CaaS Services Through AWS, Azure, and Google Cloud

CaaS Services Through AWS, Azure, and Google Cloud

CaaS Services Through AWS, Azure, and Google Cloud - Looking at Containers as a Service offering compared to other compute paradigms for cloud architectures and considering what AWS, Azure, and GCP offer.

Looking at Containers as a Service offering compared to other compute paradigms for cloud architectures and considering what AWS, Azure, and GCP offer.

On the 1st of December, 2020, as the world was preparing for the end of a turbulent year dominated by the COVID-19 pandemic among other things, AWS presented the cloud community with an early present. Container support for AWS Lambda functions. The ability to package and deploy Lambda functions as container images, hence allowing you to run your Lambda functions with the benefits that containers provide.

Serverless functions allowed the industry to get up and running with business code in an instant. The novel compute service provided the ability to break away from the complexity of setting up complex infrastructure and configurations, along with the scalability and related operations of running in production.

However, serverless offerings are in their current state, greatly limiting. For example, when attempting to use a programming language not supported by the serverless offering you’re using, or when typing to import libraries. AWS  Lambda layers targets this problem by allowing the user to add their required libraries and external code bases as 'layers' on top of your AWS Lambda function. Similarly Azure provides  Binding Extensions which is used as an open-source model for the community to build new types of bindings that can then be brought into your Azure Functions.

Unfortunately, these methods have limitations on how they may be leveraged. Hence the new container image support for AWS Lambda functions follows AWS’ goal of providing workarounds and solutions in mitigating the barriers that the cloud community is facing.

aws azure serverless lambda kubernates contaienrs

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Serverless Express – Easy APIs On AWS Lambda & AWS HTTP API

Serverless Express enables you to easily host Express.js APIs on AWS Lambda and AWS HTTP API. Here is how to get started and deliver a Serverless Express.js based API with a custom domain, free SSL certificate and much more!

Adding Code to AWS Lambda, Lambda Layers, and Lambda Extensions Using Docker

Adding Code to AWS Lambda, Lambda Layers, and Lambda Extensions Using Docker. With Docker, we have three ways to add code to Lambda that isn’t directly part of our Lambda function. Try to AWS Lambda, Lambda Layers, and Lambda Extensions Using Docker.

Serverless Proxy with AWS API Gateway and AWS Lambda

Serverless Proxy with AWS API Gateway and AWS Lambda. We can communicate between Public and Private instance via a Serverless Proxy thanks to AWS Api Gateway and AWS Lambda. Github Webhook calls a Public API Gateway, API Gateway triggers a Lambda attached to VPC.

Serverless Framework: Use AWS S3 Object Lambda to Resize Images on The Fly

Serverless Framework: Use AWS S3 Object Lambda to resize images on the fly. I will show you how to use AWS S3 Object Lambda to resize images on the fly. The Serverless Framework will be used to define the Infrastructure as Code and to simplify the deployment.

A Deep Dive into Serverless Tracing with AWS X Ray & Lambda

A Deep Dive into Serverless Tracing with AWS X Ray & Lambda. Over the past few weeks I’ve been experimenting with building a Serverless API on AWS with the goal of having everything needed to run a production system. One necessary piece was distributed tracing. While I’d seen a bit of what some non-AWS options had to offer, the extra cost of the services themselves, along with actually getting the data to them, was a bit prohibitive for what I imagined should be possible (and cheaper) with only AWS, which brought me to X Ray.