What are Cloud-Native Applications?
Bill Wilder introduced the term ‘Cloud Native’ to the world through his book “Cloud Architecture pattern”, in 2012. The Cloud Native Computing Foundation (CNCF) (founded in 2015) further stimulated Bill Wilder’s idea that catalyzed its growth into a multi-billion market that is anticipated to grow at a CAGR 6.1% for the forecast period – 2019-2024. According to the Cloud Native application definition, it has an architecture that is fully based on cloud platforms that allow applications to:
- Scale horizontally to meet the customer dynamics
- Use data to automatically upgrade and help key decision-makers take proactive decisions
- Secure data and infrastructure from cyber attackers
These are possible because these are embedded with containers that are isolated from the operating system and infrastructure and contain application code and supporting elements required to run the code. These containers make the application’s infrastructure robust and immutable. It further helps in faster development and deployments making application delivery and experience better.
With these benefits, it is easy to create hundreds and thousands of containers for an application. To manage such a massive amount of containers, most of which are ephemeral, container orchestration engines such as Kubernetes come into the picture.
What is Kubernetes?
Kubernetes is the brainchild of Google and is now a part of the CNCF. Kubernetes cloud-native applications rely on containerized infrastructure that makes them more portable. It means these applications can be easily moved from on-premises to the cloud or from one cloud to another.
At its core, Kubernetes capabilities are governed by its goals:
- Distribution of containers to maximize the capacity of the application
- Make applications scale up or down to adapt to the changes in demand.
- Continuously run the development and deployment process without unprecedented outages.
Cloud-Native Applications Using Kubernetes Architecture
Cloud-native applications using Kubernetes are architectured to handle basic server sider configurations that include networking and storage. The configuration also provides the relevant data for container analysis.
For this, a master code works at the heart of the Kubernetes application that manages the clusters and worker nodes. These worker nodes have containerized applications that are grouped and run using “pods”- a place where all the containers share the same context, resources, and lifecycle.
Kubernetes Capabilities For Enterprises
Gartner’s Top 10 Trends in Data and Analytics for 2020 report reveals that the unprecedented market shift due to covid has accelerated the enterprises to leverage the combination of data and analytics technologies with artificial intelligence. It means enterprises would be dependent on more data-driven cloud applications than before to respond proactively to such a global digital paradigm shift.
Therefore, managing and processing data at various nodes with several containers becomes a cumbersome and often erroneous task. It is where Kubernetes helps enterprises in making their cloud-native applications efficient and agile.
For enterprises, Kubernetes offers benefits in a way that helps them meet their customer expectations, such as the availability of applications round the clock and upgrades that match up with the changing market dynamics.
Another reason behind its wide acceptance is that it empowers cloud-native applications with reduced downtime and better efficiency. It simplifies the workflows and makes high-level AI and Big data-backed automation of container operations possible.
With Kubernetes-powered containerization, all these become achievable tasks. Kubernetes is the engine that keeps the containerized applications working without ever facing blackouts.
For businesses to thrive in the digital epoch, they need solutions that help them to manage the workloads in the diversified digital workplace. Kubernetes, an open-source platform, empowers enterprises with its ability to inject cost-saving solutions and manage data centers in the cloud.
Therefore, enterprises looking for innovative ways to tackle modern workloads based on high-end data-driven technologies like AI and big data, are rapidly embracing cloud-native applications using Kubernetes.