Olivier Klein says when one talks about technologies, it is not indeed a specific list, it is about technologies that do help redefine customer experiences or just improve overall operational efficiency. A big chunk of customer experience goes into data analytics – artificial intelligence (AI) and machine learning (ML) space. This in turn, is made use of in, for example, understanding voice or speech better. Thus, it is about developing more personalized customer experience and better models around how one can create better customer experiences on online platforms.
Then there is the element of actually being more operationally efficient. We do provide customers with algorithms and data sets to run operations more efficiently. For example, in India, one works work with RedBus, which does make use of services such as Amazon Sagemaker to build ML models on reviews and recommendations.
A lot of enterprises are looking into AWS to understand what are the services as well as capabilities that do allow them to move faster and also reduce their costs to operate ML.
In the case of Intuit, it received a 90 percent reduction at the time of deployment. This allows it to move a lot faster, but also time equals cost, thus, this is more cost effective.
YS: Has one noticed any trends in terms of organizations of particular sectors adopting AWS faster?
OK: Neither geographies nor industry verticals tend to define the maturity or willingness of a company to try things out. Cloud Computing has no doubts about the benefit that one has tremendous flexibility of experimentation. The level of experimenting has rather increased because of cloud computing.
YS: What challenges are enterprises facing due to rapid change and development of technologies?
OK: For us, it is always about choice and flexibility. We do give customers the flexibility to migrate from their current services to AWS as they can use the migration service. Also, in that migration process, one optimizes their platform.
For example, many of our customers have indeed asked us if we can help them with their database strategies. One does provide them choices to choose the right kind of underlying technology. One also provides them with flexibility. The key point is one informs them that they can go all into AWS by completely restructuring their respective platforms and optimizing it to a cloud-native architecture.
A lot of startups on our website to optimize for the best kind of services as well as architecture under AWS. One tends to handhold them when it comes to migration.
With traditional companies, one sees that there is a certain amount of legacy and they have these pieces of software sitting around that slowly need to be shifted. One does offer the flexibility of “lift and shift” there.
The National Australian Bank would indeed be an example that is currently on a migration process into AWS.
YS: What kind of cloud are large enterprises using today – hybrid/ public or private?
OK: One personally does believe that these terminologies do not describe how customers run in an AWS environment. If one looks at the capabilities that one provides them – any kind of development at AWS actually requires a Virtual Private Cloud (VPC). One’s customers can indeed run in a completely private isolated network environment that if they do set it up in a certain manner, can completely be disconnected from the internet.
Customers can rather pick and choose what kind of workload they want to run in which environment. One also has devices such as AWS Snowball that do allow movement of large amounts of data by having an appliance which is shipped to the customer, loaded with data and moved to a cloud environment. It can be used back and forth.
YS: Whenever one does talk about the movement of data and migration, there is always a concern about security. How is technology ensuring that an individual’s identity is protected?
OK: One is always vigilant about our customers’ data and one does not actually access our customers’ data at any point in time. But it is also about giving our customers the right kind of tools as well as services to see that they can define their security footprint that they are compliant with.
More concretely, at any given point of time at AWS, with the click of a button, a customer can indeed have his data fully encrypted. Any change in the AWS environment, can not only be traced but also be immediately accessed against the set of rules that a customer defines.
One gives customers the full flexibility to define their own requirements on how they want to set up their platform, thus making sure that changes are always traced and is also audited at any given point of time. One service called Amazon Macie, if indeed activated against a storage bucket, does look at the personally identifiable information in the buckets as well as immediately sends notifications that do trigger immediate masking of that data. Most importantly, it is using ML learning models to understand the access partners against that data.
