The Case For Go Backends

Building performant, scalable, and cost-effective backends is crucial for modern software applications. With the rise of serverless architectures and cloud computing, the choice of programming language can have a significant impact on the performance and cost of an application. In this document, we will evaluate the performance, scalability, and developer experience of three popular programming languages - TypeScript, Rust, and Go - in the context of building distributed, serverless applications. By understanding the strengths and weaknesses of each language, we aim to identify the best choice for building backends that meet specific requirements and constraints. The goal is to help developers strike a balance between performance, scalability, and cost-effectiveness while ensuring a positive developer experience.

Table of Contents

• Pros/Cons of TypeScript, Rust, and Go
  • TypeScript
  • Rust
  • Go
• Performance
• Scalability
• Developer Experience
• Conclusion
• Addendum
  • Paradigm Discussion - Functional versus Object-Oriented Programming
  • Other languages not considered - Rust and Elixir

Pros/Cons of TypeScript, Rust, and Go

TypeScript

Pros:

One of the primary benefits of TypeScript is its ease of use for developers who are familiar with JavaScript. It has a large developer community and ecosystem of libraries and tools, making it a popular choice for developing web applications. Additionally, TypeScript supports modern language features such as async/await, decorators, and interfaces, which makes it suitable for developing complex applications. It also provides good performance for small to medium-sized applications.

Cons:

One of the drawbacks of TypeScript is that it can have a performance overhead due to its type-checking and compilation processes, which may affect the performance of larger applications. Moreover, TypeScript may not be the best choice for low-level system programming since it is a high-level language. Finally, while TypeScript can handle high traffic applications, it may not be the ideal choice for developing large-scale, high-traffic applications that require high performance.

In summary, TypeScript is a useful programming language for web application development, particularly for developers who are already familiar with JavaScript. However, its performance overhead and limitations may make it less suitable for developing larger and more complex backends.

Rust

Pros:

One of the significant strengths of Rust is its speed and efficiency, with low memory usage. It is a strongly typed language that offers zero-cost abstractions, which makes it suitable for low-level system programming and performance-critical applications. Moreover, Rust ensures a high degree of safety and memory safety, which is an essential aspect of developing reliable and secure software. Additionally, Rust provides good support for concurrency and parallelism, which makes it an excellent choice for developing applications that need to handle multiple tasks at the same time.

Cons:

One of the major challenges of Rust is its steep learning curve, especially for developers who are not familiar with systems programming. It requires a different way of thinking and an understanding of how computer systems work. Furthermore, Rust has a smaller developer community and ecosystem of libraries and tools than other programming languages, which can be a drawback for developers who need to find solutions quickly. Finally, Rust can be more verbose than some other languages, which may slow down the coding process.

In summary, Rust is a robust programming language that can provide significant benefits for developers who need to create fast and reliable backends. However, it may require some time to learn and understand, and its smaller community may make it more challenging to find solutions quickly.

Go

Pros:

Go is a fast and efficient language with low memory usage, making it an excellent choice for building high-performance applications. It also provides good support for concurrency and parallelism, which makes it ideal for developing applications that require efficient handling of multiple tasks. Go is simple and easy to learn, with a clean syntax and standard library that simplifies the development process. Moreover, it offers good performance for medium to large-scale applications while maintaining a good balance between performance and ease of use.

Cons:

One of the drawbacks of Go is that it is less powerful than some other languages, with fewer language features. However, this simplicity is also a strength of the language since it makes it easier to write and maintain code. Garbage collection in Go can impact performance in certain scenarios, which may limit its suitability for some applications. Finally, Go has a smaller ecosystem of libraries and tools compared to some other languages, which can be a disadvantage for developers who require access to a wide range of tools and libraries.

In summary, Go is a powerful and efficient programming language that is ideal for developing high-performance backends that require concurrency and parallelism. However, its simplicity and limited ecosystem of libraries and tools may make it less suitable for some applications.

