Microservices have recently gained in popularity, but you may be unsure whether this architecture is right for your environment. What’s great is microservices are not necessarily a new beast, as the concepts behind them have been a solid part of software development for decades. Topics such as modular programming, separation of concerns and service-oriented architecture (SOA) all align with the objectives of a microservices architecture. In fact, many development teams have adopted microservices without necessarily calling them that—event-driven architectures are one example.
Before discussing the advantages of microservices, let’s make sure we’re aligned on a definition and the key principles:
- Microservices are a set of software applications that work together, each designed with a limited functional scope.
- They work with each other to form a larger solution.
- Each microservice has minimal capabilities for the sake of creating a highly modularized overall architecture.
Does this sound like an architecture your development team has been utilizing? If not, there are several advantages for use within the enterprise, especially as businesses build more complex solutions for customers.
Easier to Build, Easier to Enhance
Microservices are “micro,” requiring much less code than their monolithic application counterparts. The sum of code may compare to a monolithic application, but it’s the physical separation of code that draws cleaner, distinct lines between different functions for microservices. They also excel in experimentation and testing because the focus is on one small feature or capability, making incremental code updates simpler. As a result, companies increase agility, bringing higher-quality systems that have less complex code, require lower testing effort, support easier unit testing and reduce problem risk.
Microservices also free users from concerns of how one task will affect the next. When coupled with a messaging system such as Apache Kafka, they can actually simplify the development process. Each microservice can write to the messaging system in a standardized format the next can understand—no strict messaging format required. By opening the architecture to a system of smaller applications you can also base each microservice on almost any programming language. This grants you freedom in a few ways because:
- A variety of development teams can work together on a single microservice architecture without commonality on technologies.
- Each team can use a software stack they choose for their specific skills.
- You can incrementally incorporate or experiment with new technologies.
Gone are the days of worrying about updates impacting your system or waiting to update all your microservices at once, too. As long as you adhere to the simple input and output messaging formats, you can update a single microservice at your leisure without having to shut down the entire system.
Deploy With No Hesitation
Microservices are easier to deploy than monolithic applications for the same reason they’re easier to build and enhance: they’re small and modular. Consider the various dependencies between development and production environments like OS or the amount of random-access memory (RAM) and you begin to understand how complex deployment within a tech stack can be.
By reducing dependencies to a smaller scope, thus decreasing the potential for dependency conflicts, microservices become advantageous for deploying in a container with other virtualized technologies. Further, there are no limits to a single deployment option. Whether on-premises, in the cloud, in serverless environments or at the edge—which will continue to gain in significance and popularity—the possibilities are nearly endless.
Maintain, Troubleshoot and Extend With Ease
Maintenance is key to making our most valuable investments last. This is especially true for large-scale software environments where monolithic architectures can prove challenging. Microservices offer a way to seamlessly enable ongoing maintenance and fault tolerance, as well as troubleshooting, as individual outputs make isolating the source of problems easier.
Moreover, single points of failure are not an issue because the distributed nature of microservices means any given one can be deployed redundantly, in parallel, and on a continuous basis. If any single microservice for a given task fails, the others associated will pick up the slack.
Another benefit is they help extend your systems to provide more outputs. Making incremental updates is relatively low-risk because microservices are highly modular and can be plugged in easily with new or updated code. Should an unforeseen error occur, you needn’t fret about shutting down the entire system and stopping the flow of data. Instead, you can shut down a given task and temporarily stop data flow, with the messages queued in the messaging layer to be read once it is restored.
Simplify Cross-Team Coordination
Many companies overcomplicate large projects and software development is no different, with integration points serving as cumbersome, headache moments. In a microservice, internal workflows are as straightforward as:
- Reading data from a source.
- Performing an action on the data.
- Sending output to a destination.
Since microservices are designed to navigate small bits of data at a time from an otherwise large data set, managing and sharing output is straightforward. Teams simply coordinate what their respective microservices do and how the exchanged messages are formatted. Lightweight messaging systems are recommended for allowing communication, as they further support simplifying coordination across development teams by providing a fast and reliable means for exchanging data.
Speed and Scalability
It may seem with the many independent, moving parts in a microservices architecture that performance will take a severe hit, whereas a monolith runs as a single process. However, keep in mind there is a clearer opportunity for parallelism with microservices, so any task can be spread across multiple CPUs/cores and be run with much higher overall throughput. For example, machine learning models that require complex calculations in addition to lookups in external databases can be parallelized to process more data at once.
The scalability of microservices is tied in with this capability. As the workload grows with more and faster data, additional microservices can be deployed to run in mirror to spread the load across further hardware resources. In contrast, refactoring a monolithic application to handle more load—which will require significant changes—potentially creates greater risk for introducing errors.
Streamline Real-Time Processing
Demands for immediacy are only continuing to grow. As a result, businesses must increase performance and function in real-time to stay ahead. Microservices provide that competitive advantage by enabling efficient, instantaneous processing and streaming architectures.
Real-time processing is centered on fast data, often in the form of streaming. As data continues to flow in from a source such as an internet of things (IoT) device, applications must keep up with the input rate and operate reliably. A microservices architecture provides the parallelism and redundancy to maintain the load and respond quickly in a consistently reliable way. Additionally, as the flow increases, more microservices can be deployed to accommodate the growth. This structure also allows easy identification of bottlenecks that can be addressed to maintain immediate responsiveness.
The swath of consumer data available to enterprise business today is at a scale never seen before. Thinking strategically about how to handle and process it for the benefit of the business—and the consumer—is an important priority today. Microservices are just one strategy to leverage on this journey and could serve as the advantageous choice for increasing performance, speed and ease on the workloads of many.
