Demystifying the new wave of technology on the public cloud
Hyperscalers’ marketing initiatives and announcements are often around the latest lucrative addition to their catalogues. While regular upgrades and new offerings seem like a good reason to invest in these technology giants, it is also important to understand them better and take an informed decision. How do these align with your existing business infrastructure? Can they help you accelerate toward your business goals?
In this blog, we review newer technologies and their implications to guide you toward better decisioning.
As container technologies advance, cloud providers are increasingly focusing on serverless technology to take advantage of its elasticity. It isn't truly serverless, of course. Rather, from the user's perspective, they are not responsible for the operation of a public cloud environment, thus rendering it seemingly serverless.
We have witnessed the technology and IT service model transformation from traditional data centers to the cloud service models. Here is a quick overview of the different models:
- Infrastructure as a Service (IaaS) –Customers can use virtual machines and retain full control. Managing VMs is the customer’s responsibility.
- Platform as a Service (PaaS) –Customers can deploy apps on virtual machines but with lesser control. Managing VMs is the responsibility of the cloud provider.
- Software as a Service (SaaS) –Users can access software through the internet via SaaS platforms, which charge a monthly subscription fee. The cloud provider is responsible for managing apps, data and VMs.
- Function as a Service (FaaS) – This is a method of executing modular code at the edge without a server. FaaS enables developers to write and update code in real time, which can then be executed in response to events such as a user clicking on a web application function.
Growing demand, growing value of IoT
The emerging Internet of Things (IoT) provides a wide range of channels for various technologies by connecting devices and automating them with sensors. McKinsey reported that the economic effect of the Internet of Things (IoT) could range from USD 3.9 trillion to USD 11.2 trillion by 2025. According to IDC, the total number of connected devices deployed worldwide will reach 55.7 billion by 2025.
Now, these devices frequently share data and information to provide customers with greater convenience and control. In certain situations, they even allow users to automate routine operations such as ordering supplies. Despite its extensive incorporation into the consumer electronics market, IoT extends far beyond mobile devices and household appliances. Industrial internet and connected cities are IoT subsystems that aim to automate factories and metropolitan environments rather than just households.
As our present digital equipment needs to be connected to the Internet of Things, it can be safely concluded that the IoT industry is set to grow exponentially.
Gaining a competitive edge with edge computing
Edge computing is a distributed computing network that takes data sources like IoT devices and native edge servers closer to business applications. This proximity to data at its source will have significant business benefits, like quicker insights, faster response times, and more bandwidth.
The aim of edge computing is to manoeuvre the computation far from data centres towards the sting of the network, exploiting smart objects, mobile phones, or network gateways to perform tasks and supply services on behalf of the cloud. By moving services to the edge, it's possible to produce content caching, service delivery, storage, and IoT management leading to better response times and transfer rates. Simultaneously, distributing the logic in several network nodes introduces new issues and challenges.
- Amazon has already begun the Amazon Wavelength journey, which will be integrated into Vodafone's 5G network across Europe in 2021 after more than two years in beta.
- This reduces processing time from 50-200 milliseconds to 10 milliseconds.
- Azure Edge Zones expand the existing hybrid network platform by allowing distributed applications to run on premise in public and private edge data centers, and in Azure IaaS.
- Google is also collaborating with telecommunications companies, including AT&T, to install Google hardware at the network edge, to run AI/ML models and other applications for 5G solutions.
The edge market is still in its infancy; however, its complexity is just getting recognized. The edge computing market will allow diverse market players to have their say in providing edge computing products and services. These range across system integrators, major cloud providers, hardware and software vendors, telecom operators and more.
Changing the game with K8s and Containerization
Applications are packaged logically in containers, allowing them to be segregated from the environment in which they execute. This decoupling allows container-based programs to be deployed rapidly and reliably, regardless of whether the intended location is a private data centre, the public cloud, or even a developer's own laptop. Containers are designed to run the components of an application in a lighter computational environment. They boot up far faster than virtual machines, don't require a full operating system or its upkeep, and are portable across platforms, on-premises and in the cloud.
Kubernetes, often known as ‘K8s,' controls the orchestration, deployment, scaling, and maintenance of containerized systems, as well as the resources that make up the foundation of a cloud-native application. It improves your reliability by lowering the amount of time and effort you must spend on DevOps, as well as the stress that comes with these responsibilities.
Kubernetes makes the process of deploying and maintaining a software easier. It also automates rollouts and rollbacks while monitoring the health of the services to prevent disasters from occurring. Furthermore, Kubernetes will scale up or down your resources according on usage, ensuring that you're only running what you need, when you need it. Like containers, K8s allows you to manage your cluster declaratively, allowing you to switch to different versions and replicate your configuration quickly.
Kubernetes is intended for usage in a wide range of contexts, including on-premises installations, public clouds, and hybrid deployments. This enables your technology to meet your clients wherever they are, make your apps more accessible, and help your organization balance security and cost concerns, all while being tailored to your specific needs.
Understanding the different AWS Cloud Container Services
Amazon EKS (Amazon Elastic Kubernetes Service) is a managed service that allows you to run K8s on AWS without having to install, administer, and maintain your own control plane. Amazon EKS users can take use of the AWS platform's performance, scale, dependability, and availability. Furthermore, Amazon EKS connects easily with many other AWS services, and any application that runs on Amazon EKS is compatible with those that are currently operating in your Kubernetes environment.
Amazon ECS (Amazon Elastic Container Service) is a container orchestration service that allows users to effortlessly execute and deploy containerized applications on AWS. This is fast, highly scalable, and completely managed. Unlike Amazon EKS, Amazon ECS is AWS' own Docker container orchestration service.
Azure Cloud Container Services
AKS (Azure Kubernetes Service) is a K8s service that is highly available, secure, and completely managed. Azure users may utilize AKS to bring their development and operations teams together on a single platform to confidently build, deliver, and grow their containerized apps. AKS decreases the complexity and operational overhead of administering Kubernetes by shifting much of that work to Azure as a fully managed service.
GCP Cloud Container Services
GKE (Google Kubernetes Engine) is a controlled environment for deploying, maintaining, and scaling containerized applications on Google infrastructure. Your K8s control pane is handled by Google SREs (Site Reliability Engineers), who will monitor your cluster and its compute, networking, and storage resources for you, giving internal engineers more time to focus on application development.
Moving to containers is a huge transition for any company, and it won't be successful until it overcomes issues including inadequate visibility, lack of cost and usage responsibility, and outmoded IT processes.