What’s new with AWS this week? Well, AWS kicked off the 2022 AWS Summit season with a strong serverless focus, including Amazon Aurora Serverless version 2, AWS Amplify Studio making full-stack AWS more accessible, and SageMaker Serverless Insights entering GA. Also, Amazon DevOps Guru Proactive Insights gets announced for serverless applications. Let’s get into it!
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Amazon Aurora Serverless version 2
AWS Summit San Francisco saw the announcement of the next version of Aurora Serverless. Amazon Aurora is AWS’s fully managed relational database service, and Aurora Serverless is designed to maximize the scalability of your Aurora databases.
With the release of Amazon Aurora Serverless v2, you can now scale workloads to hundreds of thousands of transactions in a fraction of a second, and fine-grained increments make scaling your relational databases faster and more efficient than ever.
Aurora Serverless Version 2 is currently available for MySQL 8.0- and PostgreSQL 13-compatible versions of Amazon Aurora.
Design and build with AWS Amplify Studio
AWS Amplify was announced in 2017 as a way to make full-stack AWS more accessible to front-end developers. Amplify already offers a rich set of tools to integrate back-end AWS services with your mobile and web applications, including authentication with AWS Cognito, and storage with S3. This week, AWS announced general availability for the much-anticipated AWS Amplify Studio, which leverages the popular design tool Figma to convert designed UI components to reusable React components.
This is an extremely powerful, low-code solution for application development and design teams working in the AWS Amplify ecosystem, potentially saving front-end developers thousands of lines of code in their AWS Amplify applications.
And if you want to see Amplify in action, you can check out Kesha Williams’s talk from Pluralsight’s Tech Skills Day event last week!
AWS machine learning goes serverless
Next up in AWS news, we got the general availability of Amazon SageMaker Serverless Inference, a fully-managed, scalable deployment strategy for your machine learning models.
When you choose Serverless Inference for your machine learning model, you only pay for the compute resources necessary based on the inference requests you’ve received. Behind the scenes, this is orchestrated by AWS Lambda, and because it’s been in preview since re:Invent 2021, it’s already fully supported in the SageMaker Python SDK.
AWS has also raised the concurrent invocation limit to 200, from the preview limit of 50.
This offering will be great for people who want to leverage machine learning, but don’t want to have to configure the underlying compute resources.
Amazon DevOps Guru supports serverless apps
Amazon DevOps Guru uses machine learning to analyze your application resources and proactively identify operational constraints which may impact your application’s future performance. The AWS Summit saw the announcement of an extension of this service, to include lambda-based serverless applications.
This new functionality can help you predict and avoid common serverless bottlenecks, such as reaching lambda concurrency limits, or exceeding read-write capacity on your DynamoDB tables.
Not only will DevOps Guru automatically detect your serverless bottlenecks, it will also provide you with steps to remediate your issues and avoid potential user impact. Currently DevOps Guru is available in 9 AWS Regions.
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