In our previous blog, we covered the scalability in microservices architecture. It is quite easier to scale microservices than in a monolithic architecture. Furthermore, it makes scaling individual services and meeting the user's expectations more reliable.
It is true that because of their excellent scalability forte, microservices are way more popular than any other architecture. This powerful architectural style works by breaking down complex applications into small, loosely coupled sets of services. Consequently, businesses greatly benefit from this modern architectural style by developing innovative web, mobile, and cloud-based applications.
Tech biggies are moving fast to take up microservice structures; this speaks about its reliability more. This brings enough reasons for every small-scale and big enterprise to adopt microservice product architecture and implement cost-effective strategies for performance optimization.
But how to do this?
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Here's a detailed step-by-step guide on how to attain system scalability in microservice architecture—
Microservice architecture is a software development process where a system/application/product is organized in a collection of loosely coupled services. Adopting this paradigm shift serves better than standard monolithic architecture.
In microservice architecture, application components can be easily developed, deployed, and scaled according to the business demands. In this format, dividing the services into loosely coupled sets makes them all self-contained and able to perform a specific task and communicate through APIs.
Adopting microservice architecture benefits these three elements
Product scalability: Independent scaling up and down as needed
Resilience: Cross-microservice performance makes one more resilient toward failure.
Agility: Easy application migration without impacting the system
Certain factors affect scalability in microservice system architecture. Be it any system, its scalability is necessary to handle growing web traffic and user data volumes. Additionally, it is crucial to manage the computing demands without compromising the system's performance or structure.
Below are the factors that affect scalability in a microservices architecture
Performance Bottlenecks: This issue occurs wherever the performance is insufficient or lower than expected.
Resource Utilization: Inefficient resource utilization limits the system's scalability.
Network Latency: If high, it causes delays and impacts a distributed system's scalability.
Data Storage and Access: If issues occurred with data storage and accessibility, it could impact system scalability also.
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You might be thinking about the benefits of scalability in a microservices architecture, right?
Well, there are a handful of reasons regarding this; read the following points and understand for yourself!
#1 Managing Traffic Growth: Microservice scaling is needed to handle traffic as it increases upon the system.
#2 Enhanced System Performance: System scalability improves the overall system's performance and independently scales microservices.
#3 Increased Reliability: Scalability is necessary for the system to operate even when one or a couple of microservices fail. In such cases, other independent microservices operate and handle the task.
#4 Cost-effective measures: Every business wants to achieve the best system scalability without investing too much into the scalability features of microservice architecture. This is actually possible with the help of professional software product engineering services as well.
There are many cost-effective strategies for performance optimization and scaling in a microservice architecture. Here we will disclose all of them for you—
✅ Horizontal scaling: It is one of the most commonly utilized, by adding more microservices to handle the workload. It operates by adding new containers/machines and distributing the workload among multiple services.
✅ Vertical scaling: This scaling measure operates by increasing the resources of existing microservices to handle the overload. While it works well for short-term scaling, it has limitations when it comes to long-term business results.
✅ Performance monitoring: To ensure effective scaling of microservices, it's important to monitor their performance regularly. It's best to hire software product engineers to perform this task for you in its full-fledged form. You can also get enhanced system development benefits associated with deploying and post-live product maintenance.
✅ Microservices management platform: Having a dedicated platform to manage all activities related to microservice architecture is necessary for its better scaling.
✅ Microservice structurization: It's important to put scalability in your mind when designing the system architecture. By adopting microservice formation, businesses can attain effective scaling.
First and foremost, it's necessary to identify top business goals and objectives. Thoroughly know and understand your business requirements well. Knowing what your system aims to achieve puts forth the need to determine its key features and core functionalities.
To start off with ensuring scalability in a microservices architecture, you may conduct a couple of stakeholder meetings and outline functional/non-functional system requirements based on your knowledge base.
Although we are talking specifically about microservice architecture, it's vital to know the type of structure needed for your business. Primarily, there are three patterns—
Common System Architecture Patterns
Monolithic Architecture: Comes with limited scalability needs, more suitable for systems based on simple architecture.
Microservices Architecture: It's ideal for enterprise-level and complex systems and comes with promising scalability and a wide range of flexible and independent services.
Serverless Architecture: Works best for systems requiring rapid deployment.
Just setting up architecture isn't going to help you out!
You must also select the right technology stack to develop the whole system cycle. Make sure you're working on the right frontend and backend technologies, frameworks, and languages; also, don't forget the databases and DevOps tools for CI/CD and containerization.
To create an innovative and high-level design, you must outline and include all major components of the overall system architecture. Start by defining the data flow and mapping out its system-flowing process. You may also identify and align data sources and their steps of processing.
