![]() ![]() If you use Python and Postgres, chances are good that you use the psycopg2 library. But I don’t think I’d welcome it quite so warmly if all it let me do was write a Lambda in C++.įor me, the big benefit of Lambda Container Images is that it lets me package dependencies with my Lambda code. It’s a little easier, and if you use one of the pre-built images you can continue focusing on your application and not the polling loop. Lambda Container Images let you deploy arbitrary code into a Lambda runtime, again with the caveat that it has to interact with the Runtime API. I’m sure that solved some class of problems, but I never ran into one of them. As long as you interacted with the Runtime API, you could deploy arbitrary code into a Lambda runtime since at least early 2018 there’s an awslabs project that shows you how to develop a C++ lambda. With normal Lambdas you don’t see this polling loop: it’s managed by the framework, which calls your deployed code when it finds an event. To operate “as a Lambda,” your container must interact with the Lambda Runtime API: an HTTP endpoint that your container’s code polls to be notified of invocation events. But if you just want to run Docker images without managing servers, look at ECS or AWS Batch don’t try to shoehorn them into Lambda. Well, that’s not strictly true: I uploaded the Docker hello-world image to my ECR registry and ran it, although Lambda complained that it exited without a valid return code. And there weren’t any tutorials floating around when I first Googled, so I figured it was worth writing one.īut first, let’s get one thing out of the way: Lambda Container Images are not a way to run arbitrary Docker images within the Lambda execution environment. They arrived just in time to solve an annoying build problem for me, so got my attention. The AppSync section in our serverless.Lambda Container Images were announced at re:Invent 2020, providing a new way to build and deploy Lambda functions. A data source, in our case a DynamoDB database.A GraphQL schema that describes our API.A set of mapping templates that will help AppSync understand how to resolve each GraphQL you send out.We are using the Serverless AppSync plugin to simplify the configuration, and all we need to provide, in addition to the authentication config, is: We start by defining how we will be using AppSync in our Serverless project. We broadly divided the process of getting a chat app running on Serverless with AWS AppSync into two parts: setting up the backend part of the service to fetch the data and deliver it via the GraphQL API, and creating a simple frontend to consume the API. ![]() Let’s get to it! Building a chat app with AppSync In this article, we show how you can get started with AWS AppSync in a Serverless project, and talk about the benefits and drawbacks of using AppSync for your Serverless applications. It’s the best of GraphQL with less complexity than before. ![]() No more GraphQL resolvers in Lambda functions. Developers can now model the data better, and deliver a more pleasant experience to the end user.ĪppSync, AWS’s managed GraphQL layer, builds on the benefits of GraphQL and adds a few more cool things in its mobile and web SDKs: subscriptions, convenient authentication via Cognito Pools, and the ability to plug in directly to a bunch of AWS services for data.ĪppSync can do a lot while still being a fully managed service, which works out great for Serverless applications. Users get from more responsive frontend apps, while also saving bandwidth. This is what allows React apps powered by GraphQL APIs to seem so fast, even if they are moving a lot of data: the moving of data happens in the background. Namely-many frontend GraphQL frameworks make a distinction between the data in the app state and the data on a remote server. But there is an additional benefit that mostly goes unnoticed. GraphQL gets a lot of praise for its expressiveness, for the idea of batching requests for data, and for its great development tooling. ![]()
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