In tidylab/microservices: Breakdown a Monolithic Application to a Suite of Services

source(file.path(usethis::proj_get(), "vignettes",  "_common.R"))

Why should I use Microservices?

What is the nature of R Applications?

• Most applications are used by a small amount of users, if any
• Most applications are seldom used concurrently

Why should I use a Microservices with R applications?

A microservice is a piece of business functionality with clear interfaces. Implementing an Microservice around an R application, allows its integration to platforms such as Android applications, Python applications, and commercial off-the-shelf products (COTS) products. This is because, a typical microservice is a process that communicate over a network throughout HTTP requests. The caller, whether it is a Website, Android application or even another R application, is neither aware nor care about the programming language that powers the service.

stop("Adding a Microservice increases complexity. You must have good reasons to do so.")

message("
Good reasons to add a Microservice:

1. Scalability for non-uniform traffic
2. Error resilience
3. Separate deployments
4. Complete isolation
5. Different requirements
")

Microsrvice as an R package

We can write a microservice as an R extension, specifically in a pseudo-package manner. In this mode, we take advantage of well-documented practice and mature toolkit designated to develop R packages. To be clear, our microservice is not an R package, rather it is built as an R package. Writing a microservice as an R package means:

1. We use the standard R package folder structure as a cookie cutter;
2. We develop (write, document and test) the microservice functionally as they were functions of an R package.
3. We use mature, i.e. existing and well-established, toolkit to facilitate the development.

While development of microservices and R packages share folder structure and toolkit, they have a distinctly different purpose. In short, R packages "serve" microservices, but not the converse. Rather, microservices are stand-alone applications that serve a user or another system. Microservices are built primarily be practitioners.

Layering the Microservice Functionallity

Seperation of Concerns

We can separate the concern of microservice functions into two:

1. Core-domain functions. These functions are not aware of the API.
2. API functions. These functions wrap core-domain functions.

Where does each function belong?

Core functions belong under the R folder. For example, the function demo$class_input (see excerpt) is part of R/demo.R. This function receives any object and returns its class. It can operate without an API, e.g. calling demo$class_input(mtcars) returns data.frame.

demo <- new.env()

demo$class_input <- function(x = NULL){
    return(class(x))
}

API function, including entrypoints and endpoints, are stored outside the R folder. In this demonstration they are stored under inst/entrypoints and inst/endpoints, respectively. We discuss in entrypoints and endpoints in length in subsequent documentations. For now, an example for an endpoint that wraps demo$class_input is a nameless function located under inst/endpoints/plumber.R:

function(x = NULL){
    x <- x |> jsonlite::fromJSON(flatten = TRUE)
    demo$class_input(x)
}

As you can see, the nameless function knows about the existence of demo$class_input, but not the converse.

tidylab/microservices documentation built on Oct. 3, 2022, 6:48 p.m.