In the most recent installment of the Serverless Dash series, we’ll look at implementing proper authentication using Cognito. This post covers setting up the user pool, the app client and also the logout option.
Many projects get to the point where your sophisticated infrastructure delivers reports to S3 and now you need a way for your end users to get them. Giving everyone access to the AWS account usually doesn’t work. In this post we’ll look at an alternative - we’re going to build a Serverless S3 Explorer with Dash, Lambda and the API Gateway.
I’ll teach you how to add interactive basic auth to the Serverless Dash app that we deployed recently.
Today I’m going to show you how to deploy a Dash app in a Lambda Function behind an API Gateway. This setup is truly serverless and allows you to only pay for infrastructure when there is traffic, which is an ideal deployment model for small (internal) applications. Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas.
When setting up a microservice architecture, each individual service is often owned and managed by a different team. To achieve a higher level of resource isolation, and allow for more granular security and cost management, each service team usually deploys its resources into a dedicated AWS account. While this type of distributed approach offers many benefits in terms of productivity, scalability, and resiliency, it introduces another layer of complexity in regard to AWS cross-account communication and microservice consumption. In this blog post, I would like to show you how you can leverage AWS services like Amazon API Gateway, Lambda, DynamoDB, and VPC Endpoints in combination with Terraform to build a fully-managed and serverless cross-account microservice architecture.
When implementing REST APIs in AWS there is one service that always comes to mind - Amazon API Gateway. Even though feature-rich, properly documenting your API may become a time-consuming task relatively quickly. In this post, I would like to show you how you can use Swagger UI in combination with a serverless deployment to automatically generate interactive and up-to-date documentation for your APIs.
