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Build scalable Low-Code backends with Booster

The Agile Monkey

However, these tools may not be suitable for more complex data or situations requiring scalability and robust business logic. In short, Booster is a Low-Code TypeScript framework that allows you to quickly and easily create a backend application in the cloud that is highly efficient, scalable, and reliable. WTF is Booster?

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Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning - AI

The WebSocket triggers an AWS Lambda function, which creates a record in Amazon DynamoDB. Another Lambda function gets triggered with a new message in the SQS queue. The Lambda function reads the job ID and invokes an AWS Step Functions workflow for processing data files. The response data is stored in DynamoDB.

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Innovative data integration in 2024: Pioneering the future of data integration

CIO

According to a recent report by InformationWeek , enterprises with a strong AI strategy are 3 times more likely to report above-average data integration success. By integrating IoT data with other enterprise data sources, organisations can comprehensively understand their operations, customer behaviour, and market dynamics.

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IBM and AWS Partnership Accelerates Cloud Modernization

CIO

But enterprise application portfolio and ecosystem complexity, coupled with diverse business requirements, means there is no one-size-fits-all. Typically, this journey requires strategically coordinating many overlapping objectives in line with clearly defined business outcomes and orchestrated without disrupting business continuity.

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Fundamentals of Data Engineering

Xebia

The authors divide the data engineer lifecycle into five stages: Generation Storage Ingestion Transformation Serving Data The field is moving up the value chain, incorporating traditional enterprise practices like data management and cost optimization and new practices like DataOps. Architect for scalability. It’s never finished.

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5 Questions to Ask Before Going Serverless

Modus Create

Legacy databases can’t scale fluidly with your serverless functions, creating a major bottleneck in the scalability of your serverless application. Since it was an isolated feature, we created a separate Lambda function for it on AWS. In the AWS world, the go-to options for solving this issue would be DyanamoDB or Aurora Serverless.

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Putting the stack in JAMstack

Stackery

Our secure delivery platform is used to ship Lambda functions, HTTP Gateways, Aurora database clusters, and many more services which you can view usage of in Anna’s blog on the topic. This could come from client JavaScript or from server-side infrastructure like Lambda-driven forms or video streaming services.