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Syntax errors are notorious in dynamic languages since there is no compiler. Thus you write code, have no idea if it’s right, and just run it to see if it is. The pro’s here is dynamic languages tend to be fast so this process of “does it work? does it work? does it work?” can be done many times a minute. As code bases grow, however, this starts to get tedious and error prone. Many languages have linting tools to help with this like ESLint for JavaScript and Black for Python which adds tooling complexity, but with the pro meaning you may keep the same speed of iteration.
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As soon as you need to change the name or something, delete a field, or change a field… you’ve broken the API. This means you first need to change your Lambda(s) that use this new data, and ensure your unit tests (using ReTest) pass, and your integration tests (using Mocha & JavaScript) which invoke your Lambdas directly on a QA server still work.
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SurveyJS
Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
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Functional languages like Haskell, Rust, Elixir, and Scala tick the Correctness, Functional first philosophies. However, they’re build times & deployment methodologies are are slow. They’re technically “fast” if you speak to a developer experienced in those technologies, but they’re too slow for me. Haskell and Rust have notoriously slow compile times. It’s extremely common to deploy all 4 to servers vs. serverless architectures, which often uses Docker which is also slow. Utilizing languages like TypeScript in a functional way can be done, but TypeScript compilation is notoriously slow on larger code bases or when using types over interfaces, hence the rise of native alternatives like Vite, or built-in support such as Deno and Bun.
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R: ReScript
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The elm-graphql library enables code generation. This enables us to extend the “fearless refactoring” across the entire stack. As we build, learn, and eventually change our domain model from those learning’s, we can regenerate the front-end code needed, and the compiler lets us know what to modify (I still haven’t found something this powerful for ReScript yet).
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As soon as you need to change the name or something, delete a field, or change a field… you’ve broken the API. This means you first need to change your Lambda(s) that use this new data, and ensure your unit tests (using ReTest) pass, and your integration tests (using Mocha & JavaScript) which invoke your Lambdas directly on a QA server still work.
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G: GraphQL
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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If your code as a definite shape, a compiler can help you. Things like Haskell, Scala/Gleam, TypeScript, Python Typings with mypy, and Rust have really good compilers to get you “close” to correctness. Meaning, you’ll no longer have syntax errors when you run your code.
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Syntax errors are notorious in dynamic languages since there is no compiler. Thus you write code, have no idea if it’s right, and just run it to see if it is. The pro’s here is dynamic languages tend to be fast so this process of “does it work? does it work? does it work?” can be done many times a minute. As code bases grow, however, this starts to get tedious and error prone. Many languages have linting tools to help with this like ESLint for JavaScript and Black for Python which adds tooling complexity, but with the pro meaning you may keep the same speed of iteration.
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Functional languages like Haskell, Rust, Elixir, and Scala tick the Correctness, Functional first philosophies. However, they’re build times & deployment methodologies are are slow. They’re technically “fast” if you speak to a developer experienced in those technologies, but they’re too slow for me. Haskell and Rust have notoriously slow compile times. It’s extremely common to deploy all 4 to servers vs. serverless architectures, which often uses Docker which is also slow. Utilizing languages like TypeScript in a functional way can be done, but TypeScript compilation is notoriously slow on larger code bases or when using types over interfaces, hence the rise of native alternatives like Vite, or built-in support such as Deno and Bun.
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Functional languages like Haskell, Rust, Elixir, and Scala tick the Correctness, Functional first philosophies. However, they’re build times & deployment methodologies are are slow. They’re technically “fast” if you speak to a developer experienced in those technologies, but they’re too slow for me. Haskell and Rust have notoriously slow compile times. It’s extremely common to deploy all 4 to servers vs. serverless architectures, which often uses Docker which is also slow. Utilizing languages like TypeScript in a functional way can be done, but TypeScript compilation is notoriously slow on larger code bases or when using types over interfaces, hence the rise of native alternatives like Vite, or built-in support such as Deno and Bun.
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aws-lambda-java-libs
Official mirror for interface definitions and helper classes for Java code running on the AWS Lambda platform.
L: AWS Lambda
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If you have a BFF, that means you have a front-end. If you have a front-end, you gotta host it somewhere. Amplify is an AWS managed service built for hosting Single Page Applications. It abstracts away all the existing serverless tech you’d traditionally use on AWS into a single place, automating most of it. S3 static asses, cache busting on deploy, and it even abstracts it’s own build pipeline using CodeDeploy sourced right from your code repository. Like AppSync, it creates a CloudFront distribution for you, and optionally provides automatic Route53 creation if you want at full URL.
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ReScript uses OCAML under the hood which is the fastest compiler in the world. It also has prior art of positively impacting communities, such as the MTASC compiler in the ActionScript of days past. As long as you ensure all your functions eventually have type definitions on top, Elm is also near instant. Although CloudFormation is notoriously slow, you can utilize the AWS SDK, whether in various frameworks like Serverless’s deploy function, or AWS SAM’s Accelerate to deploy your code to a QA environment in seconds. The ramp up time for new Lambda functions to be operational in an eventually consistent way is also near instant to seconds. This includes being linked to an existing AppSync setup. Finally, Amplify’s cache busting for deploying a new UI change is near instant as well.
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A: AWS Amplify and AppSync
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