Performance

TypeScript is a popular superset of JavaScript that adds optional static typing to the language. Many developers prefer TypeScript due to its ease of use and its similarity to JavaScript. However, when it comes to performance, TypeScript may not be the best choice. Since TypeScript is compiled into JavaScript, it incurs some performance overhead due to the additional type-checking and compilation processes. Nevertheless, the performance impact of TypeScript is usually minimal, particularly for small to medium-sized applications.

In the following code snippet, we are using TypeScript to calculate the 45th Fibonacci number. The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding numbers. The first two numbers in the sequence are 0 and 1, and each subsequent number is the sum of the two preceding numbers. The 45th Fibonacci number is 1,134,903,170. In this code snippet, we are using recursion to calculate the 45th Fibonacci number. Depending on your machine's performance, this code snippet may take up to 17 seconds to run.

function fibonacci(n: number): number {
  if (n < 2) {
    return n;
  }
  return fibonacci(n - 1) + fibonacci(n - 2);
}

const result = fibonacci(45);
console.log(result);

Rust is a programming language that prioritizes speed and safety in systems programming. Its excellent performance is a result of its zero-cost abstractions and high-level control over system resources. Rust's ability to handle low-level system programming, coupled with its performance, makes it an ideal choice for serverless functions that require high performance.

As an example, using Rust, we can calculate the 45th Fibonacci number in as little as 10 seconds.

fn fibonacci(n: u32) -> u32 {
    if n < 2 {
        return n;
    }
    fibonacci(n - 1) + fibonacci(n - 2)
}

fn main() {
    let result = fibonacci(45);
    println!("{}", result);
}

Go is a compiled programming language developed by Google, which prioritizes simplicity, performance, and concurrency. Go's performance is excellent due to its fast compilation, optimized concurrency, and garbage collection. Its simplicity also makes it easy to write and maintain code. As a result, Go is a popular choice for building high-performance serverless applications, thanks to its low memory footprint and fast execution speed.

As an example, using Go, we can calculate the 45th Fibonacci number in approximately 5 seconds.

package main

import "fmt"

func fibonacci(n int) int {
    if n < 2 {
        return n
    }
    return fibonacci(n-1) + fibonacci(n-2)
}

func main() {
    result := fibonacci(45)
    fmt.Println(result)
}

Wait, isn't Rust supposed to be faster than Go? Rust is generally considered faster than Go due to its zero-cost abstractions, memory safety, and low-level control over system resources. The Fibonacci version is a recursive function that creates a large number of temporary objects in memory, which can put a strain on the memory management system of the language. Rust's ownership model ensures memory safety without the need for garbage collection, which can sometimes lead to better performance in scenarios where memory management is critical. However, the Rust implementation of the Fibonacci function uses a naive recursive algorithm, which can lead to a large number of stack frames being allocated. In contrast, Go's garbage collector is highly optimized and can perform concurrent garbage collection, which can help manage the memory usage of the Fibonacci function. In this particular scenario, the garbage collector in Go help manage the memory usage of the Fibonacci function more efficiently than Rust's ownership model, leading to better performance.

When it comes to building serverless functions that require high performance, Rust and Go are both excellent choices. For a deeper analysis of their performance, there is an entertaining and informative video on YouTube that compares TypeScript, Rust, and Go. Rust's focus on speed and safety makes it ideal for low-level system programming, while Go's simplicity, speed, and optimized concurrency make it an excellent choice for building high-performance serverless applications.

While TypeScript is a great language, it may not be the best choice for high-performance applications. However, its ease of use and familiarity with JavaScript make it an excellent choice for smaller applications, such as Microsoft's just-js.

For high-performance serverless applications, Rust and Go are both excellent options, while TypeScript may be better suited for smaller applications or projects that require greater ease of use and familiarity with JavaScript.

Scalability

Scalability is a critical factor to consider when building serverless applications. With the right language and tools, it's possible to build highly scalable applications that can handle increasing levels of traffic, data, or complexity.

