There are many different ways to be “in the cloud” these days. Being in the cloud might mean a cloud-enabled solution that went through a “lift and shift” of a legacy application to the cloud or a cloud-first solution that takes advantage of the elastic scaling capabilities in storage and compute power. But in order to take advantage of everything the cloud has to offer, your software needs to be truly cloud-native.
Being cloud-native means your approach to building and running applications takes advantage of :
a microservices-based architecture, where your application is built as a collection of small, separate and useful services (like text analytics, image processing, machine learning etc.) each of which can be deployed, scaled, (re)started or upgraded independent of one another.
The limitless flexibility and auto-scalability of cloud infrastructure and compute power to ensure that you get what you need, when you need it.
Why is it beneficial?
There are many reasons I could list, but here are just a few:
Resilience: Since a truly cloud-native application is a collection of independent services, your application can remain resilient while just one piece of it goes offline.
Development efficiency: Because of the independent and loosely coupled nature of the microservices that comprise a truly cloud-native application, developers are able to work on their individual components without needing to be as reliant on the compatibility of another team’s code with legacy software architectures. Release pace also improves with a continuous improvement approach.
Cost savings: Because being cloud-native means the services you need are spun up or down only when they are required, it leads to more cost savings as the parameters on which most cloud billing works off are efficiently used.
Future-proofing your application: By building cloud-native applications on any of the giant cloud infrastructure providers today, you can take advantage of all the goodness of the continuously improving microservices.
Happy customers/users: None of the above would really matter as much if it didn’t result delighting your customers or users. New features can be launched and improved dramatically faster than can be done with a heavy legacy approach and performance never needs to be an issue again.
As a modern platform that simplifies business analytics on Amazon Web Services (AWS), Qrvey was born cloud-native and takes advantage of over two dozen Machine Learning (ML) enabled services that enable our customers to create business analytics applications in a self-service fashion. We serve as an orchestration layer over these microservices that simplifies access and empowers a range of users (whether you are a data analyst, a data scientist or just a data enthusiast) to take advantage of them without having the super-developer grade skills that would normally be required to do so. From Amazon Comprehend for Natural Language Processing (NLP) and text analysis to Amazon Rekognition for image and video analysis and Amazon Textract for text extraction from scanned documents to Amazon Sagemaker for machine learning model building and many more, our platform allows our customers to evolve to the next generation of analytics, whether those capabilities are activated for their employees or customers.
The future isn’t just cloud anymore, it’s cloud-native.
