Amazon kicked off its annual customer conference, AWS re:Invent, in Las Vegas with a few new serverless options aimed at making the management of Redshift, Aurora, and Elastic Cache serverless services easier.
AWS VP Matt Wood states that while Aurora Serverless is great for quickly getting up and running with a cloud database, it becomes difficult for customers to deal with large numbers like tens of millions of customers or millions of different records at a time, forcing them to split the database into multiple parts. As a customer, you have historically had to divide the data into ever smaller segments and then manage those segments independently in order to be able to handle that scale. It is known as sharding. Additionally, it’s a pain in the butt, Wood admitted to TechCrunch.
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“We’re announcing a limitless database, which handles all of that sharding for you under the hood completely automatically. So as a customer as your needs change, the database service itself, Aurora serverless, will be able to make those adjustments and manage those shards automatically,” Customers can now handle a single database thanks to it, and it should also eliminate a significant management burden that was present before this feature was developed.
Elastic Cache Serverless, a serverless caching solution that resides in between your application servers and database and enhances response times while saving database expenses, was also unveiled by the firm at that time, he said.
“And what we’re adding here is we’re making it all serverless in a highly available way for mission critical applications that run across availability zones. And so you can set up a highly available caches with microsecond response times, which are ready to scale for pretty much any volume of data you can throw at it in under a minute,” according to Wood.
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The company finally announced Redshift Serverless, which significantly reduces the amount of work IT must perform in the background by using AI to autonomously scale and optimize Amazon Redshift data warehouses based on query patterns and data volumes.
Because all of these alternatives are separable, Amazon takes care of all hardware management in the background and provides just the proper number of resources, scaling up as necessary so that IT doesn’t have to handle all back-end administration tasks.
