Microservices was once positioned as a strategy to increase responsiveness to changing market demands. Today, microservices have become a mainstay for modern applications and an imperative for all those who want to augment competitiveness in a complex marketplace.
The pace of technological innovation is only becoming faster, and the enterprise is moving towards lean IT. Therefore, modernization of monolithic applications and of IT becomes essential to move ahead of competitors and scale the business easily.
Microservices breaks down the traditional monolithic approach to software development and IT into smaller and more manageable components. A generic definition of Microservices is that of creating a software architecture where the applications are composed of small and independent components and processes that communicate seamlessly using language-agnostic APIs. Microservices are highly decoupled and take a modular approach to system-building.
While Microservices is all this, it is also an architectural approach that draws on long, evolving experience in software engineering and system design gleaned from developments in this space over the past two decades. A Microservices architecture leverages a spectrum of tool categories but is primarily an architectural approach to system design. Microservices is often used as a blanket term that applies to the breaking down of applications and IT systems into smaller, more granular elements.
Microservices are developed using modern, stateless back-end architecture. However, doing this does not mean that all microservices are automatically scalable. Architects have to take special care and the centralized services and databases are also designed such that they can scale easily.
The scaling conundrum
While the versatility of microservices is one of its strongest characteristics, it can come at a price. Microservices employ individual components that can be run on different platforms, a microservices solution can have multiple virtualizations and servers working harmoniously together. Since this approach is drastically different from legacy IT solutions, it needs a different approach to scalability.
Handling an increase in demand in a monolithic application is done by allocating more resources to the application when running it from a single server. The load must be spread out evenly by leveraging new instances if there are more than usual individual users on the application.
Microservices, on the other hand, demand that upscaling accounts for the handling of the different components at work. This means that either all components scale up at the same time or individual components have to be identified for scaling. With microservices, it also becomes essential to ensure that these upscaled components easily integrate with the rest of the system.
Defining the growth scale
When building a microservices architecture understanding and determining ‘how’ a microservices scales is essential to maintain and ensure scalability. Identifying the qualitative growth scale helps in assessing where the service fits into the overall ecosystem and which key high-level business metrics it impacts.
It is also important to assess the quantitative growth scale. This scale provides a quantitative, measurable, and well-defined understanding of how much traffic a microservice can handle and is essential for traffic and capacity planning.
Building this understanding helps in allocating the right software and hardware resources across the microservice ecosystem to enable high-level resource abstraction. Enabling a high level of resource abstraction enables dynamic resource allocation and eliminates all the pitfalls that impede scalability and performance
Building resource awareness
Identifying the resource requirements of each microservice and the resource bottlenecks are important for enabling scalability. These involve identifying specific resource requirements such as CPU, RAM, etc., and all components of each microservice that the microservice needs to run properly, process tasks easily, and scale vertically or horizontally.
Apart from CPU and RAM, assessing requirements like database connections, application platform resources like logging quotas also becomes important to improve scalability and performance.
It is equally essential to identify the performance and scalability limitations of each microservice that is dependent on the features of its resources. Anything that inhibits the scalability of an application is considered a resource bottleneck.
Apart from this, capacity planning and dependency scaling is required to ensure that the microservices can scale easily, especially since each microservice is a small part of a large, intertwined, and intricate dependency chain.
Choosing the right programming language
Choosing the right programming language can contribute immensely towards scalability in microservices. While one of the attractions of microservices is the ability to write it in any language, this comes with a caveat – for microservices scalability success, it is essential to take the constraints of the programming language as well.
The choice of programming language, thus, should be determined based on the performance and scalability limitations of the language. The programming language must be optimized for scalability and performance as such, those languages that do not have performance and scalable frameworks do not work out well to drive scalability and performance in microservices.
Languages that can efficiently handle concurrent and partitioned task handling and processing are better suited than others for microservices. It is also important to ensure that the language itself does not introduce scalability constraints on the microservices. For instance, many times, using a language that offers an asynchronous framework like C++ is better to optimize for concurrency and partitioning than Python.
Apart from these aspects, making the right database choices and efficiently building, running, and maintaining the databases in large microservices ecosystems also become important for scalability.
Microservices can be easily combined into a wide array of combinations to tackle a variety of problems. However, this very aspect sometimes makes it complex to scale microservices. This is not to say microservices are not scalable. In fact, they are infinitely more scalable than the earlier monolithic architectures and legacy applications. To bring about scalability, microservices need to be designed as such.
This article was originally published ET CIO