CTT Big4 News AWS Recently #AWS020

CTT Big4 News AWS Recently #AWS020

Hello Friends, welcome to Big4 Recently

AWS, IBM, Google & Azure – the Big4 Cloud Service providers. In this article, we will explore latest AWS Recently.

Application Load Balancer can now Invoke Lambda Functions to Serve HTTP(S) Requests

Application Load Balancers now support invoking Lambda functions to serve HTTP(S) requests. This enables users to access serverless applications from any HTTP client, including web browsers. With the Application Load Balancers’ support for content-based routing rules, you can also route requests to different Lambda functions based on the request content. Prior to this launch, you could only use EC2 instances, containers, and on-premises servers, as targets for Application Load Balancers, and you needed other proxy solutions to invoke Lambda functions over HTTP(S). You can now use an Application Load Balancer as a common HTTP endpoint to simplify operations and monitoring for applications that use servers and serverless computing.

Support for Lambda invocation via Application Load Balancer is available for existing and new Application Load Balancers in US East (N. Virginia), US East (Ohio), US West (Northern California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada ( Central), EU (Frankfurt), EU (Ireland), EU (London), EU (Paris), South America (São Paulo), and GovCloud (US-West) AWS Regions.

AWS Step Functions Adds More Service Integrations

AWS Step Functions is now integrated with eight additional AWS services, making workflows faster to build, simpler to secure, and easier to monitor.

AWS Step Functions allows you to add resilient workflow automation to your applications. The steps of your workflow can exist anywhere, including in AWS Lambda functions, on Amazon EC2, or on-premises. Now, AWS Step Functions is also integrated with Amazon ECS, AWS Fargate, Amazon DynamoDB, Amazon SNS, Amazon SQS, AWS Batch, AWS Glue, and Amazon SageMaker. This helps you quickly automate workflows for applications that need to run batch processing jobs, process media or data files, send notifications, and orchestrate machine learning workflows. Step Functions will pause execution of the workflow until the invoked job or task has completed, and then either retry or continue to the next step of the workflow.

AWS Serverless Application Model Supports Nested Applications Using the AWS Serverless Application Repository

You can now assemble and deploy new serverless architectures using nested applications supported by the AWS Serverless Application Model (SAM) using the AWS Serverless Application Repository. Nested applications are loosely-coupled components of a serverless architecture.

Nested applications enable you to rapidly build highly sophisticated serverless architectures by reusing services that are independently authored and maintained but easily composed using SAM and the Serverless Application Repository. Using nested applications, you can build more powerful applications, avoid duplicated work, and help ensure consistency and best practices across your teams and organizations. Today, building a service to handle bad messages in an event stream is common practice for building resilient systems. Now, you can develop that solution as a SAM application, share it via the Serverless Application Repository, and enable teams to include it as a nested application across their serverless architectures.

Nested applications using the Serverless Application Repository are available in the US East (Ohio), US East (N. Virginia), US West (N. California), US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central), EU (Frankfurt), EU (Ireland), EU (London), and South America (São Paulo) regions.

AWS Lambda Supports Ruby

You can now develop your AWS Lambda function code using Ruby. AWS Lambda is a compute service that runs your code in response to events, and automatically manages the compute resources for you. 

To get started, you simply upload your Ruby code as a ZIP file through the AWS CLI or AWS Lambda console, select the ruby2.5 runtime, and Lambda takes care of everything required to run and scale your application with high availability. You can use your favorite Ruby tools and libraries when developing your functions. You can also use the AWS Serverless Application Model (SAM) and SAM CLI to test locally, deploy and manage your serverless application authored in Ruby. Support for performance monitoring and tracing of Ruby functions with AWS X-Ray is coming soon. You can read more about the Ruby programming model in the AWS Lambda documentation.

AWS Lambda Now Supports Custom Runtimes and Enables Sharing Common Code Between Functions

AWS has announced Lambda Runtime API and Lambda Layers, two new AWS Lambda features that enable developers to build custom runtimes, and share and manage common code between functions.

Lambda makes it easy for developers to run code for virtually any type of application or backend service – all with zero administration. The Runtime API for AWS Lambda defines a standardized HTTP-based specification which codifies how Lambda and a function’s runtime communicate. It enables you to build custom runtimes that integrate with Lambda to execute functions in response to events. By leveraging the Runtime API, you can use binaries or shell scripts, and your choice of programming languages and language versions. Getting started with Runtime API is simple. When deploying your function using the Lambda management console or CLI, specify that you are providing your own runtime. During an invoke, Lambda will bootstrap your runtime code and communicate with it over Runtime API to execute the function code. With this release, we are also publishing a reference implementation of the C++ and Rust runtimes. You can read more about the Runtime API in the Lambda documentation.

Runtime API and Layers can be used independently. You can also use them together to publish custom runtimes which can be then shared as layers. You can also use the AWS Serverless Application Model (SAM) and SAM CLI to test, deploy and manage serverless applications that leverage Runtime API and Layers.

Introducing Amazon Managed Streaming for Kafka (Amazon MSK) in Public Preview

AWS has announced Amazon Managed Streaming for Kafka (Amazon MSK) in public preview. Amazon MSK is a fully managed, highly available, and secure service that makes it easy for developers and DevOps managers to run applications on Apache Kafka in the AWS Cloud without needing Apache Kafka infrastructure management expertise. Amazon MSK operates highly available Apache Kafka clusters, provides security features out of the box, is fully compatible with open-source versions of Apache Kafka allowing existing applications to migrate without code changes, and has built-in AWS integrations that accelerate application development.

Amazon MSK supports Apache Kafka version 1.1.1, and offers Amazon EC2 M5 instances as Apache Kafka brokers. 

That’s it friends in this week for AWS Recently, however please visit specific Cloud provider news that you are interested in from below links.

Author: Debashree

A Technical writer and passionate about digital life. Always eager to learn and share knowledge.

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