TypeScript is a popular choice for building serverless applications on AWS Lambda. With TypeScript, it's easy to create serverless functions that can handle API Gateway requests, process data, and interact with other AWS services.

import { APIGatewayProxyHandler } from 'aws-lambda';

export const handler: APIGatewayProxyHandler = async (event, context) => {
  console.log('Handling request:', event);

  const response = {
    statusCode: 200,
    body: JSON.stringify({ message: 'Hello, World!' }),
  };

  console.log('Returning response:', response);
  return response;
};

Rust is another language that works well with AWS Lambda. Rust's fast execution speed, low memory usage, and strong memory safety features make it well-suited for building high-performance and secure serverless applications. Additionally, Rust has a growing ecosystem of libraries and tools specifically designed for building serverless functions, which makes it easy to create and deploy serverless functions in Rust.

use lambda_http::{handler, lambda, IntoResponse, Request, Response};
use std::error::Error;

fn main() -> Result<(), Box<dyn Error>> {
    lambda!(my_handler);
    Ok(())
}

fn my_handler(_: Request, _: lambda_runtime::Context) -> Result<impl IntoResponse, lambda_http::Error> {
    Ok(Response::builder()
        .status(200)
        .header("Content-Type", "application/json")
        .body(r#"{"message": "Hello, World!"}"#.into())
        .expect("Failed to render response body"))
}

Go is perhaps the best language for building scalable serverless applications. Go offers several advantages over other languages that make it well-suited for building serverless functions:

• Fast startup time: Go has a very fast startup time, which is important for serverless applications because the function needs to start up quickly in response to an event.
• Low memory usage: Go uses less memory compared to TypeScript and Rust, which can be important for reducing the cost of running serverless functions in a cloud environment.
• Concurrent execution: Go's lightweight thread model and support for concurrency make it easy to write code that can handle multiple requests in parallel, which is important for scaling serverless applications.

package main

import (
    "context"
    "encoding/json"
    "fmt"
    "github.com/aws/aws-lambda-go/events"
    "github.com/aws/aws-lambda-go/lambda"
)

type Response struct {
    Message string `json:"message"`
}

func handler(ctx context.Context, request events.APIGatewayProxyRequest) (events.APIGatewayProxyResponse, error) {
    fmt.Printf("Handling request: %+v\n", request)

    response := Response{
        Message: "Hello, World!",
    }

    body, err := json.Marshal(response)
    if err != nil {
        return events.APIGatewayProxyResponse{}, err
    }

    fmt.Printf("Returning response: %+v\n", response)
    return events.APIGatewayProxyResponse{
        StatusCode: 200,
        Headers:    map[string]string{"Content-Type": "application/json"},
        Body:       string(body),
    }, nil
}

func main() {
    lambda.Start(handler)
}

One example of a scalable serverless application built with Go is a real-time chat application. With Go, it's definitely feasible to build a chat application that can handle a high volume of messages from multiple users. By using a microservices architecture, load balancing, and database sharding, it's possible to build a highly scalable chat application that can handle millions of concurrent users.

While Go is a great language for building scalable serverless applications, it's not perfect. There may be situations where other languages or tools are a better fit, depending on the specific needs of the application. For example, some applications may require more sophisticated machine learning capabilities, or may need to be integrated with other systems that are written in different languages. In these cases, it may be appropriate to use other languages or tools to build the application.

In summary, when it comes to building scalable serverless applications, Go is the clear winner. While TypeScript and Rust are both excellent languages with their own strengths, Go's combination of fast startup time, low memory usage, and support for concurrency makes it a great choice for building build highly scalable applications that can handle a high volume of traffic and data.

Developer Experience

TypeScript, Rust, and Go are also known for providing a great developer experience, with features that can make it easier and more enjoyable for developers to write and maintain code. Here are some ways in which these languages provide a good developer experience:

/w TypeScript

• Type safety that catches errors at compile time, rather than at runtime.
• Great tooling support, including powerful code editors, linters, and debugging tools.
• A large and growing ecosystem of libraries and frameworks, with strong support for web development and server-side development.
• A strong focus on developer productivity, with features like optional chaining and nullish coalescing that can make code more concise and readable.

