Learn Faunadb, Go and Jasmine

This application serves as an introduction to building products with a JAMStack and Serverless approach. We cover everything from the beginning:

* starting with the Gatsby client
* handling authentication with Netlify Identity
* Shipping a GraphQL server on Netlify Functions
* Building in access control with a serverless capable database

It uses tools that remove as many of the barriers as possible while also allowing upgrading in the future. Netlify Functions can grow into AWS Lambda, Netlify Identity can grow into Auth0 or Cognito, and FaunaDB can grow into DynamoDB.

Gatsby is a blazing fast static site generator built with React. Gatsby gives you all of the modern JavaScript tools you want; set up and ready to go out of the box.

gatsby

Building a Serverless JAMStack Todo app with Netlify, Gatsby, GraphQL, and FaunaDB

Go is a server-side language, but today we can compile Go code to WebAssembly as well - making it possible for us to bring programs written in minimalistic Go code into the browser!

With this collection, we will learn how to compile and run Go WebAssembly programs in Node.js and the browser, and how our Go code can interop with JavaScript and manipulate the DOM. We will also talk about configuring our VS Code workspace and optimizing the Go WASM binary size.

Go is an open-source programming language that makes it easy to build simple, reliable, and efficient software.

WebAssembly with the Go Language

This collection is a sequel to the [Building a Serverless JAMStack Todo app with Netlify, Gatsby, GraphQL, and FaunaDB](https://egghead.io/playlists/building-a-serverless-jamstack-todo-app-with-netlify-gatsby-graphql-and-faunadb-53bb) collection. In this collection we take the TODO application we built and convert it to run using Netlify Identity, AWS Lambda (using the serverless framework) and DynamoDB. We cover

* Fauna vs DynamoDB and when to use each
* Setting up AWS accounts
* Creating DynamoDB tables and data modeling differences between Fauna and Dynamo
* Converting our Netlify Functions deployment to a Serverless Framework deployment
* Implementing Custom authorizer functions on AWS

It uses tools that remove as many of the barriers as possible. Netlify Functions grows into Serverless Framework adn AWS Lambda, Netlify Identity is kept around, and FaunaDB can grows into DynamoDB.



FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.

faunadb

Converting a Serverless App to run on AWS Lambda and DynamoDB with Serverless Framework

This collection of lessons will cover a variety of topics that teach you how to work with slices and arrays in go. You'll learn how to declare them, create them using literal syntax, iterate over them, add to them, remove from them and other useful things.

Learn about slices and arrays in Go

FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.

Fauna is inspired by [Calvin](https://blog.acolyer.org/2019/03/29/calvin-fast-distributed-transactions-for-partitioned-database-systems/), has [built-in GraphQL integration](https://docs.fauna.com/fauna/current/api/graphql/), and a query language based on lambda calculus. Be sure to check out the [Jepsen analysis](https://jepsen.io/analyses/faunadb-2.5.4) and the associated [chart of consistency models](https://jepsen.io/consistency)

The Complete Guide to FaunaDB

Go is an open source programming language that makes it easy to build simple, reliable, and efficient software. It is used frequently in the container ecosystem by projects such as Kubernetes (container orchestration), Docker (containers), and Cilium (BPF networking).

This playlist is a collection of videos that will start you off on your Golang journey.

Golang from Scratch

We'll cover a small Golang program that prints a string to the terminal, showing how to set up an executable program, import a package, and build a binary.

Getting Started with Hello World in Go

Returning multiple values from a function is a common idiom in Go, most often used for returning values along with potential errors. We'll go over how to return multiple values from a function and use those values in our program.

Returning Multiple Values from a Function in Go

Functions are as useful in Go as many other programming languages. In this lesson we write a function that operates on numbers covering the func keyword, argument and return signatures, and writing the function body.

Writing a Function that Multiplies a Number by Two in Go

Golang has testing tools built into the standard go tool and the standard library. Here is how to write a unit test on a function so that you can run it with `go test`.

Writing a Unit Test in Go

iota is a constant generator that can be used to construct enums. It is effectively an infinite list that starts at 0 that can be used to produce a value for a set of constants.

iota, The Golang Constant Generator

Constants are expressions whose values are known at compile time, which means that we can generate errors for expressions using those constants at compile time as well, instead of runtime.

