Hello, Cloud Gurus and welcome to AWS this week.
This week kicks off the 2022 AWS summit season,
and they did not hold back with exciting announcements from AWS San Francisco,
including Amazon Aurora Serverless scales faster than ever with version two;
AWS Amplify studio brings your full stack team together.
SageMaker Serverless insights,
enters general availability and Amazon DevOps Guru proactive
insights have been announced for serverless applications.
You're watching AWS this week with me, David Blocher.
AWS announced this week that they have released version two 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 version two,
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 two is currently available for mysql 8.0
and PostgreSQL 13 compatible versions of Amazon Aurora.
AWS Amplify was announced in 2017 as a way to make full stack AWS
more accessible to frontend developers.
Amplify already offers a rich set of tools to integrate backend AWS
services, your mobile and web applications,
including authentication with AWS Cognito and storage with
S3. This week,
AWS announced general availability where the much anticipated AWS Amplify
Studio,
which leverages the popular design tool Figma to convert design
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 frontend developers,
thousands of lines of code in their AWS Amplify applications.
If you want to see Amplify in action,
check out Kesha Williams talk from Pluralsight's Tech Skills Day event,
this past week.
You can find that link here on the screen or in the video description.
Next,
AWS has announced the general availability of Amazon SageMaker Serverless
inference, a fully managed,
scalable deployment strategy for your machinery 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.
Because it's been in preview since reinvent 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 uses machine learning to analyze your application resources
and proactively identify operational constraints,
which may impact your application's future performance. This week,
AWS announced the extension of the 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 nine AWS regions.
Finally here at A Cloud Guru,
we are making it easier than ever to grow your cloud skills.
Right now you can save on our personal plus annual plan with the link in the
description or the QR code here on the screen. That's all for this week.
Keep being awesome. Take care of each other, and I'll see you next time.