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How a container-first cloud modernization approach benefits organisations?

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By Pallab Chatterjee, Senior Director and Enterprise Solution Architect, Movate

Introduction
In the race to stay ahead in today’s tech-driven world, organisations are constantly under pressure to revamp their IT systems while cutting operational costs. One pivotal challenge they encounter is the limitations posed by traditional virtual machine-based architectures, particularly in the context of microservices. While virtual machines have served as a cornerstone of IT infrastructure for years, their inherent overhead and lack of agility hinder the seamless deployment and scaling of microservices-based applications. Even in today’s world, where 92% of global organisations are running at least one production workload with a cloud Hyperscaler, VM-based infrastructures still dominate.

That’s where container-first cloud modernization steps in. It’s a game-changer, using containerisation and cloud-native tools to shake things up. In this article, we explore the transformative benefits of Container-First Cloud Modernization and its profound impact on organisations seeking to achieve operational excellence and optimise operational costs.

What is a container-first approach?
A container-first approach involves developing or refactoring applications to run in Docker containers. These containers are lightweight yet contain everything necessary for an application to run, source code, runtime, system tools, dependencies, external libraries, and configurations. Once packaged as a container, applications can run universally, regardless of computer architecture or operating systems. Often coupled with cloud-native services, this approach amplifies its advantages.

The issue with virtual machine based architecture for microservices
Before we delve into the benefits of a container-first approach, it’s important to understand the
limitations of the traditional Virtual Machine (VM) based architecture, especially when it comes to
microservices.
-Resource intensive: Each VM runs a full copy of an operating system, which can lead to
wasted resources. This is particularly problematic for microservices, which are meant to be
lightweight and efficient.
-Slow Start-up Times: VMs can take a significant amount of time to boot up, which can slow
down the deployment of microservices and affect the agility of the organization.
-Less Portability: VMs are less portable than containers as they are closely tied to the
underlying host OS. This can create challenges when moving applications between different
environments.

Benefits of a Container-first Approach
-Improved portability: Containers encapsulate all dependencies, ensuring that applications run consistently across different computing environments. This portability simplifies the process of moving applications between environments, such as from development to production or from on-premises infrastructure to the cloud.

-Enhanced scalability: Containers can be rapidly started, stopped, and replicated. This makes it easier to scale applications in response to demand. With cloud-based container orchestration tools like Kubernetes, this scaling can even be automated.

-Increased efficiency: Containers are more resource-efficient than traditional virtual machines, as they share the host system’s OS kernel rather than requiring a full OS for each instance. This leads to significant savings in terms of system resources, which can reduce costs and improve performance.

-Faster deployment cycles: The container-first approach can streamline the software development lifecycle. Containers support CI/CD pipelines, enabling faster, more reliable deployments. This can help organisations respond more quickly to market changes and customer needs.

The rise of Kubernetes in container orchestration
Kubernetes, an open-source platform designed to automate deploying, scaling, and operating application containers, has become the de facto standard for container orchestration. It provides a framework to run distributed systems resiliently, scaling and healing applications as needed. Its popularity stems from its:
-Powerful orchestration capabilities: Kubernetes can manage complex applications composed of multiple containers, handling tasks like load balancing, network traffic distribution, and service discovery.
-Extensive ecosystem: Kubernetes has a vibrant community and ecosystem, with a wealth of available tools, services, and integrations.
-Vendor-agnostic platform: Kubernetes can run on almost any infrastructure – whether it’s on-premises, in public clouds, or in hybrid environments – providing organizations with flexibility and avoiding vendor lock-in.

Benefit Comparison for a VM-based vs Containerized architecture
For this comparison, I have chosen AWS as the cloud provider, and we have used an online retailer’s
eCommerce website as the reference workload. The following comparisons aim to mimic the
hosting in an EC2-based infrastructure vs Amazon Elastic Kubernetes Service (EKS), a managed
Kubernetes engine. Every Cloud Hyperscaler has similar capabilities, and this comparison is valid for
equivalent services across all Cloud Hyperscalers:
   
Features incomparison- Services in Comparison- Amazon EC2 Amazon EKS

Infrastructure setup

-Requires provisioning and managing EC2 instances with specific resource allocations (CPU, RAM, storage)
-Each application typically runs on

-Utilises managed Kubernetes service (EKS) for container orchestration
-Containers run on worker nodes within an EKS cluster, a separate EC2 instance, leading to potential resource wastage due to over-provisioning sharing the underlying EC2 instances for improved resource utilisation.

Deployment flexibility

-Deployment involves spinning up new EC2 instances for each application, which can be time-consuming and resource intensive.

-Deployment is streamlined through container images managed by Kubernetes, enabling rapid scaling and deployment of applications with minimal overhead.

Scalability

-Scaling requires provisioning additional EC2 instances, which may lead to underutilisation during periods of low traffic and potential over-provisioning during peak times.

-Offers horizontal scaling by dynamically scaling the number of pods (containers) based on demand, ensuring optimal resource utilisation and cost efficiency.

Cost analysis

-Costs include EC2 instance provisioning fees, typically charged based on resource allocation (CPU, RAM, storage) and uptime.

-Additional costs may arise from software licenses for operating systems and applications installed on each EC2 instance.

-Costs primarily consist of AWS EKS service fees and underlying EC2 instance costs for worker nodes in the EKS cluster.

-Containerisation minimizes overhead, potentially leading to cost savings compared to EC2 instances, especially in scenarios with fluctuating workloads

Operational overheads

-Management involves monitoring and maintaining individual EC2 instances, including patching, updates, and security configurations.

-Simplifies operations with centralised management through Kubernetes, automating tasks like scaling,
load balancing, and service discovery.

Total Cost of Ownership (TCO)

-TCO will be higher due to potential inefficiencies in resource utilisation, higher infrastructure costs, and
increased operational overheads.

-TCO tends to be lower due to improved resource utilisation, streamlined operations, and potential cost savings from utilising managed Kubernetes service for container management.

In summary, while both EC2-based and EKS container-based architecture have their merits, containerization with EKS offers a significant advantage in terms of cost efficiency, scalability, and operational simplicity for retail eCommerce organisations, making it a compelling choice for modernizing IT infrastructure on AWS.

Conclusion
A container-first cloud modernization approach offers numerous benefits for organisations, including improved portability, enhanced scalability, increased efficiency, and faster deployment cycles. By adopting this approach and leveraging tools like Kubernetes, organizations can overcome the limitations of traditional VM-based architectures, optimize costs, and position themselves for success in the digital age.

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