Golang Constants Basics

Golang includes the `go mod` command to initialize a new project. Sometimes that command fails even though it tries to be smart about where to get the name of your module from so we give an example of how to explicitly set the name of your go modules based project.

```shell
mkdir my-go-project
cd my-go-project
go mod init github.com/christopherbiscardi/my-go-project
```

Initializing a project using Go modules

FaunaDB is a Calvin inspired hosted database marketed towards JAMStack and serverless users. It is geo-replicated across multiple providers (AWS, GCP, and soon Azure), uses a lambda calculus based query language (FQL) or the built-in GraphQL support, and is quick to get started with. Don't worry about the vocabulary here (Consistency, lambda calculus, etc), FaunaDB can be quickly put to work without reading any papers and without knowing what lambda calculus is.

* [Calvin Paper](http://cs.yale.edu/homes/thomson/publications/calvin-sigmod12.pdf) (warning: pdf link)
  - [Morning Paper Overview of Calvin Paper](https://blog.acolyer.org/2019/03/29/calvin-fast-distributed-transactions-for-partitioned-database-systems/) if you don't want to read the whole paper
* [jepsen report](https://jepsen.io/analyses/faunadb-2.5.4)

An Introduction to FaunaDB

FQL is the main query language for interacting with FaunaDB. It supports all JSON types, plus some additional types like Ref, Date, and Set. FQL is based in expressions and as such everything returns a value. This makes it easy to compose logic into larger queries.

Code shown in the shell:

```
Match(Index("all_customers"))
```

Overview of the FaunaDB Query Language

When working with FQL it's often the case that you'll encounter `Ref`s. `Ref`s don't have any fields on them though! So how do we access the fields? `Get`.

```
Collections()
```

```
Collection("customers")
```

```
Ref(Collection("customers"), "244075679454331401")
```

```
Get(Ref(Collection("customers"), "244075679454331401"))
```

```
Get(Collection("customers"))
```



Refs and Get in FaunaDB

FQL Page objects have additional fields like `before`, and `data`, that may make it seem like you need to `Select` to get at the underlying array of results. However, FQL supports passing Page objects directly to functions that operate on arrays and the function will transparently operate on the contained `data` field.

```
Paginate(Match(Index("all_customers")))
```

```
Drop(1, Paginate(Match(Index("all_customers"))))
```

```
Take(1, Paginate(Match(Index("all_customers"))))
```

FQL Page objects can be arguments to array functions

`Ref`s are opaque. To access the fields on a document associated with a Ref, we first need to run `Get` on our results and then we can access fields using `Select`

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda("X", Get(Var("X")))
)
```

```
Map(
  Paginate(Match(Index("all_customers"))),
  Lambda("X", Select(["data", "firstName"], Get(Var("X"))))
)
```

Accessing fields through Refs with Select

Golang has no built-in function(s) to filter an array. This lesson will teach you two different ways to filter.

The first is to create a separate array and add the filtered elements to it. This works great, but doesn't use memory as efficiently as the second way.

The second way shows you how to filter by altering the original array in place without making another array to hold the filtered elements. But, it has a side-effect that I'll tell you about which may help you decide which approach you will use to filter your array. 

Filter an Array in Go

We walk through creating a new Database in the FaunaDB console complete with some demo data. We do some exploration of the data, introducing concepts like Collections and Indexes, before showing an example FQL query that runs against the database. This sets us up to talk about FQL in future videos

Topics

Instructors

Content Type

Building a Serverless JAMStack Todo app with Netlify, Gatsby, GraphQL, and FaunaDB

WebAssembly with the Go Language

Converting a Serverless App to run on AWS Lambda and DynamoDB with Serverless Framework

Learn about slices and arrays in Go

The Complete Guide to FaunaDB

Golang from Scratch

Getting Started with Hello World in Go

Returning Multiple Values from a Function in Go

Writing a Function that Multiplies a Number by Two in Go

Writing a Unit Test in Go

iota, The Golang Constant Generator

Golang Constants Basics

Initializing a project using Go modules

An Introduction to FaunaDB

Overview of the FaunaDB Query Language

Refs and Get in FaunaDB

FQL Page objects can be arguments to array functions

Accessing fields through Refs with Select

Filter an Array in Go

An Introduction to FaunaDB

Creating your first FaunaDB database