In today’s whirlwind digital era, the transition from anonymity to prominence can happen virtually overnight. Suddenly, even the most under-the-radar companies can find themselves thrust into the public eye, experiencing an explosion in customers, transactions, and web traffic, scaling to new heights.
While this might seem like the ultimate dream for any organization, it can bring a tidal wave of challenges, especially for IT teams without access to native cloud computing. This surge in demand can strain legacy data systems to their breaking point, risking service outages and potentially paralyzing operations.
The need to handle surges in demand makes cloud native applications appealing because they can run in public, private and hybrid multi cloud systems. Containers, service meshes, microservices, immutable infrastructure and declarative APIs are elements of this approach, and IT industry observers see cloud native technologies proliferating across industries.
Today, MIT Technology Review reports that 84% of executives report having a cloud-first technology development policy and 98% of organizations already use some form of cloud computing.
The widespread adoption of cloud technology is also fueling growth in the sector, with venture capital funding rising by 27% in the past year—the first year to see funding growth in three years. The rising demand for artificial intelligence (AI) applications is largely fueling this growth, with 40% of all venture capital funding in the cloud industry going into AI startups.
Because of this rapid growth in Generative AI cloud computing, Gartner’s VP Analyst Sid Nag recently wrote that the firm expects “public cloud end-user spending to eclipse the one trillion dollar mark before the end of this decade.”
The 2025 Enterprise Cloud Index (ECI) report, a Nutanix survey of 1,500 IT and business decision-makers worldwide, showed a significant technological shift underway as generative AI (GenAI) enters a hockey-stick growth phase. This is happening just two years after OpenAI's ChatGPT kicked off the commercial GenAI industry.
The ECI findings showed that beneath the rapid adoption of new application workloads like GenAI is widespread adoption of cloud native technologies that enable seamless, secure access to data across hybrid and multicloud IT environments. When it comes to GenAI apps specifically, 70% of respondents said they have containerized or intend to containerize them, the highest percentage among all application categories.
“For AI developers, cloud native technologies deliver the ability to package models and dependencies into containers and deploy them seamlessly via orchestrators like Kubernetes,” said Dan Ciruli, senior Nutanix cloud native product manager.
“This supports portability across environments, from on-premises data centers to public clouds.”
Ciruli said that for data scientists and machine learning engineers “cloud-native tooling simplifies building machine learning pipelines and putting models into production. On the infrastructure side, using Kubernetes for dynamic resource management helps optimize expensive AI workloads.”
Businesses Bet Big on Cloud Native Technology
“Adopting cloud native platforms means that digital or product teams will use architectural principles and capabilities to take advantage of the inherent capabilities within the cloud environment,” Milind Govekar, Distinguished Vice President at Gartner, told Nutanix in 2021.
“New workloads deployed in a cloud native environment will be pervasive, not just popular. Anything non cloud will be considered legacy.”
Three years later, these predictions remain accurate. Organizations of all sizes, from multinational corporations to local businesses, are increasingly relying on native cloud computing to improve workflows and increase efficiency.
Companies are embracing cloud native technologies to build and manage applications and data across different IT infrastructures, including on-premises data centers, private cloud and public cloud services, according to Tobi Knaup, general manager for Cloud Native at Nutanix. In a podcast interview with The Forecast, Knaup explained what’s behind the acceleration of cloud native application development and why enterprises run them across hybrid multicloud IT environments, especially as they embrace new AI capabilities.
“If you're building applications on top of Kubernetes in containers, that makes them truly portable, so you can run them anywhere.”
He said cloud native applications are typically microservice-oriented and run in containers built on the Kubernetes platform. They are decoupled from underlying IT infrastructure, making them portable so IT teams to run them anywhere from public and private clouds to the edge.
“Containers are a very lightweight way to package an application, so it's very easy to ship them all around, all over the place,” he said.
He said technology leaders see cloud native resources as a way to build adaptability and resiliency into their organization’s IT infrastructure.
What Is Cloud Native Application Development?
Cloud native technology empowers organizations to use cloud computing to build and run scalable applications in modern, dynamic IT environments. Containers, service meshes, microservices, immutable infrastructure and declarative APIs exemplify this approach.
Traditionally, applications were developed and run on a physical server. Then they were modified to migrate them into a public or private cloud. Instead, cloud native apps are built and deployed in a cloud, with the cloud’s specific architecture in mind.
Core characteristics of cloud native applications include the following:
Code packaged as containers: Containers encapsulate an application's code and dependencies, ensuring consistent performance across different cloud environments, facilitating portability, and streamlining deployment processes.
Architected as collections of microservices: Applications are divided into small, independent services communicating via APIs, allowing for flexible development, deployment, and scaling of individual components.
Integrated DevOps: Merges development and operations for enhanced collaboration and productivity, embedding continuous integration and delivery into the application lifecycle for faster and more reliable software releases.
Elastic cloud infrastructure: Utilizes the cloud's ability to automatically scale resources up or down based on demand, optimizing application performance and cost-efficiency.
Automated, policy-driven resource allocation: Employs automation and predefined policies for dynamic resource management, minimizing manual intervention and ensuring efficient, reliable application operations.
