Retiring technical debt is a top challenge for all-in cloud model: Madhusudan Shekar, Amazon Internet Services

In an exclusive interaction with IDG India, Madhusudan Shekar, Head of Digital Innovation at Amazon Internet Services, discussed how his company is helping Indian enterprises achieve digital transformation with the help of AWS cloud platform.

According to Madhusudan Shekar, Amazon Internet Services is excited about the company’s portfolio in AI/ML, commercial databases and serverless computing as those are finding a huge amount of traction in the Indian market. 

Edited excerpts: 

How does Amazon Web Services help its customers in India to drive innovation and create intelligent enterprises? 

Enterprises across the world are looking to the cloud to scale their businesses and innovate. Similarly, Indian customers are demanding more of their IT framework, and coming to us to help them remove barriers to innovation, and respond to business demands in real time.

The customers I talk to love our pace of innovation, which helps them move at a faster clip, especially in areas such as machine learning and artificial intelligence, internet of things, and serverless computing. 

With millions of active customers and tens of thousands of partners globally, AWS has the largest and most dynamic ecosystem. Customers across virtually every industry and of every size, including start-ups, enterprises, and public sector organizations, are running every imaginable use case on AWS.

 

 

*/ /*–>*/   Indian customers are demanding more of their IT framework, and coming to us to help them remove barriers to innovation, and respond to business demands in real time. Madhusudan Shekar Head of Digital Innovation- Amazon Internet Services

What are the various technology offerings by AWS to help drive constant innovation?

AWS cloud platform offers more than 165 fully featured services across analytics, compute, databases, developer tools, enterprise applications, IoT, management tools, mobile, networking, security, and storage.  In particular, there are a few areas of technology that are particularly exciting for us and our customers. 

The first is artificial intelligence and machine learning. We have an extensive portfolio of services on artificial intelligence organized in three layers, with the lowest level for expert machine learning practitioners and the top layer is for developers that can leverage machine learning using their developer skills. AWS released more than 200 machine learning features and capabilities in 2018, with tens of thousands of customers using the services, spurred by the broad adoption of Amazon SageMaker. 

Another area where customers are seeking help is commercial databases, which are expensive, and tend to have a long lock-in period, with too many licensing terms. Customers want the performance of commercial grade databases with the pricing and friendliness of open engines. That is why AWS spent a few years building our own database engine in Amazon Aurora, a fully managed MySQL and Postgre compatible service that has at least the same durability and availability of the commercial engines, but at one-tenth of the cost.  

The next is serverless computing achieved through AWS Lambda. AWS Lambda lets customers upload code through the AWS management console, set triggers, and when those triggers are met, it runs that code. Customers don’t have to think about servers or clusters. They don’t have to think about auto-scaling or administration. It’s all done for them. With AWS Lambda, AWS pioneered the event-driven, serverless computing space. Today AWS Lambda, after just three years of launch handles trillions of executions per month. 

What are the challenges that you see in cloud migration and adoption, especially in the Indian context?

According to IDC, more than 93 percent of Indian organizations are still in the early stages of maturity when it comes to cloud adoption. While cloud adoption is a relatively easier decision for startups, thanks to the very low entry barrier, greater speed, and agility, for larger enterprises this could be a challenge owing to their technical debt. Retiring this technical debt is one of the top challenges faced by enterprise customers when it comes to the all-in cloud model. However, we have witnessed Indian customers are quickly moving to the cloud. 

Which sectors are you getting the most traction from? 

While customers across sectors are moving to the cloud, the pace of adoption is unique to each sector. When it comes to startups and digital native businesses, they have a fundamental imperative to adopt cloud and are among the fastest to embrace it. 

Alternatively, for enterprises, the pace and scale of adoption are very different as compared to a startup. The traction for AWS solutions by large enterprises is gaining momentum as they remove their legacy IT infrastructure. Enterprises today are betting on emerging technologies such as AI and ML to drive innovation and business growth. 

For example, HDFC Standard Life Insurance’s adoption of AWS Cloud to create a new data platform, Atom, is a testament to this. Atom is an agile and responsive solution that delivers a frictionless onboarding experience to customers. AWS is also witnessing an accelerated appetite for cloud solutions by public sector customers in India.

How do you see the future of cloud innovation and adoption? 

Organizations are realizing the true power of the cloud and using it creatively to be in a position to respond with the business needs in real time. Virtually all the customers we speak with today are interested in AI/ML. Startups don’t want to invest money in upfront infrastructure and hence are adopting cloud to innovate with AI and, more importantly, to scale. 

Similarly, enterprises are increasingly moving to an all-in cloud strategy, to focus on product innovation that requires speed and high computing power, while keeping costs low. At AWS, we are focused on solving some of the toughest challenges and making ML more accessible to every developer, every company irrespective of size, at the same cost structure and scalability.