However...

• Type annotations can add complexity and verbosity to the code, especially for simple or small-scale projects. For example: const add = (a: number, b: number): number => a + b; versus const add = (a, b) => a + b;
• The learning curve for TypeScript can be steeper than for other languages, especially for developers who are not already familiar with JavaScript.
• Code editors and other development tools may require additional configuration to work properly with TypeScript, which can be time-consuming.

/w Rust

• A powerful type system that ensures memory safety and eliminates data races.
• Great tooling support, including a powerful package manager and code editors with strong syntax highlighting and code completion.
• A focus on performance and efficiency, with low-level control over system resources and efficient memory management.
• A growing ecosystem of libraries and frameworks, with support for web development, systems programming, and game development.

However...

• Rust's strong type system and borrow checker can be challenging for developers who are not used to working with memory-safe languages, especially when dealing with complex data structures or concurrency.
• The syntax and language features in Rust can be more complex and verbose than in other languages, which can make it harder for some developers to learn and write code.
• The Rust compiler can be slower than some other languages, especially when dealing with large codebases or complex projects.

/w Go

• A simple and intuitive syntax that is easy to learn and read.
• Great tooling support, including a powerful command-line interface and a growing ecosystem of code editors and IDEs.
• A focus on performance and concurrency, with lightweight threads and efficient memory management.
• A growing ecosystem of libraries and frameworks, with support for web development, distributed systems, and cloud computing.

However...

• Go's focus on simplicity and minimalism can make it less expressive than some other languages, which can make some code less elegant and harder to read.
• Go's type system can be less flexible than other languages, which can be limiting for some projects.
• Go's tooling and package management system can be less user-friendly than other languages, especially for developers who are used to more sophisticated tools and frameworks.

TypeScript, Rust, and Go all provide a great developer experience, with features that can make it easier and more enjoyable to write and maintain code. However, there are also potential challenges and drawbacks that developers may face when working with these languages. These include issues with verbosity, complexity, and learning curve, as well as challenges with tooling, type systems, and performance.

Cost Efficiency

With TypeScript shops on the rise, this guide is tailored to help those contemplating a shift to Rust, Go, or staying with their current language.

Cost of Development

Choosing to stick with TypeScript while not taking advantage of the benefits that Rust or Go offer can still be a viable option for certain projects. TypeScript is a mature language with a rapidly expanding ecosystem, robust tooling support, and an emphasis on developer productivity and safety. Rust and Go have their unique advantages, such as efficient memory management, low-level control, and performance, but these may not always be necessary for every project. If a project doesn't require these features or if the development team lacks the proficiency or experience to use these languages effectively, then staying with TypeScript can be an excellent decision.

Moreover, sticking with TypeScript can be a wise choice if a project has already invested significantly in TypeScript code, and the cost of migrating to a new language would be prohibitive. It is often more practical and efficient to continue working with the same language and building on the existing codebase instead of starting anew with a different language. TypeScript, particularly in web development, remains an excellent choice.

Making a switch from TypeScript to Rust can provide numerous benefits, especially for projects that require efficient memory management, performance, and low-level control. Rust is a systems programming language that offers developers the ability to manage and allocate memory at a low level while still ensuring safety and security. However, there are also some challenges that come with switching to Rust, particularly for developers who are unfamiliar with working with memory-safe languages or who are not accustomed to Rust's syntax and features. Rust has a steeper learning curve than some other languages, and its strong type system and borrow checker can pose challenges for developers at the beginning. Additionally, the tooling and ecosystem for Rust may not be as established or robust as those for more established languages like TypeScript.

