Top 5 Technologies that Optimize Microservices Architecture Development

We have been building software solutions for many years using various tools, technologies, and architectural patterns. Many software applications tend to become massive complex monoliths over time. A monolith app is like a large ball of spaghetti with criss-cross dependencies among its constituent modules. With the system’s growth, the code gets more complicated, the architecture more complex, and the app’s maintenance becomes extremely difficult, requiring more developers to support it.

Over the years, an architectural pattern known as Microservices has emerged as an alternative to Monolith one.

Microservices are the number-one trending topic in software engineering at the moment. However, many IT decision-makers are still in the dark as to what they are & why they should consider this architectural pattern.

Microservices are an architectural method in software engineering that promotes application development as a collection of autonomous, smaller programs. Each program is in command of a single feature and communicates with other programs through APIs to solve a complex business problem. For instance, one modular service takes care of authentication, another – a database, the other – blog posts, etc. 

The aim is to facilitate the deployment process and develop high-end, cloud-ready software programs fast. By decomposing the application into multiple smaller components, you make them easier to scale, modify, and deploy.

The adoption of microservice infrastructure grows every single day. From tech giants and large enterprises to small businesses, many companies choose microservices over monolith.  

Here are impressing statistics from the O’Reilly survey 2020:

• 61% of businesses have been exploiting microservices-based software around a year or more
• 28% have been utilizing for around three years
• 29% of businesses are migrating to or implementing microservices 

So why are these architectural patterns becoming the preferred choice for plenty of organizations and dev teams?

Multiple smaller components that operate together as a single application can be easily deployed, modified if necessary, and redeployed separately without affecting the rest of the software’s codebase. 

In other words, you can effortlessly implement new features in an app modifying one particular component instead of having to redeploy the entire application.

Since each microservice is independent, it doesn’t rely on tech-related bindings. Developers can build microservice on virtually any coding language, using the tech stack based on their specific skills. Plus, this grants you the freedom to experiment by combining several technologies or incorporate new ones.

Since each microservice is independent, it doesn’t rely on tech-related bindings. Developers can build microservice on virtually any coding language, using the tech stack based on their specific skills. Plus, this grants you the freedom to experiment by combining several technologies or incorporate new ones.

Technical limitations decide the whole architecture of a traditional monolithic development approach. Specifically, you would have teams organized around their technical expertise: a team designing the user interface, another team working on databases, and the other responsible for the server-side logic.  

As opposed to the monolith method, the microservices style is often arranged around business capabilities. This architecture allows developers to stop using traditional software layers and encourages building the overall landscape of the microservice system based on business functionalities. Hence, the teams are formed in accordance with their expertise in a particular business function. Each dev team owns the full life-cycle of its service, from development and deployment through production support to collecting customer feedback. 

A microservices architecture doesn’t dictate container usage, but most developers will find this approach more compatible to implement apps. Containers occupy less space, are quicker to load & far better from an efficiency perspective than standard virtual machines (VMs) environments. 

So you are more likely than not will need the right container technology. 

Out of all container software available in the market, Docker & Kubernetes platforms have proven to be powerful tools for the speedy creation of developer environments. These frameworks are aimed at orchestrating multiple containers in enterprise environments and optimizing the deployment process. 

Docker is a containerization tech for building, testing, and running software systems as self-contained packages in a loosely isolated environment – container. Kubernetes is a system designed for the automation of the manual work involved in deploying and managing containerized apps that helps with container scaling & scheduling, and more.

Using these techs in duo will help you create a flexible foundation for microservices infrastructure, effortlessly scaling up or down as per your requirements.

Benefits: Docker containers are lightweight and involve everything needed to develop, test, run applications, saving hours in patching and downtime as opposed to VMs. It provides facilities for continuous integration and deployment fitting DevOps culture. Moreover, it supports various operating systems, integration with popular tools & services, and multiple available plugins that enhance its features.

It’s critically vital to monitor the state of a developed application from time to time, especially in a distributed topology like microservices. Most conventional monitoring instruments are meant for static app environments. Although some of them were remodeled to meet microservices demands, they fail to support multiple complex environments. 

A fantastic solution to this issue brings a Prometheus platform. It’s a full-service monitoring system & alerting tool designed for dynamic distributed app topologies comprising a considerable number of nodes. 

Prometheus implements multidimensional data by using key-value labels and offers data store & scrapers. It’s fast and easy to filter data based upon their labels. 

The tool offers stellar visualization features for alerts and statistics. It allows gathering & visualizing data and enables time-based tracking options to discover anomalous patterns effectively. This monitoring system provides a convenient dashboard interface and a host of useful graphing instruments. 

Benefits: Support for multidimensional data collection and a rapid tagged query language are exceptional Redis’ strengths. Its tight integration with Kubernetes, availability of numerous exporters and libraries are in favor of Prometheus. Since its server has its standalone unit that doesn’t rely on network storage, there is no need for additional infrastructure or software.