Plenty of cloud-enabled software exists. Likewise, plenty of software is built in cloud sandboxes simply because it’s more convenient to keep the DevOps team in the loop. However, something developed and deployed on the cloud isn’t necessarily cloud native unless it takes advantage of distributed systems within its architecture.
In other words, cloud native apps are built on the cloud and meant for the cloud. They’re not designed to run on the server in the office. Therefore, the term “cloud native” refers not simply to where an application is built but how. Specific architecture may vary from project to project.
How Native Cloud Computing Builds Resiliency
IT organizations need the adaptability and speed-to-market that containerized applications enable. To demystify the fervor around containers, teams can view them as vehicles for freedom and flexibility across the software lifecycle. Containers effectively abstract the application from the underlying operating system.
A well-designed containerized application built with microservices design principles can be upgraded without downtime. It can also be rapidly scaled up or down and easily ported across disparate Kubernetes environments.
Many experts agree. A team of McKinsey researchers recently wrote that “Moving to the cloud can significantly improve stability compared to on-premises environments. The cloud can offer faster recovery time, more flexibility to support resiliency, and more tools that provide sophisticated resiliency capabilities.”
But, despite the many benefits associated with the transition to a cloud environment, adoption of native cloud computing still comes with the price of a steep learning curve in building cloud native environments and applications. Yet, the Global Kubernetes community around Kubernetes is beginning to make significant progress.
Scaling Out, Not Up: Cloud Native Apps & the Cattle Model
DevOps, which blends developers with operations, is a set of practices that combines software development and IT operations. It aims to shorten the systems development life cycle and provide continuous delivery with high software quality. In DevOps, two primary service models exist: pets and cattle. Cloud native apps embrace the latter.
Unlike on-premises applications and servers, where everything is part of a single, monolithic service that gets bigger as it scales up, cloud native apps leverage the concept of distributed systems to stay quick and agile.
Each part of an app gets packaged into its own container, where it acts like an independent service that runs its own processes. Together, these microservices communicate with each other to form the app’s fabric or mesh.
Any time an application needs to scale, more of these containers are provisioned and deployed automatically. It’s like calling a bunch of temporary helpers. Then, when the need disappears, they automatically de-provision to conserve resources.
Likewise, if any part of an application “gets sick” or fails to function correctly, it’s easy to simply replace it with a new microservice that’s almost entirely identical. Since it happens automatically and in real time, end users won’t notice this little switch out.
Rather than building a monolithic application that eventually crumbles under its own weight, the infrastructure of the cloud native app doesn’t fundamentally change—resources of the same type are added instead of getting bigger and (supposedly) better ones. It’s immutable. That’s why scaling in cloud native applications is sometimes expressed as “out” rather than “up.”
The result is an agile, resilient, highly scalable model. It eliminates many of the problems associated with legacy systems that have become too large, calcified, and so convoluted it’s impossible to tell where something goes wrong.
Rather than becoming large and all-encompassing, “cloud native architecture focuses on achieving resilience and scale through horizontal scaling, distributed processing, and automating the replacement of failed components,” wrote cloud native expert, Tom Grey.
For example, if a web service experiences a usage spike thanks to a Tweet, a cloud native app can assemble more containers to meet demand without taking the whole office out by tying up the server.
Other Features of Cloud Native Apps
Containers and microservices are some of the most common features that appear in cloud native development. However, they’re far from the only features that set cloud native architecture apart from cloud-enabled or traditional applications.
With a cloud native application, the typical variables and factors include:
Web-centric languages: Rather than C/C++, cloud native apps more frequently leverage HTML, Java, .Net, PHP or Ruby.
Real-time updating: Like other cloud applications, cloud native apps leverage real-time updates to maintain availability. Likewise, if a part of the app goes down, it’s far less noticeable because another container will appear to replace it.
Multi-tenancy: Cloud native apps assume multi-tenancy or the presence of multiple apps sharing resources in a single space. This is something traditional applications struggle with even today.
Redundancy: If one container goes down, another one can take its place. More redundancy in cloud native apps means fewer instances of downtime. In contrast, if a server goes down, then everyone will notice.
Automation: Cloud native apps are designed to leverage automation to handle things like dynamic scaling. That’s part of what keeps them so responsive and agile.
Statelessness: Because the state of the cloud natives app is stored in an external entity, it’s not tied to the infrastructure it runs on, unlike a web service running from a server. That makes it easier to run in a distributed manner and helps keep it available.
Defense-in-depth: Perimeter defense doesn’t work with the cloud, requiring more thorough authentication mechanisms and zero trust models to be put in place. Cloud native app security is simultaneously more lightweight and more effective.
This is an updated version of the original article published on March 16, 2021. Marcus Taylor contributed to this update.
Michael Brenner is a keynote speaker, author and CEO of Marketing Insider Group. Michael has written hundreds of articles on sites such as Forbes, Entrepreneur Magazine, and The Guardian and he speaks at dozens of leadership conferences each year covering topics such as marketing, leadership, technology, and business strategy.
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