The decision to stick with TypeScript and forego the advantages of Rust or Go will depend on the specific requirements of the project and the goals of the team. TypeScript is a mature language with a rapidly growing ecosystem, strong tooling support, and a focus on developer productivity and safety. Rust, on the other hand, is an excellent choice for building network servers.

Switching from TypeScript to Go can provide multiple benefits, especially for projects that require fast compilation times, low memory footprint, and high concurrency. Go is designed to be a simple, scalable, and efficient language that makes writing highly concurrent programs a breeze. However, transitioning to Go may pose some challenges, particularly for developers who are unaccustomed to working with statically-typed languages or those who are not familiar with Go's syntax and features. Go's type system and error handling can be tricky for developers to work with at first, especially if they are used to more dynamic languages like TypeScript. Additionally, the tooling and ecosystem for Go may not be as mature or robust as those for more established languages like TypeScript.

The return on investment of switching from TypeScript to Go will depend on the specific requirements of the project and the goals of the team. The learning curve and migration costs associated with switching require a significant investment in time and resources. However, Go's simplicity and ease of use make it an attractive choice for developers who are transitioning from TypeScript to Go. Go is a straightforward and intuitive language that is relatively easy to learn, especially for developers who are already familiar with C-like syntax. Moreover, Go's emphasis on minimalism and simplicity makes it easier to write and read code, resulting in faster and more efficient development. These advantages can translate into measurable returns on investment for development shops that convert from TypeScript to Go. For instance, developers who quickly learn and use Go may be able to speed up their work on new projects, reducing development costs. Also, the simplicity and efficiency of Go code can reduce the amount of code that needs to be written and maintained, minimizing the risk of errors and bugs.

Go is an excellent choice for developing highly concurrent and distributed systems such as network services, cloud-based microservices, and serverless applications.

Cost of Operation - Serverless

Serverless applications can be a cost-effective way to build and run applications, but they can also be expensive if they are not designed and implemented properly. Here are some ways in which TypeScript, Rust, and Go can help to keep serverless applications cost-efficient:

• Efficient resource utilization: All three languages, TypeScript, Rust, and Go, have a strong focus on efficient resource utilization, which can help to reduce the overall cost of running serverless applications. This can be achieved through features such as efficient memory management, low memory overhead, and optimized code execution. a. Rust is often considered to be the most efficient language in terms of resource utilization because of its ownership model, which helps to ensure that memory is managed correctly and efficiently, reducing the risk of memory leaks and other performance issues. Additionally, Rust's built-in optimizer produces highly optimized code that can run efficiently on both CPUs and GPUs. b. However, both TypeScript and Go are also known for their efficient resource utilization. TypeScript benefits from the strengths of the underlying JavaScript engine, which has been optimized for years, and Go has built-in support for concurrency, lightweight threads, and a garbage collector, which can all help to ensure efficient memory management and optimized code execution.

• Rapid startup times: Serverless applications are designed to scale up and down quickly based on demand. This means that fast startup times are essential to ensure that the application can respond to changes in demand in a timely manner. TypeScript, Rust, and Go are all designed to provide fast startup times, which can help to keep serverless applications cost-effective.
  a. Go is often considered to be the fastest language for startup times because of its simplicity and minimalism. Go's lightweight threads, called "goroutines," can be created and destroyed quickly, and its simple syntax can help to reduce the time required for compilation and startup.
  b. TypeScript and Rust can also provide fast startup times. TypeScript's compilation process is generally fast, especially for small and medium-sized applications, and its support for incremental compilation can help to reduce the time required for recompilation. Rust also provides fast startup times because of its optimized code execution and its use of LLVM, a compiler infrastructure that can produce fast and efficient code.

