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Aurora Serverless: No servers, no instances to set up! You pay for only what you use

Built on top of the existing Aurora database system, Aurora Serverless is the database equivalent of a serverless, event-driven compute platform, tailormade for unpredictable or intermittent workloads.

This could be Amazon’s yet another shot across the bow to Oracle. The undisputed cloud king is well aware its database segment is a small fish in a pond dominated by Oracle. But as more number of enterprises move from on-premise to the cloud, Amazon’s database market share could improve. One of the standout announcement from this year’s re:Invent conference was a “serverless database” based on and expanding upon the company’s fully managed Aurora database architecture.

Aurora Serverless will let customers create database instances that only run when needed and automatically scale up or down based on demand. If a database isn’t needed at all, it will shut down until it is needed.

This way, users will be able to pay by the second for the Aurora Serverless computation that they use – they won’t end up footing the bill for a database sitting idle overnight.

In essence, Aurora was itself a pretty good database model in itself, in an environment where the workload was predictable. But the Amazon Web Services (AWS) eventually realized the workloads can be intermittent in some cases, and equally unpredictable at other times as requests may arrive in a span of few minutes or hours per day or per week.

This is where the new variant of Aurora comes into the picture. Aurora Serverless has been designed keeping in mind workloads that are highly variable and subject to rapid change. Further, you are paying on a second-by-second basis, for the actual database resources you use.

“Because storage and processing are separate, you can scale all the way down to zero and pay only for storage. I think this is really cool,” AWS evangelist Jeff Barr said, describing the serverless model that builds on a clean separation of processing and storage (an intrinsic part of the Aurora architecture).

So in use cases when you have a low-volume blog site which is only used for a few minutes several times per day or week, or applications which peak for around 30 minutes each day or several times per year such as the HR budgeting and operational reporting forms, Aurora Serverless auto-scales to the capacity requirements. There could also be cases when the peak of activity is hard to predict, such as a traffic site which may get all of a sudden ‘active’ when it starts raining. Here again, the serverless database meets the needs of peak load, and then scales back down when the surge is over.

This is a rather upright feature that has been introduced. Your developers may be using databases during work hours but they certainly don’t need them on nights or weekends. Thanks to Aurora Serverless, your database automatically shuts down when not in use.

On the other hand, manually managing database capacity for each application is not a sensible approach – it can take up valuable time and lead to inefficient use of database resources. With Aurora Serverless, you simply create a database endpoint, optionally specify the desired database capacity range, and connect your applications. The endpoint is a simple proxy that routes your queries to a rapidly scaled fleet of database resources. This allows your connections to remain intact without disruptions, even as scaling operations take place behind the scenes. You can also migrate between standard and serverless configurations with a few clicks in the AWS Management Console.

Such  an on-demand, auto-scaling configuration where the database automatically starts up, shuts down, and scales up or down capacity based on your application’s needs, Aurora Serverless is truly how you ‘reinvent’ an Aurora database. 2018 will make it more clear how the new database is actually implemented.

Meanwhile, you can sign up for the preview of Aurora Serverless by filling up this form.

Abhishek Jha

Writes and reports on lnformation Technology. Full stack on artificial intelligence, data science, and music.

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