Most microservices rely on APIs, a communication tool between and within the autonomous services. They simplify software development a lot by saving a significant amount of resources. 

API performance testing is crucial to the project development life-cycle. A well-arranged process supported by an effective method and the correct API automation instruments is of great importance.  

Postman is what one needs to conduct comprehensive API tests. A well-designed GUI allows interacting with APIs effortlessly, build requests and see responses. 

It’s also a great automation tool. Postman dramatically reduces testing time and advances the quality of the product. It helps detect bugs earlier in the development process, often even before the UI has been created.  

This is an excellent instrument for streamlining API management & testing. Our team runs all APIs through Postman to identify critical bugs on time and avoid serious issues in later stages. Postman has a free version that can be downloaded immediately and paid versions for teams.

Benefits: Postman can be smoothly integrated into the project development life-cycle. It facilitates the design and maintenance of numerous API versions. Postman has a fantastic IDE-like GUI that simplifies the exploration and navigation of RESTful API. It offers automated along with exploratory testing, various integration options including, support for external editors.

Each component takes responsibility for its own data model. Ideally, the service data must be isolated from other data layers to ensure uncoupled scaling. 

This is where Redis comes in hand. It may not be a blanket solution, but Redis, alongside its high availability and automatic partitioning functionality, suits well most of the demands. Additionally, it supports the master-replica option, data persistence, and outperforms relational databases several-fold.

Redis is a versatile technology offering a wide variety of features that make it powerful for a broad spectrum of use cases.

First and foremost, Redis is an indisputably superb, high-speed NoSQL database that supports fast responses and elastic data structures designed to solve complex coding problems using simple commands. Besides a core data model, which is a key-value, Redis also supports Hashes, Streams, and other kinds of values. Given that microservices are focused on one business function, the state they store is intrinsically non-relational and perfectly matched to NoSQL.

Redis is a high-performing platform with the capability to handle up to millions of operations a second & a read operations speed of a millisecond.  

Another Redis’s forte is its distributed caching engine. Safe temporary data storage, data persistence, and smooth data sharing between microservices all these needs and much more Redis have covered. Its caching mechanism reduces data access latency and relives the load off the app & database. 

Benefits: Redis helps optimize the data layer, anything from inter-service communication through data management to synchronization across geographies. It allows the user to access a scalable data store offering multiple processes, applications, and servers. This platform helps to decrease the client workload and significantly speeds up the app performance as a cache manager. The greatest thing about Redis is its multipurpose usage for various data manipulations.

Autonomous services interact with each other, either synchronously or asynchronously, using the messaging queues. 

We’ve already mentioned that Redis can operate as a message broker as well. Since all the data resides in memory, it’s incredibly fast and also scalable. Redis doesn’t have persistency as such instead it drops its memory into a DB or disk. The possibility to write the data onto the disk every two seconds is useful for having a backup in case of an outage. Furthermore, Redis’s Pub/Sub support enables establishing high-performance server intercommunication.   

Benefit: Redis is an exceptionally easy-to-deploy message broker tech with a friendly UI that offers basic features for queue messaging, speedy service, and a host of sound capabilities. Perfect for a simple message queue implementation, Redis doubles up as a key-value store. 

RabbitMQ is a reliable message technology that supports both message queueing and pub/sub messaging patterns as well as several standardized protocols. It’s doing well at clustering and is deemed to be the most robust message broker among most developers. 

You can configure RabbitMQ to use SSL, thus creating an extra security layer. It provides more multifaceted functionality for queue messaging when compared to other message brokers and particularly Redis. What’s more, it’s exceptional at clustering and scales up to half a million messages per second.  

Benefit: If you work on a complex microservice-based application with huge messages that require scalability, RabbitMQ will help with complex routing communication. It’s beneficial for long-term tasks when you require to run reliable background jobs. RabbitMQ provides a host of features such as publisher confirms & persistence to let you trade off performance with reliability.

When speaking of the best coding languages, there is no clear answer as none was built specifically for microservices, except for several frameworks. The system doesn’t care about the language it’s written in as long as the service performs the tasks and does it in a reasonable time. Nevertheless, some languages possess better options for the patterns required for microservice implementation.  

According to a survey 2020, JavaScript and Typescript coding languages are the most widely used technologies among the vast majority of surveyed microservice developers. Next come Java and .NET taking second and third place correspondingly, then go Python, PHP, Go, and Ruby. 

Note that no tool or language gives an answer to the phenomenon that is microservices. The bigger discussion is rather the quality of implementation and glue between the services, i.e. interservice communication and dev ops culture. You can’t go wrong if you stick to the three pillars of microservice architecture, taking into account such pre-requisites as IT operating model, infrastructure, and developer skillsets.

If you’re willing to go with microservices but not sure if it’s the right solution for your business, we would be pleased to assist you. Our microservices development experts deliver reliable, easily maintainable tech solutions. Contact us, and our team will help you build custom software that aligns with your business needs.