• Concurrency support: Serverless applications often need to handle multiple requests simultaneously. Concurrency support is essential to ensure that the application can handle these requests efficiently, without incurring additional costs. TypeScript, Rust, and Go all have strong support for concurrency, which can help to keep serverless applications cost-effective.
  a. Go is often considered to be the strongest language for concurrency support because of its built-in support for lightweight threads called "goroutines," as well as its channels, which can be used to communicate between goroutines. This makes it easy to write highly concurrent and distributed systems that can handle multiple requests efficiently.
  b. TypeScript and Rust also have strong support for concurrency. TypeScript supports asynchronous programming through its support for Promises and async/await syntax, which can help to write highly concurrent applications that handle multiple requests efficiently. Rust's ownership model helps to ensure that code is thread-safe and free of data races, which can make it easier to write highly concurrent applications that handle multiple requests efficiently.

• Smaller code size: Smaller code size can help to reduce the overall cost of running serverless applications, as it reduces the amount of code that needs to be deployed and executed. TypeScript, Rust, and Go all have features that can help to reduce code size, such as built-in optimization and tree-shaking.
  a. Rust is often considered to be the best language for smaller code size because of its built-in support for static linking, which can help to reduce the size of the final executable. Additionally, Rust's ownership model helps to ensure that code is free of unused or unnecessary components, which can help to reduce the code size further.
  b. TypeScript and Go also have features that can help to reduce code size. TypeScript's incremental compilation can help to avoid recompiling unchanged code, which can help to reduce the size of the final code bundle. Go's built-in optimization and tree-shaking can help to reduce the size of the final executable by removing unused components.

• Smaller container size: Smaller container size can also help to reduce the overall cost of running serverless applications, as it reduces the amount of resources that are required to deploy and run the application. TypeScript, Rust, and Go all have features that can help to reduce container size, such as built-in support for static linking and compiled binaries.
  a. Rust is often considered to be the best language for smaller container size because of its built-in support for static linking and compiled binaries. This makes it possible to create fully self-contained binaries that can be deployed without requiring additional dependencies or runtime libraries. Additionally, Rust's ownership model helps to ensure that only the necessary components are included in the final executable, further reducing the container size.
  b. TypeScript and Go also have features that can help to reduce container size. TypeScript's incremental compilation can help to avoid recompiling unchanged code, which can help to reduce the size of the final container. Go's built-in support for static linking and compiled binaries can also help to reduce the size of the final container.

Overall, TypeScript, Rust, and Go can all help to keep serverless applications cost-effective by providing efficient resource utilization, rapid startup times, strong concurrency support, smaller code and container size, and other cost-saving features. However, the specific cost savings will depend on the individual application and the way it is designed and implemented.

Conclusion

The choice of programming language is a critical factor in building performant, scalable, and cost-effective backends. In this document, we evaluated the performance, scalability, and developer experience of three popular programming languages - TypeScript, Rust, and Go - in the context of building distributed, serverless applications. While all three languages offer unique strengths and advantages, we found that Go stands out as the best choice for some backend projects.

Go's simplicity, efficiency, and ease of use make it an excellent choice for building scalable and performant serverless applications. Its support for concurrency and lightweight threads makes it easy to handle multiple requests simultaneously, while its efficient memory management and optimized code execution help to reduce costs.

• Go's support for lightweight threads can be beneficial is in the development of web servers that need to handle a large number of concurrent requests. By using goroutines, Go's lightweight threads, developers can easily handle thousands of connections simultaneously, allowing web servers to efficiently scale and handle high traffic loads without incurring additional costs. This approach can be much more efficient than using traditional operating system threads, which are heavier and more resource-intensive.
• In a serverless environment, efficient memory management and optimized code execution can help to reduce costs. Go's garbage collector automatically frees up memory that is no longer needed, while its compiled code executes quickly and efficiently, reducing the amount of compute resources needed to run the application. For example, a serverless function processing large amounts of data can run faster and more efficiently in Go, resulting in lower costs.

While TypeScript and Rust also offer many advantages for building serverless applications, Go's unique combination of simplicity and performance make it an excellent choice for specific use cases. We encourage developers to consider Go as a potential option when building performant, scalable, and cost-effective backends."

Of course, the decision to switch to using Go for some backend projects will depend on the specific requirements and constraints of each project, as well as the expertise and preferences of the development team.

