Desmond  Gerber

Desmond Gerber

1626439200

Golang, Microservices and Twirp

In this blog post I want to talk about APIs, and how to design your API when working with microservices.

Prerequisites:

1. Golang —  https://golang.org/doc/install

2. Protobuf compiler — https://grpc.io/docs/protoc-installation/

The project’s source code can be found  here

Breaking the Monolith

Until fairly recently, the go-to approach to building applications was creating a single-tiered and indivisible unit that handles multiple related tasks. This is the Monolith pattern.

This pattern was by far the most common back then, it still works well in many cases and is still widely used in the industry today.

However, this approach has some drawbacks:

1. Your code base becomes huge

2. You violate the  SRP principle — a component should do one thing and do it well.

3. Components are tightly coupled.

4. Monoliths don’t scale well both in development and product operation — everything is run and developed on the same piece.

5. High risk of bugs, data leakage and security breaches — have a security breach? well, your entire app is affected.

These days, the market forces you to move fast, break things, change directions, scale and be available all the time at all cost.

In hopes of meeting these requirements, the software industry started adopting a new approach— Microservices.

Microservices allow you to have a highly maintainable and testable software, that is loosely coupled and deployed independently.

Small teams can own a microservice or several microservices and develop at their own pace, with the language and frameworks of their choice.

To me, the answer to the Monolith vs Microservices debate is that it depends. I am not going to cover this question in this scope, but each has it’s own pros and cons.

The use case

A company has a SaaS product and exposes a REST API to users.

The product has grown and the monolith they have used up to this point no longer serves their goals:

  • Delivering new features is now taking too long.

  • There is need a different language for some component(s) to perform better.

  • Another component needs to scale but it’s a bit tiny and you don’t want to scale the entire application.

There can be quite a lot of reasons.

So they decide to break the monolith into 5 microservices and a queue.

#twirp #golang #api #microservices

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Golang, Microservices and Twirp
Desmond  Gerber

Desmond Gerber

1626439200

Golang, Microservices and Twirp

In this blog post I want to talk about APIs, and how to design your API when working with microservices.

Prerequisites:

1. Golang —  https://golang.org/doc/install

2. Protobuf compiler — https://grpc.io/docs/protoc-installation/

The project’s source code can be found  here

Breaking the Monolith

Until fairly recently, the go-to approach to building applications was creating a single-tiered and indivisible unit that handles multiple related tasks. This is the Monolith pattern.

This pattern was by far the most common back then, it still works well in many cases and is still widely used in the industry today.

However, this approach has some drawbacks:

1. Your code base becomes huge

2. You violate the  SRP principle — a component should do one thing and do it well.

3. Components are tightly coupled.

4. Monoliths don’t scale well both in development and product operation — everything is run and developed on the same piece.

5. High risk of bugs, data leakage and security breaches — have a security breach? well, your entire app is affected.

These days, the market forces you to move fast, break things, change directions, scale and be available all the time at all cost.

In hopes of meeting these requirements, the software industry started adopting a new approach— Microservices.

Microservices allow you to have a highly maintainable and testable software, that is loosely coupled and deployed independently.

Small teams can own a microservice or several microservices and develop at their own pace, with the language and frameworks of their choice.

To me, the answer to the Monolith vs Microservices debate is that it depends. I am not going to cover this question in this scope, but each has it’s own pros and cons.

The use case

A company has a SaaS product and exposes a REST API to users.

The product has grown and the monolith they have used up to this point no longer serves their goals:

  • Delivering new features is now taking too long.

  • There is need a different language for some component(s) to perform better.

  • Another component needs to scale but it’s a bit tiny and you don’t want to scale the entire application.

There can be quite a lot of reasons.

So they decide to break the monolith into 5 microservices and a queue.

#twirp #golang #api #microservices

Einar  Hintz

Einar Hintz

1599055326

Testing Microservices Applications

The shift towards microservices and modular applications makes testing more important and more challenging at the same time. You have to make sure that the microservices running in containers perform well and as intended, but you can no longer rely on conventional testing strategies to get the job done.

This is where new testing approaches are needed. Testing your microservices applications require the right approach, a suitable set of tools, and immense attention to details. This article will guide you through the process of testing your microservices and talk about the challenges you will have to overcome along the way. Let’s get started, shall we?

A Brave New World

Traditionally, testing a monolith application meant configuring a test environment and setting up all of the application components in a way that matched the production environment. It took time to set up the testing environment, and there were a lot of complexities around the process.

Testing also requires the application to run in full. It is not possible to test monolith apps on a per-component basis, mainly because there is usually a base code that ties everything together, and the app is designed to run as a complete app to work properly.

Microservices running in containers offer one particular advantage: universal compatibility. You don’t have to match the testing environment with the deployment architecture exactly, and you can get away with testing individual components rather than the full app in some situations.

