Migrating to Cloud Native: How To Move Apps With Microservices

Businesses encounter the task of deploying and overseeing applications in production on a large scale. Luckily, there is a wealth of technologies and tools at our disposal. Nevertheless, shifting from a conventional, monolithic structure to a cloud-native one presents its own set of hurdles. Here, you'll discover a list of essential initial steps to undertake when moving applications from a monolithic setup to a microservices-based architecture.

Logical Steps for a Seamless Transition

Compared to traditional big applications, microservices are like small independent units that handle specific tasks and collaborate to make an application work. While using these distributed components offers many benefits, it also brings its own set of challenges.

Maintaining software quality during the shift from a traditional system can be tough. Often, it holds teams back from even starting the transition. But with some planning and preparation, it can be done. The process can be broken down into several steps. Let's walk through them together.

Step 1: Define Boundaries

The initial phase involves delineating the boundaries and capabilities of your application, a crucial step in uncovering the level of coupling within your monolithic structure. Coupling, which poses the primary challenge, is often referred to disparagingly as 'spaghetti code' in the context of monolithic applications. This term stems from the tendency of codebases to accumulate increasing levels of coupling with size and age.

Decoupling tightly interconnected elements proves challenging during the transition, and while codebase age and size are potential indicators of coupling issues, they aren't definitive. A monolithic application isn't inherently tightly coupled; it depends on coding practices. Viewing coupling as the adversary, we emphasize that well-established coding practices, balancing cohesion and coupling during monolith creation, contribute to smoother transitions.

Effective transitions hinge on proper boundary definitions within the monolith, where microservices serve as single units with specific capabilities. Applying similar boundary principles within a monolithic application facilitates a more manageable transition.

Step 2: Identify Coupling

While the initial step focuses on delineating the system's capabilities, the second step establishes the boundaries (Bounded Context), encompassing a collection of these capabilities. For instance, in a point-of-sale application, the shopping cart might consist of an inventory boundary component on one side and an identity-bounded element on the other. The cart object serves as the means to consolidate and integrate these elements.

Step 3: Move to RPC

In the third step, our focus is on identifying and documenting the interconnections between Bounded Contexts, discerning which ones reference others, and determining the capabilities necessitating function calls across contexts. This coupling manifests in two main categories: Functions/APIs and Database Schema.

For Functions/APIs, the transition from in-process calls to a separate service involves Remote Procedure Calls (RPC) over the network, commonly executed through HTTP, gRPC, etc. While synchronous RPC serves as an intermediate step, it is not a sustainable solution for distributed systems. The ultimate goal is to replace synchronous RPC calls with an asynchronous messaging system.

Throughout this process, each boundary maintains its data autonomy. Microservices discourage the use of shared databases directly, as it introduces undesired coupling. Post-decoupling, querying one Bounded Context's schema from another is avoided.

Summing up the steps, we've essentially transformed our architecture into a distributed monolith by transitioning all in-process communication to RPC calls over the network—a significant stride towards achieving a cloud-native application.

Step 4: Define Data Ownership

In this phase, the objective is to eliminate the rigid coupling of data and the stateful storage mechanism that preserves the application's state. This shift allows a transition to a more stateless model, where the data transmitted between microservices includes only the necessary information for the task within the microservice's boundaries. For instance, rather than making frequent trips to a persistent storage area for data retrieval and updates in a shopping cart, the cart object can retain the purchaser's identity and inventory IDs for products until they are utilized at checkout.

Step 5: Implement Asynchronous Messaging

Concluding in the fifth step, there's additional effort required to achieve autonomy for your services. After isolating a Bounded Context, the process involves applying identical principles to other boundaries and capabilities until the entire transition is complete. Commands and Events are dispatched and broadcasted to a Message Broker, eliminating the need for RPC. This simplifies the intricacies associated with maintaining the access required for remote procedure calls between services, even if they operate on different hosts. The replacement of this interaction with Role-Based Access Controlled certificates marks a significant stride toward attaining service autonomy.

Choosing the Right Programming Languages for Cloud-Native Development

Now, let's explore some programming languages suitable for modern cloud-native development.

Given my experience, I'll start with some reliable options that have stood the test of time and then delve into newer languages that are gaining prominence as they are increasingly taught in educational settings.

Let's begin with languages that evolved with the growth of the Internet:

Java

Recognized as a versatile general-purpose programming language, Java has solidified its status as one of the premier choices for cloud computing, embraced by millions of developers and executed across over 15 billion terminals globally. Offering unparalleled versatility, Java stands out as one of the rare languages capable of creating applications for websites, desktops, mobile devices, and video games using a unified codebase.

Key Benefits of Java Include

1. Object-oriented: Embraces an object-oriented paradigm.
2. Dependency-free usage: Can be employed without complications from dependencies.
3. Platform independence: Truly platform-independent, compatible with various operating systems.
4. Ease of learning: Known for its relatively straightforward learning curve.
5. Universal codebase: Cloud computing programs developed in Java can seamlessly run on different operating systems, such as Windows, iOS, Blackberry, and Linux, maintaining a consistently interpreted codebase.