Addendum

Paradigm Discussion - Functional versus Object-Oriented Programming

There will be a method to my madness, I promise. Let's start with a quick overview of functional and object-oriented programming.

Functional programming emphasizes immutability, pure functions, and higher-order functions, which can lead to code that is easier to reason about, test, and parallelize. Functional programming is also well-suited for applications that deal with large amounts of data, such as data analysis, machine learning, and scientific computing. However, functional programming can have a steeper learning curve, and some developers may find it more difficult to write and maintain functional code compared to object-oriented code. There are 3 key tenets of functional programming:

• Immutability: Immutable data cannot be changed after it is created. This makes it easier to reason about the state of a program, and it can also lead to better performance because the compiler can optimize away unnecessary copies of data.
• Pure functions: A pure function is a function that has no side effects and always returns the same output given the same input. Pure functions are easier to reason about and test, and they can be easily parallelized.
• Higher-order functions: A higher-order function is a function that takes a function as an argument or returns a function as a result. Higher-order functions can be used to abstract common patterns, which can lead to more modular and reusable code.

It's easy to see how these tenets can lead to code that is easier to reason about, test, and parallelize. For example, consider the following code:

const numbers = [1, 2, 3, 4, 5];
const doubled = numbers.map((number) => number * 2);
console.log(doubled);

This code uses the map function to double each number in the array. The map function takes a function as an argument, and it returns a new array containing the results of calling the function on each element in the original array. In this case, the function passed to map is a pure function that doubles its argument. This code is easy to reason about because it's clear that the doubled array contains the same number of elements as the numbers array, and it's also clear that the elements in the doubled array are twice as large as the elements in the numbers array.

Object-oriented programming emphasizes encapsulation, inheritance, and polymorphism, which can lead to code that is more modular, reusable, and extensible. Object-oriented programming is also well-suited for applications that deal with complex state and behavior, such as user interfaces, games, and simulations. However, object-oriented programming can lead to code that is more tightly coupled, and it can be more difficult to reason about the behavior of an object-oriented system as a whole compared to a functional system. So, the 3 key tenets of object-oriented programming are:

• Encapsulation: Encapsulation is the process of hiding the implementation details of a class from the rest of the program. This makes it easier to change the implementation of a class without breaking other parts of the program that depend on that class.
• Inheritance: Inheritance is the process of creating a new class from an existing class. The new class inherits the behavior of the existing class, and it can also add new behavior. Inheritance can be used to reduce duplication in a program by sharing behavior across multiple classes.
• Polymorphism: Polymorphism is the process of reusing the same interface for multiple types. This can lead to more modular and reusable code because a function can operate on different types of data as long as they all implement the same interface.

For example, consider the following code:

class Animal {
  constructor(name) {
    this.name = name;
  }

  speak() {
    console.log(`${this.name} makes a noise.`);
  }
}

This code defines an Animal class that has a name property and a speak method. The speak method prints a message to the console, but it doesn't actually say what noise the animal makes. This code is easy to reason about because it's clear that all animals have a name property and a speak method, and it's also clear that the speak method doesn't actually say what noise the animal makes. Now, let's create a Dog class that inherits from the Animal class:

class Dog extends Animal {
  speak() {
    console.log(`${this.name} barks.`);
  }
}

This code defines a Dog class that inherits from the Animal class. The Dog class overrides the speak method so that it prints a message to the console that says what noise a dog makes. This code is also easy to reason about because it's clear that all dogs have a name property and a speak method, and it's also clear that the speak method prints a message to the console that says what noise a dog makes.

Why do I bring this up in the context of TypeScript, Rust, and Go? Some functional programming concepts are better suited for writing highly concurrent and distributed systems, which are common in many modern backends. While TypeScript, Rust, and Go are not strictly functional languages, they do offer some functional programming features and can be used to build highly concurrent and distributed systems. These languages are well-suited to building backend systems that require high availability and fault tolerance. OOP concepts can cause problems in highly concurrent and distributed systems because of its reliance on mutable state and shared data. In a concurrent system, multiple threads or processes may need to access and modify the same data simultaneously, which can lead to race conditions, deadlocks, and other types of synchronization issues. This is not to say that OOP is inherently bad or unsuitable, but focusing on immutability and pure functions will mitigate the aforementioned issues.

