“The problem with moving to the Cloud is deciding on where to start, how to start and what all to move to the cloud. The biggest challenge is monitoring technology advances and building the new stack. While we can easily adopt cloud, what’s important is how quickly we can do this. We need to accelerate whatever we are doing. Time to market is more important. Also, with the cloud, you need a completely different skill set. CIOs are struggling to get cloud native resources. Rather than building a stack, you can directly use managed services, you can make a predictive technology stack and get transparency and fast result that impacts your bottom line,” says Ajay Yadav, Country Head, Media Agility.
Media Agility works as an extended arm taking out Google Cloud technologies to different verticals and helping the businesses to adopt these technologies. In his presentation, Ajay Yadav, Country Head, Media Agility discusses the factors that distinguish Google Cloud from the competition in the Cloud market.
Security is the core of every Google service consumed, either in the enterprise segment, or in the consumer’s day-to-day life. Google believes Security is the utmost priority when moving to Cloud. Google has nine defence layers starting right from the chip required for BIOS to the top SaaS encryptions. Most of these security layers are built on a ML model that keeps on improving as and when the data gets improved. From security while building the application to security while deploying the application, Google has those features enabled just as checkboxes. When you are deploying an application on the Google cloud with a single service you can check the whole application vulnerability and other threats.
Whatever Google is designing and offering in the enterprise world, is trying to be in the space of open source services. So, that tomorrow if you feel something is more interesting and innovative, you don’t need to lock in yourself to a particular service or a model of Google. You should be able to port these services as and when you want.
Every single Google service that you consume today is built on an intelligent model. Even if you are using a Google Cloud platform, it gives you recommendations for the right size of optimization. Based on the behaviour and consumption on the machine that you are using, Google will suggest you to optimize your machine so that you can optimize your investment. To that extent ML is enabled with all the Google services.
This is where Google proves to be the most engineering organization. We don’t believe in moving services with a status quo, moving services from a co-location to cloud. It does help in pre-empting the challenges of scalability. But for Google, the shift to Cloud has to be transformative in nature. Even with the Data Analytics space, most of these services are managed services so that you don’t have to build an army to manage your infrastructure. What you should be focused on is innovation, which is what your business is demanding.