everywhere—whether it’s AI-enabled consumer-facing devices, products and services augmented with AI, or the delivery of AI as a platform—AI is deeply integrated into our lives. 77% of today’s devices use AI in some form. Additionally, 37% of organizations have implemented AI in some fashion over the last 4 years alone, and by 2021, 80% of emerging technologies will have a basis in AI. This was made possible in part by advancements in cloud technology. Some have even argued that we should see cloud and AI as two sides of the same coin. Regardless of the relationship between cloud and AI, it’s clear that this synergy will continue paying dividends by democratizing access to AI for years to come.
Cloud-native security arose in response to cloud security gaps
Reliably securing cloud systems and infrastructure has proven to be a challenge given the speed at which organizations have adopted cloud, how fast cloud technology has evolved, and how drastically organizations’ cloud architectures tend to vary. Perhaps one of the biggest security developments in the past decade is the implementation of cloud-native security solutions that are designed to seamlessly scale and integrate with an organization’s existing cloud architecture. This insight is partly what inspired the development of Nightfall’s DLP platform, which is designed to detect and secure against data spray across a variety of cloud services and integrations. Cloud-native security is a relatively recent development, but it’s one that we expect to take off in the coming decade, especially as hybrid and multicloud architectures become more common.
Looking at 2020 and beyond
While we don’t have a crystal ball, we expect that the synergies between all of these developments will help usher in the next era of cloud technology. For example, we’re hopeful that emerging synergies between microservices, AI, and edge computing will result in an even faster and more intelligent Internet of Things. We’re also excited that organizations will likely begin adopting cloud-native tools, like Nightfall, that combine AI and cloud-native security to automate data discovery and protection.
Nightfall is the industry’s first cloud-native DLP platform that discovers, classifies, and protects data via machine learning. Nightfall is designed to work with popular SaaS applications like Slack & GitHub as well as IaaS platforms like AWS. You can schedule a demo with us below to see the Nightfall platform in action.
“This article is originally posted on Nightfall.ai”