Summary of AWS blogs for the week of Mon Nov 06

In the week of Mon Nov 06 2023 AWS published 115 blog posts – here is an overview of what happened.

Topics Covered

Desktop and Application Streaming

Desktop and Application Streaming with Amazon AppStream 2.0

Transform Application Delivery with AppStream 2.0

Software-as-a-Service (SaaS) models are transforming the way organizations deliver applications to end users. Amazon AppStream 2.0 makes it easy for organizations to deliver applications without having to rewrite complex code. AppStream 2.0 has a number of advantages, including reducing the cost of deploying, managing, and scaling applications. It also enables organizations to quickly deploy applications with minimal effort and provide secure access to applications for end users.

Optimize Costs with AppStream 2.0 Fleet Options

The migration to cloud-native End User Computing (EUC) solutions means organizations have the ability to leverage the benefits of the cloud. One way organizations can do this is by using Amazon AppStream 2.0. AppStream 2.0 offers cost-optimization capabilities to help organizations scale applications without sacrificing performance. It allows organizations to allocate resources, such as compute and storage, to meet their needs. AppStream 2.0 also enables organizations to make use of auto-scaling to automatically increase or decrease resources based on user demand.

Cloud2: Your Trusted Partner

At Cloud2, we specialize in helping organizations to maximize the benefits of the cloud. Our team of experienced AWS consultants can help you to get the most out of AWS, including Amazon AppStream 2.0. We provide both professional services and managed services to help organizations migrate, deploy, and manage cloud-native applications. Together, we can ensure your organization is leveraging the power of cloud-native solutions and AppStream 2.0.

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AWS DevOps Blog

AWS CodeBuild adds support for AWS Lambda compute mode

AWS CodeBuild recently announced that it now supports running projects on AWS Lambda. AWS CodeBuild is a fully managed continuous integration (CI) service that simplifies the process of building and testing code. This new compute mode allows developers to execute their CI process on AWS Lambda base images. This makes it possible to build and test projects quickly and efficiently.

What is AWS Lambda?

AWS Lambda is an event-driven, serverless computing platform provided by Amazon Web Services (AWS). It enables developers to build applications and services that respond instantly to events and scale automatically. Lambda functions are triggered by events from other AWS services or from user-defined web or mobile applications. AWS Lambda is used to run code in response to events, with no need for servers or provisioning.

Benefits of using AWS Lambda as a compute mode for AWS CodeBuild

Using AWS Lambda as a compute mode for CodeBuild provides a number of benefits. First, it simplifies the process of building and testing code, allowing developers to focus more on the development process itself. Additionally, it helps reduce the cost associated with running a CI process, since the cost is based on the amount of time consumed and not on the number of build servers used. Finally, Lambda’s event-driven nature makes it easy to quickly scale up or down depending on the need, allowing developers to quickly adjust to changing project requirements.

Cloud2 Can Help You Get the Most out of AWS CodeBuild

At Cloud2, we are experts in AWS and can help you take advantage of the benefits of AWS CodeBuild’s new Lambda compute mode. Our team of AWS professionals can help you build a CI/CD pipeline optimized to take advantage of the features available in AWS CodeBuild using Lambda. We can also help you design and optimize your Lambda-based CI/CD pipeline for maximum performance and cost savings. Contact Cloud2 today to get started.

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Official Machine Learning Blog of Amazon Web Services

Harness the Power of Generative AI with Amazon Web Services

Ensure Trust and Safety with Amazon Comprehend

Organizations relying on large language models (LLMs) to power AI applications are increasingly focused on data privacy, as well as preventing abusive and unsafe content from being propagated. Amazon Comprehend features enable seamless integration to ensure trust and safety for AI applications. This includes handling customers’ PII data properly, and checking that data generated by LLMs follows the same principles.

Create Predictions with Machine Learning Without Code

Amazon SageMaker Canvas allows users to create ML predictions, especially for text and images, without extensive ML knowledge. This makes ML accessible to any user looking to generate business value from ML models.

Optimize Hyperparameters with Automatic Model Tuning

Creating high-performance ML solutions requires exploring and optimizing training parameters, or hyperparameters. Hyperparameters are levers used to adjust the training process and vary depending on the model and task at hand. Amazon SageMaker Automatic Model Tuning helps explore hyperparameters in an efficient and cost-effective way.

Automate ML Pipelines with Model Registry

Building an MLOps platform to bridge the gap between data science experimentation and deployment requires meeting performance, security, and compliance requirements. Amazon SageMaker Model Registry automates ML pipelines and helps ensure regulatory and compliance requirements.

Customize Coding Companions for Organizations

Generative AI models for coding companions are usually trained

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