Of course, you will have to embrace the new cloud-native approach across the pipeline. Rather than creating critical dependencies between microservices, you need to treat each one as a semi-independent module.

The only monolith or centralized portion of the application is the database, but this too is an easy challenge to overcome. As long as you have a persistent database running on your test environment, you can perform tests at any time.

Keep in mind that there are additional things to focus on when testing microservices.

  • Microservices rely on network communications to talk to each other, so network reliability and requirements must be part of the testing.
  • Automation and infrastructure elements are now added as codes, and you have to make sure that they also run properly when microservices are pushed through the pipeline
  • While containerization is universal, you still have to pay attention to specific dependencies and create a testing strategy that allows for those dependencies to be included

Test containers are the method of choice for many developers. Unlike monolith apps, which lets you use stubs and mocks for testing, microservices need to be tested in test containers. Many CI/CD pipelines actually integrate production microservices as part of the testing process.

Contract Testing as an Approach

As mentioned before, there are many ways to test microservices effectively, but the one approach that developers now use reliably is contract testing. Loosely coupled microservices can be tested in an effective and efficient way using contract testing, mainly because this testing approach focuses on contracts; in other words, it focuses on how components or microservices communicate with each other.

Syntax and semantics construct how components communicate with each other. By defining syntax and semantics in a standardized way and testing microservices based on their ability to generate the right message formats and meet behavioral expectations, you can rest assured knowing that the microservices will behave as intended when deployed.

#testing #software testing #test automation #microservice architecture #microservice #test #software test automation #microservice best practices #microservice deployment #microservice components

Norbert  Ernser

Norbert Ernser

1595316660

Introducing Hippo: A Golang Microservices Toolkit

It all began when I started to build some web services in golang. and everytime I have to create the whole architecture from scratch than solving whatever problem I was trying to solve.

So why don’t we use one of the available frameworks?

Go is different compared to many other programming languages. It is built for the modern web and it has a built-in standard libraries to accomplish most web programming tasks.

To make this argument clear, let’s have a look at HTTP handler for vanilla Golang, Python (Flask), PHP (Laravel) and Java (Spark)

func handler(w http.ResponseWriter, r *http.Request) {
     fmt.Fprint(w, "Hello world!")
}
import static spark.Spark.*;

public class HelloWorld {
    public static void main(String[] args) {
        get("/hello", (req, res) -> "Hello World");
    }
}
@app.route('/'):
def handler():
    return "Hello world!"
use Illuminate\Http\Request;

Route::get('/', function (Request $request) {
    //
});

Also comparing HTTP request on Golang vs PHP

// Get cURL resource
$curl = curl_init();
curl_setopt_array($curl, [
    CURLOPT_RETURNTRANSFER => 1,
    CURLOPT_URL => 'http://clivern.com',
    CURLOPT_POST => 1,
    CURLOPT_POSTFIELDS => [
        item1 => 'value',
        item2 => 'value2'
    ]
]);
// Send the request & save response to $resp
$resp = curl_exec($curl);
// Close request to clear up some resources
curl_close($curl);
import (
    "http"
)

response, _, err := http.Get("http://clivern.com/")

#golang #microservices #scaling #microservices

Tia  Gottlieb

Tia Gottlieb

1597438200

What Is a Microservice Architecture? Why Is It Important Now?

We have been building software applications for many years using various tools, technologies, architectural patterns and best practices. It is evident that many software applications become large complex monolith over a period for various reasons. A monolith software application is like a large ball of spaghetti with criss-cross dependencies among its constituent modules. It becomes more complex to develop, deploy and maintain monoliths, constraining the agility and competitive advantages of development teams. Also, let us not undermine the challenge of clearing any sort of technical debt monoliths accumulate, as changing part of monolith code may have cascading impact of destabilizing a working software in production.

Over the years, architectural patterns such as Service Oriented Architecture (SOA) and Microservices have emerged as alternatives to Monoliths.

SOA was arguably the first architectural pattern aimed at solving the typical monolith issues by breaking down a large complex software application to sub-systems or “services”. All these services communicate over a common enterprise service bus (ESB). However, these sub-systems or services are actually mid-sized monoliths, as they share the same database. Also, more and more service-aware logic gets added to ESB and it becomes the single point of failure.

Microservice as an architectural pattern has gathered steam due to large scale adoption by companies like Amazon, Netflix, SoundCloud, Spotify etc. It breaks downs a large software application to a number of loosely coupled microservices. Each microservice is responsible for doing specific discrete tasks, can have its own database and can communicate with other microservices through Application Programming Interfaces (APIs) to solve a large complex business problem. Each microservice can be developed, deployed and maintained independently as long as it operates without breaching a well-defined set of APIs called contract to communicate with other microservices.

#microservice architecture #microservice #scaling #thought leadership #microservices build #microservice

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