Figure out data storage solutions and it's security and implement major security considerations based on authentication and encryption. Together, these steps will help in developing the most cost-effective strategies for performance optimization of your system.
The next step is to develop a basic system prototype via effortless programming and codes. You may hire software product engineers and a whole dedicated team to help you out in this case. The team will develop the whole system prototype and validate the design and technology choices as per business demands and preferences.
Once the prototype is fully developed, you may preview it to the best stakeholders and gather their feedback to make the necessary adjustments.
Product testing is critical before its deployment to ensure that it meets the actual user demands and adheres to the market performance standards. You can build a Proof of Concept (PoC) to test the critical components related to scalability in a microservices architecture. You must use PoC excellently to refine the system architecture.
Now after you've got the basic homework ready, it's time to shower your talents over the exams!
Start with setting up the development environment and configure it via the chosen technology stack and tools. Follow agile methodologies and establish a version control with robust systems like Git. For an even more enhanced modular development, you must conduct a regular sprint plan and a microservice architecture style of development.
The bottom line is, you must ensure every module is fully developed and thoroughly tested; afterwards, it is deployed independently too.
Now that you've completed the full-fledged system development cycle, go for the testing part now. There are three metrics for testing the application and system:
Automated testing—end-to-end tests, unit tests, and integration tests
Performance testing—load testing and overall performance testing
Security testing—penetration testing and vulnerability assessments
Under application/system deployment, you must first consider setting up Continuous Integration/Continuous Deployment (CI/CD) pipelines. This step is necessary for a smooth and automated system deployment process. In cloud deployment, you can implement top-rated applications like AWS, etc., to extensively utilize and scale your system.
Lastly, you must implement robust system monitoring and logging tools to track the application performance and activity logs.
There starts your post-deployment tactics! Right here when you need to think about optimal system maintenance measures.
Start with keeping system regularities in check and up-to-date with the latest security patches. The scalability features of your microservice architecture must be the latest and adaptable with changing market demands. You must also conduct code reviews periodically and refactor them to maintain the code quality.
To enhance the system's performance, you must implement caching and database optimization, regular monitoring, user iteration, and feedback. You may also plan the required iterative updates based on user feedback.
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Amazon doesn't need any introduction. Previously a monolith in the early 2000s, Amazon initially found it working well. However, as the codebase expanded with the growing database and projects, the development team was affected negatively. as they needed to struggle a lot to manage and scale through the tightly coupled services and their functioning. This further resulted in productivity loss, brand mismanagement, etc.
Though Amazon's customer base was growing rapidly, the team was unable to meet the scaling requirements as per the demand. Amazon then broke out from its monolith shell and adopted a microservice structure by breaking its system into smaller, independent services that were loosely coupled. Now the brand has become more able to modify individual service features within the system without affecting the major system segments.
It was all Amazon wanted! It made massive improvements through its “service-oriented architecture” and introduced a handful of other business solutions to support its architecture.
Etsy stands proud with a successful microservices-based infrastructure. Initially, this brand started to face backlash due to its poor server processing time. In its scaling strategy, Etsy decided to adopt concurrent transitions to achieve its goal of reducing the processing time to “1,000-millisecond time-to-glass.”
For this, Etsy's API team needed to build a new approach—to keep the API familiar and accessible. At that time, Etsy's PHP-based system had certain limitations that made API calls virtually impossible; hence, the team's main challenge was to undo this.
Eventually, the team started utilizing cURL for parallel HTTP calls. They also developed a custom Etsy libcurl patch, relevant monitoring tools, and various developer-friendly tools to speed up the tasks for developers.
In 2016, Etsy went live, and since then it is benefitting from its concurrent processing techniques!
This taxi service, Magnum, also began as a monolith initially but began to encounter various growth hurdles soon after its launch. To fix bugs, add new features, and rapidly integrate them with the growing global operations, Uber needed a robust and extensive new approach. It was already struggling with a clunky system design, and hence Uber decided to dissolve into microservice architecture since then.
After breaking its structure into cloud-based microservices, Uber's developer team subsequently built individual microservices for different functions and connected them via an API gateway. Since Uber adopted microservice architecture in its early stage, the changes were also faster than its contemporary rivals. Fewer functions were only needed to mix within the existing monolith design, which made the task simpler for the team.
Scalability in a microservices architecture is a key factor in the overall system design. If you want to showcase the best scalability features of your system, then you must opt for the top-rated software engineering services. Getting professional help is never a hard initiative to perform. Of course you will get more chances to build scalable systems by managing more traffic and data.
The above-mentioned step-by-step guide isn't just information, but a whole bundle of cost-effective strategies for performance optimization itself. You can utilize this information to its best form while planning for your next business venture!
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