Amazon announces three new serverless offerings at the start of re:Invent – ​​​​TechCrunch

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Amazon kicked off its annual AWS re:Invent customer conference in Las Vegas this evening with several new serverless offerings designed to make it easier to manage its Aurora, Elastic Cache and Redshift serverless services.

Matt Wood, AWS vice president, says Aurora Serverless is great for getting up and running very quickly with a cloud database, but over time as you reach very, very large scale and are dealing with tens of millions of customers , or millions of different records, it becomes challenging for customers to handle such numbers and they are forced to split the database into multiple parts. “What you have to do as a customer to handle this scale is that traditionally you had to break the data into smaller and smaller segments and then manage those segments independently. It’s called sharding. And it’s kind of annoying,” Wood told TechCrunch.

“We are announcing an unlimited database that will do all the sharding for you completely automatically under the hood. As your needs as a customer change, the database service itself, Aurora Serverless, can make those adjustments and manage those shards automatically,” he said. This allows customers to work with a single database and should eliminate the large administrative burden that existed before this feature was developed.

While it was at it, the company also announced Elastic Cache Serverless, a serverless caching service that sits between your application servers and your database, improving response times and reducing database costs, he said.

“And what we’re adding here is that we’re making everything serverless and highly available for mission-critical applications that run across availability zones. “And so you can set up highly available caches with microsecond response times that are scalable to almost any volume of data that you can process in less than a minute,” Wood said.

Finally, the company announces that Redshift Serverless now leverages AI to automatically optimize and scale Amazon Redshift data warehouses based on query patterns and data volumes, significantly reducing IT workload behind the scenes.

Because each of these options is independent, this means Amazon manages all the hardware in the background, providing just the right amount of resources you need and scaling as needed, without IT having to worry about all the back-end management work must .