Mastering microservices architecture on AWS – A complete guide with examples

Intro

Microservices help businesses build flexible and scalable applications. AWS offers many tools to support this approach and makes it easier to manage services, handle data, and keep systems running smoothly.

In this guide, our team at Touchlane covers the key AWS services, steps to build a microservices system, and real-world examples to show how companies use this approach.

Key components of microservices on AWS

Selecting the fitting resources can influence how well your system scales and functions. Below we offer an overview of some essential AWS services to consider. 

Compute – AWS Lambda, EC2, and ECS 

AWS offers a variety of compute resources suited for different microservice-related needs. AWS Lambda facilitates running code in response to events without handling server provisioning. This can reduce overhead for smaller tasks or specific triggers within your application. Amazon EC2 provides more control with virtual servers that can be configured based on performance and resource requirements. For containerized apps, running and managing Docker containers is supported by Amazon ECS, which helps orchestrate microservices at scale with the flexibility to choose different compute instances. 

Networking – Amazon VPC, API Gateway, and Elastic Load Balancing 

In microservices, networking guarantees uninterrupted communication between services. Amazon VPC (Virtual Private Cloud) provides a dedicated, isolated network to host your resources and control IP addresses, subnets, and routing. Amazon API Gateway helps manage APIs and facilitates easy, scalable interaction between microservices. It exposes APIs in a secure way and supports controlled access to services. Meanwhile, Elastic Load Balancing (ELB) automatically distributes incoming app traffic across multiple targets. 

Data – Amazon RDS, DynamoDB, and S3 

Amazon RDS (Relational Database Service) supports various database engines and makes database setup, administration, and scaling easier. For non-relational data, Amazon DynamoDB provides a fast and flexible NoSQL solution that scales to meet the demands of future-ready apps. Amazon S3 serves as a scalable object storage solution and offers secure storage for large amounts of data. 

Monitoring – CloudWatch, AWS CloudTrail, and X-Ray  

Amazon CloudWatch is a useful instrument for real-time monitoring of AWS resources and apps, which helps to track and fix issues that affect performance. AWS X-Ray gives detailed insights into application behavior and traces requests to understand latencies between services. AWS CloudTrail records user activity and API calls, providing an audit trail of your AWS environment that can be crucial for compliance and safety. 

Overall, if you integrate these AWS services into your microservices setup, your company can maintain better control, scalability, and visibility, as well as support both current and future growth.

Five steps to implement microservices on AWS

1.

Define your microservices architecture

Start by dividing your application into standalone services that can be launched independently. Clearly define the responsibilities and boundaries of each service and emphasize specific business capabilities. Work closely with your team to map out how these services will communicate with one another and with external systems. Focus on building a foundation that supports scalability, fault tolerance, and modularity during this stage.

2.

Choose appropriate AWS services

Determine the AWS services that best support your business needs. For instance, in a microservices architecture, AWS Lambda handles computation tasks. You can refer to the information in the previous section to guide your decision. 

3.

Set up service discovery and communication

As you already know, microservices depend on efficient communication. AWS Cloud Map supports dynamic service discovery and helps microservices locate each other. Our team recommends utilizing Amazon Simple Queue Service (SQS) or Amazon Simple Notification Service (SNS) to facilitate asynchronous communication. Build secure and dependable APIs with Amazon API Gateway.

4.

Deploy microservices with AWS EKS or AWS Fargate

Using containers makes managing microservices more efficient. AWS EKS integrates with Kubernetes to orchestrate containerized applications while supporting high scalability. For a more hands-off approach, AWS Fargate allows you to run containers without managing infrastructure. Tools like AWS CloudFormation or Terraform help automate deployment through Infrastructure as Code (IaC).

5.

Monitor and improve performance

Use AWS monitoring tools like Amazon CloudWatch and AWS X-Ray to track system performance and health. Next, try to detect bottlenecks, maintain high availability, and promptly resolve potential issues. Frequently assess system metrics to drive improvements and preserve the flexibility of your architecture.

Microservices – Common struggles and resolutions

While being an indispensable tool for app development, microservices still come with their own pitfalls. What are these and how do you solve them? Let us take a closer look.

Managing data consistency across microservices

Dividing an application into multiple microservices can make data consistency challenging. Typically, a service manages its own database, and synchronizing these databases requires careful planning. Problems such as race conditions or outdated data may arise, particularly during updates or transactions that involve multiple services.

How to solve

Use event-driven architecture to manage data updates. For instance, employ Amazon Simple Notification Service (SNS) or Amazon EventBridge to broadcast events between services. Integrating a distributed transaction manager, which coordinates transactions across multiple services to confirm all operations succeed together, or applying patterns such as Saga will help maintain consistency while preventing bottlenecks.

Handling service-to-service communication

Microservices rely on service interactions to form a cohesive system. These interactions can cause latency, add complexity to the system, and increase the risk of failure when services depend on each other.

How to solve

Use asynchronous communication when possible to decouple services and boost resilience. AWS offers tools such as Amazon SQS (Simple Queue Service) for message queuing as well as Amazon API Gateway for efficient API management. Also, retry mechanisms and circuit breakers should be incorporated to manage failures effectively. Circuit breakers are design patterns that monitor and limit the impact of failures in interconnected systems by temporarily stopping operations to prevent cascading issues.

Striking a balance between cost and performance

Microservices often require deploying multiple smaller services, which can increase operational costs without careful management. Balancing costs with performance demands can present significant challenges.

How to solve

Monitor resource usage frequently and allocate resources as needed based on demand. AWS provides tools such as Auto Scaling and AWS Cost Explorer to track and adjust resources. AWS Lambda can handle event-driven, on-demand processing and prevent idle services. Thoughtful design decisions in database management and network communication can help reduce costs while maintaining performance.

Examples of microservices implementation on AWS

Microservices architecture has been rising in popularity in modern software development. Big tech companies from Amazon itself to Netflix rely on it for speed and adaptability.

One of the most prominent recent examples of such implementation is NVIDIA. The company has integrated its AI microservices, NIM, with AWS to produce instruments for drug discovery, medical imaging, and genomics. This partnership gives developers access to AI models via AWS’s infrastructure, which facilitates the deployment of machine learning models and high-performance computing clusters. Additionally, the collaboration supports AI applications for decoding proteins, analyzing genomic sequences, and advancing healthcare research.

Another AWS microservices architecture example​ is DoorDash. The popular food delivery company transitioned from a monolithic to a cell-based microservices architecture hosted on AWS to support its rapid growth. Its Supercell project addressed issues like failure isolation and deployment strategies.

Conclusion

Microservices architecture offers greater flexibility, resilience, and efficiency for businesses that implement it. Although challenges like data consistency and cost control can arise, with proper planning and AWS tools, companies can tackle these issues and remain agile and competitive. Microservices are used by giant corporations and startups alike, supported by flexibility that AWS offers.

At Touchlane, we employ microservices in our projects for the most demanding industries and we know how to build a microservices architecture for a future-proof application. Contact our team to discuss if we can help you build one, too.