Java boasts built-in robust security features, making it a preferred choice for those aiming to implement serverless architecture. Leveraging ahead-of-time (AOT) compilation of diverse frameworks, Java efficiently addresses large distributive sizes and long cold start times. Major cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) offer robust support for Java in their SDKs, affirming its stronghold in cloud development.

Python

Python stands out as one of the most prominent languages in the current cloud landscape. With a learner-friendly approach, Python caters to novices, making programming accessible to nearly everyone. Boasting outstanding features like an array of third-party modules, extensive support libraries, and robust open-source and community development options, Python is a high-level, interpreted, and highly interactive object-oriented scripting language. Its well-defined hierarchical indented format contributes to easy readability, utilizing English syntax and keywords more frequently than punctuation, simplifying the learning process.

Python amalgamates advanced attributes such as speed, productivity, robust community support, and open-source development, along with a rich array of support libraries and third-party modules. Versatile in its application, Python is suitable for creating business applications, games, operating systems, computational and scientific applications, as well as graphic design and image processing applications.

Key Features and Benefits of Python Include

1. Web Frameworks and Applications
2. Scientific and Computational Applications
3. GUI-Based Desktop Applications
4. Language Development

Python finds extensive use in the AWS Cloud and enjoys native support in AWS Lambda, making it an excellent choice for developing serverless applications on Amazon Web Services.

.NET

While not my preferred language for several reasons, mainly due to its bias towards the Windows Operating System and being governed by Microsoft, ASP.NET still occupies a significant place in web programming.

Primarily employed for developing web applications and feature-rich websites, ASP.NET stands out in the realm of cloud computing due to its capability to deliver dynamic web pages and cutting-edge solutions compatible across various browsers.

Novice developers will appreciate the user-friendly nature of the ASP.NET framework, equipped with numerous built-in features, including:

1. Minimizing code usage in large application development.
2. Effective creation of dynamic web pages.
3. Language independence and ease of use.
4. Separation of logic and content to streamline application development.
5. Utilization of built-in Windows authentication for enhanced application security.

PHP

PHP, a widely used language among programmers, is primarily employed for website automation. Known for its ease of learning and manipulation, PHP is a preferred choice for creating applications with dynamic elements. As an object-oriented language, PHP is capable of developing complex and large-scale web applications.

Running on both UNIX and Windows servers, PHP boasts a powerful output buffer feature, contributing to its popularity. Its noteworthy speed, cost-effectiveness, reliability, and security make it a compelling option for exploration in cloud-native applications.

Furthermore, PHP seamlessly integrates with various popular database management systems, facilitating a straightforward connection to MySQL for tasks like database backups. Its reliability, safety, speed, and affordability position PHP as a viable language for fulfilling unique development needs in cloud computing.

Node.js

Node.js, leveraging the JavaScript V8 engine, operates seamlessly in various browsers, including Chrome, and functions as a standalone tool. It excels in handling server requests with ease, expanding JavaScript's functionality across coding languages, APIs, and external libraries. Node.js plays a crucial role in web app development, embodying the 'JavaScript everywhere' paradigm for both server-side scripting and client-side programming.

Known for its user-friendly manipulation and effectiveness in end-to-end application development, Node.js features a non-blocking, evented, asynchronous communication pattern, allowing for the efficient handling of numerous connections. Running on the Google JS engine, Node.js stands out for its exceptional speed, making it a favorite among modern developers.

Key benefits of Node.js include cross-platform compatibility, the convenience of using a single coding language (JavaScript), the power of the JavaScript V8 Engine, support for quick deployment and microservice development, high scalability, impressive data processing capabilities, an active open-source community, additional functionality through Node Package Manager (NPM), advanced hosting capabilities, and fast data streaming.

Now, let's explore some of the newer offerings that have emerged to address the evolving needs of cloud-native programming.

Now, let's explore some newer languages emerging in the cloud-native programming landscape.

Golang

• Rapidly becoming the language of choice for cloud-native operations.
• Prominent in creating Docker, Kubernetes, and other cloud-related technologies.
• Gaining popularity for its simplicity, speed, efficiency, and scalability.
• The standard library supports major cloud providers.

Ballerina

• Open-source language for the cloud, designed for network services.
• Focuses on making coding network constructs inherent in the language.
• First-class support for distributed transactions, circuit-breaker patterns, and more.
• It deploys directly onto Docker and Kubernetes and integrates with common IDEs.

Pulumi

• Infrastructure-as-code language, launched in 2018, supports Kubernetes.
• Leverages existing programming languages like TypeScript, JavaScript, Python, Go, and .NET.
• Provides a downloadable CLI, runtime, libraries, and a hosted service for efficient infrastructure management.
• Aims to address build, deploy, and manage needs for cloud applications.

Selecting the right language depends on your project's requirements and your team's expertise. Whether you opt for the well-established or the latest entrants, ensure they align with your microservices development goals in a cloud-native environment.

In conclusion, the programming language landscape for cloud-native development offers diverse options. Established choices like Java, Python, .NET, PHP, and Node.js provide versatility. Golang stands out for its simplicity and scalability, while Ballerina integrates network constructs seamlessly. Pulumi addresses infrastructure-as-code needs with language versatility. Whether opting for proven languages or embracing newer ones, align your choice with project requirements and team expertise for efficient and scalable cloud applications.