TypeScript provides many features that make it easier to write large-scale applications, including classes, interfaces, and modules. TypeScript also support functional programming concepts like lambdas and higher-order functions. Additionally, TypeScript is often used with Node.js to build server-side applications, which can be highly concurrent and distributed.

Rust provides many features that make it easier to write highly concurrent and distributed systems, including lightweight threads and an ownership model that ensures memory safety and eliminates data races. Rust also supports functional programming concepts like closures and iterators, which can make code more concise and easier to reason about.

Go is purposefully designed to make it easy to write highly concurrent and distributed systems. Go provides lightweight threads, called goroutines, and a simple syntax that makes it easy to write concurrent code. Go also includes features like channels, which can be used to communicate between goroutines, and a garbage collector, which can simplify memory management. While Go is not a functional language, it does support some functional programming concepts, like first-class functions and closures.

Languages such as C#, Java, and Python were not considered for this distributed application discussion because, while they are also widely used for building backend systems, they may not be as well-suited for highly concurrent and distributed systems as TypeScript, Rust, and Go. C# and Java are primarily object-oriented languages, although they do offer some support for functional programming concepts. Python, on the other hand, is a general-purpose language that is often used for data science and web development, but it is not specifically designed for building highly concurrent and distributed systems.

In distributed, serverless applications, where the system may be composed of multiple processes or functions running on different machines, the potential for concurrency issues is even greater. This is because each process or function may be running independently and concurrently, with the potential for shared data or resources. In this context, functional programming can be particularly useful for reducing the complexity of concurrent and distributed systems, by emphasizing immutability and pure functions that avoid shared state and side effects.

Also, C#, Java, and Python are not specifically designed for building serverless applications, although they can still be used for this purpose. Serverless applications typically require a different architectural approach, with a focus on event-driven and stateless computing. Languages like TypeScript, Rust, and Go are well-suited for building serverless applications because they provide support for concurrency, fault tolerance, and memory safety, which are important considerations for serverless computing. Additionally, these languages provide efficient runtime performance, which is critical for serverless applications that are often charged based on resource consumption.

However, usage of a C# framework like ASP .NET Core or a Java framework like OfficeFloor are more than capable in the right hands. The key is to understand the tradeoffs of each language and framework, and to choose the right tool for the job.

Other languages not considered - Ruby and Elixir

While Ruby and Elixir are both powerful languages that are well-suited for building highly concurrent and distributed systems, they do have some potential drawbacks.

One potential disadvantage of Ruby is its runtime performance. Ruby is an interpreted language, which can make it slower than compiled languages like C++ or Rust. Additionally, Ruby's garbage collector can sometimes cause performance issues, especially in large-scale systems. While Ruby has a large ecosystem of libraries and frameworks, it may not have the same level of support for building highly concurrent and distributed systems as other languages like Elixir. A very timely article titled "Whatever Happened to Ruby?" was published when I started writing this document, and it provides a good overview of the current state of Ruby.

Elixir, on the other hand, is a relatively new language, and it may not have the same level of community support as more established languages. Additionally, while Elixir provides excellent support for concurrency, it may not be as well-suited for building systems that require a lot of mutable state. Finally, while Elixir runs on the Erlang virtual machine, which provides excellent support for fault tolerance and distributed computing, it may not have the same level of support for low-level systems programming as other languages like Rust. Elixir has a different syntax and programming paradigm than many other popular languages, which can make it challenging for developers who are not familiar with functional programming to learn. Still, if you want to learn more about the pros and cons of Elixir, I recommend reading this article titled "The Pros & Cons of Elixir Programming Language".