Microservices revolutionize how large-scale applications are structured by breaking them down into discrete, autonomous components, each with its own well-defined scope of operation. This modular approach allows a microservices-based application to seamlessly orchestrate multiple internal microservices in response to a single user request. The inherent flexibility of microservices architectures facilitates efficient scaling and expedites the development process, empowering teams to innovate and swiftly introduce new features to the market. This agile framework ultimately translates into a significant reduction in time-to-market for cutting-edge functionalities.

Microservice stands as a pillar for event-driven applications (EDAs), which empowers applications to take action or respond to events. In contrast to the request-response model, here, clients receive data automatically when an event occurs within the application. Microservice advocates for EDA as it is based on loose coupling between components, fostering flexibility and agility. 

In similar scenarios, one of our clients, a call center business owner, approached us with a specific challenge- they needed an application that could effectively monitor and enhance employee productivity. The plan involved using laptop cameras to take pictures at regular intervals during the workday. These images would then undergo sophisticated analysis to detect the duration spent or actively engaged with the computer,  instead of engaging in activities like phone usage or temporarily leaving their work. Our task was to transform this concept into a functional and user-friendly application.

The client needed to ensure that their employees gave full attention, and this was a challenging endeavor for us as this required a scalable application that was not only capable of performing intricate image analysis but also met crucial technical requirements as mentioned below:

Need for  Scalability, High Availability, Security, and Performance:

The application had to be designed to accommodate higher workloads. This means it should be able to handle increased demands without compromising performance or causing disruptions.

It also needed to be structured to ensure it remained accessible and operational around the clock, without any significant downtime.

Due to the sensitive nature of the data, the application needed to be incorporated with robust security measures. This included encryption, access controls, and other safeguards against unauthorized access or data breaches.

Cost Optimization in Cloud Infrastructure: 

Given the choice of AWS (Amazon Web Services) as our cloud provider, cost optimization was a key consideration. We aimed to build an efficient infrastructure that would not only meet our client’s needs but also be cost-effective.

Techment’s Targeted Approach:

Our client necessitated an application capable of handling substantial volumes of data from diverse devices with a robust security framework. Hence, the desired solution must be scalable, secure, cost-effective, and high-performance. To address these challenges, we decided to adopt a microservices architecture, leveraging serverless technologies offered by AWS.

Microservices for Agility and Efficiency

Microservices architecture involves breaking down an application into smaller, loosely coupled services, each responsible for specific functionalities. This method gives businesses increased flexibility and agility, enabling them to split out specific functions.

Scalability: In a microservices architecture, scaling becomes highly specific and accurate. This approach allows the ability to allocate resources to individual microservices. This level of flexibility ensures the optimal utilization of resources and cost-effectiveness.

High Availability: To provide continuous and uninterrupted services, we ensured high availability by distributing services across multiple instances.

Security: Microservices can be isolated, and security can be implemented at each microservice level.

Performance: Smaller, focused services often improve performance as they can be optimized individually.

Key Components of Applied Microservice for Agility & Efficiency

DNSSEC for Enhanced Security:

To ensure the workplace productivity monitoring application, implementing DNSSEC provided an additional assurance that communication between various microservices occurs securely. This was especially important when dealing with sensitive data from laptop cameras, as it helped to protect against potential DNS-related attacks or spoofing attempts. When microservices communicate with one another (e.g., for data retrieval or processing), it relies on DNS to locate the specified service’s endpoint. DNSSEC prevents malicious actors from redirecting or intercepting these requests, ensuring the communication remains secure and trusted. 

CloudFront and S3 for Web Hosting:

Amazon S3 Bucket was utilized to host our web layer using Amazon CloudFront to deliver, track, and manage the data. The S3 bucket was not accessible to the public internet; only the AWS CloudFront service could access it. We employed Cloud Functions with CloudFront for header security checks. A backup S3 bucket was also linked to CloudFront through a group origin policy, ensuring that data would be served from the backup bucket in case of primary bucket downtime.

AWS Fargate for Docker Container Hosting:

One of the primary requirements was to ensure the scalability of resources as we capture data from remote locations during a particular monitoring cycle. Utilizing AWS Fargate proved to be an ideal solution for dynamically allocating resources based on demand, optimizing both performance and cost, and managing the dynamic aspects of our deployments.

It allowed us to effortlessly manage sudden spikes in real-time workloads while allowing our developers to receive almost instant feedback on deployments, all without the hassle of managing infrastructure or facing downtime. The seamless integration with Fargate streamlined this process.

Decoupled Architecture for Flexibility

To enhance flexibility and maintainability, we designed our architecture with separate layers: web layer, web API layer, application layer, and database layer. This decoupled approach allowed us to update and scale each layer independently, reducing complexity.

Amazon Aurora for Database

Amazon Aurora, a relational database engine, ensures cost-effectiveness with the power, performance, and reliability to efficiently store and manage our application’s data. We chose this option because it scales automatically based on the load and reduces the cost when no activity exists. It automatically increases the database volume’s size by storage needs.

Serverless Image Storage and Analysis

Amazon Rekognition is a fully managed machine learning service connected to S3, which stores face recognition images. AWS Lambda enabled us to execute code responding to events, such as image uploads, while Amazon Rekognition provided powerful image analysis capabilities. S3 served as a secure and scalable storage solution for our image data. 

Lambda functions by analyzing data stored in S3 and gets triggered when Rekognition sends the task completion status, i.e., about detected faces, emotions, and activities in the images. We stored the images and the analysis results in S3 buckets. 

Angular and .NET Core for Application Development

For Application Development, we harnessed the power of Angular and .NET Core, two robust technologies. We seamlessly integrated Amazon API Gateway into our architecture to expose our web APIs. Leveraging the capabilities of .NET Core, we meticulously crafted a strong backend, focusing on building RESTful APIs that ensure efficient data communication. We turned to the versatile Angular framework, utilizing its components, services, and directives. 

Maximizing Scalability through Microservice: Containerization, Orchestration, and Continuous Deployment

Mastering the art of designing a scalable microservices architecture is paramount in achieving high-performance applications that meet the demands of today’s dynamic digital landscape. By prioritizing loose coupling, fault isolation, and efficient communication, developers can lay the foundation for systems that effortlessly adapt to growing user bases and evolving requirements. Embracing containerization, orchestration, and continuous deployment practices further enhances scalability, ensuring seamless expansion and resource optimization. Ultimately, the journey towards a high-performance microservices architecture is an investment that pays off in agility, resilience, and a competitive edge in the ever-evolving world of software development.

Unlock the full potential of your scalable and distributed applications with Techment Technology. Elevate your microservices infrastructure with us and enable your organization to construct robust, scalable, and high-performing microservices applications. Connect with our experts for more. 

About the Author: Amit Sharma, Solution Architect, role encompasses comprehensive system design, crafting high-level system architectures, architectural reviews, code assessments, and proactive risk management, fostering innovation and seamless technology adoption.