10 min.

Design principles for microservices in AWS

Overview of design principles for microservices and their application in AWS based microservice architectures.

Microservices represent a software development approach where applications are structured as a collection of small, autonomous services, each communicating through well-defined APIs. 


Unlike monolithic architectures where applications are built as a single, interdependent unit, microservices allow each process to function independently. This structure not only simplifies scaling individual components as needed but also accelerates development, fostering innovation and quicker delivery of new features.


In contrast to monolithic architectures, where all processes are interlinked and scaling requires expanding the entire system, microservices operate independently. This independence means that in the event of increased demand, only the specific service in need can be scaled, avoiding the complexity and risk associated with scaling a monolithic application. 


Moreover, this decoupling reduces the risk to application availability since a single process failure has less impact on the overall system.


Within the AWS ecosystem, microservices are implemented as independent components, each responsible for a distinct function and communicating predominantly via HTTP APIs. This architectural choice allows for more manageable and efficient application scaling and updating.


Key characteristics of microservices include:



Each service in a microservice architecture operates independently, without sharing code or implementation with others. Communication between services is handled through clearly defined APIs, allowing each to be developed, deployed, and scaled without impacting others.



Services are tailored to specific business capabilities, focusing on solving particular problems. This specialization means that if a service becomes overly complex, it can be subdivided further into more manageable, focused services.

This approach contrasts sharply with monolithic architectures, where every aspect of the application is tightly coupled, making changes and scaling more challenging and risk-prone



What are design principles for microservices in AWS


Design principles for microservices focus on creating small, independently deployable services, each responsible for a specific function or business capability.


Key principles include:


Decomposition into Small Services


Structure the application into multiple small, independent services. Each service should align with a business capability, and be capable of being developed, deployed, and scaled independently. AWS services like Lambda, EC2, ECS, and EKS are ideal for running these microservices in both containerized and serverless environments.





Designing services in such a way that they don't retain user or session-specific data internally between requests. Instead, they rely on external services to store any necessary state. This approach contrasts with stateful services, where the service itself holds and manages the state, which can complicate scaling and recovery from failures.


Store any necessary state in external databases or storage services. AWS offers options like Amazon RDS for relational databases, Amazon DynamoDB for NoSQL, and Amazon S3 for object storage.


Use stateless compute services like AWS Lambda, which inherently don't retain state between function calls, or containerized services using Amazon ECS or Amazon EKS, where containers can be stateless and ephemeral.


Implement stateless authentication mechanisms offered by Cognito and API Gateway like JWT (JSON Web Tokens) that don't require server-side session storage




Loose Coupling and Asynchronous Communication


Services should be loosely coupled and communicate asynchronously through well-defined APIs. This approach facilitates independent development and evolution of services. AWS API Gateway can be utilized for managing these APIs.


Both Amazon SQS and Amazon SNS facilitate loose coupling between microservices. Instead of services communicating directly with each other, they can communicate indirectly through queues (SQS) or topics (SNS). This setup means a change in one service doesn’t necessitate changes in others, as long as the communication contract via queues or topics remains consistent



Dedicated Data Storage


Use AWS databases such as DynamoDB, RDS, or ElastiCache to enable each service to manage its data independently, avoiding the complexities of a centralized database.



Monitoring and Distributed Tracing


Implement comprehensive monitoring across services using tools like AWS CloudWatch for logging and AWS X-Ray for tracing interactions between microservices, aiding in troubleshooting.



Service Discovery and Load Balancing


Utilize AWS API Gateway and Application Load Balancer for service discovery and balancing the load across multiple service instances.


Route 53 can also be used for service discovery. It allows services to register their instances and can route traffic based on various conditions like endpoint health, geolocation, etc


AWS Cloud Map enables to define custom names for your application resources, and it keeps track of the changing locations of these dynamically changing resources. This makes it an ideal service discovery tool in AWS, allowing applications to discover and connect with each other seamlessly.



Automated Deployment Pipelines


Leverage AWS CodePipeline and CodeDeploy to automate the continuous delivery process of microservices.



Single Responsibility and High Cohesion


Adhere to the Single Responsibility Principle, ensuring each microservice is focused on a specific function. High cohesion within services ensures that their internal components are closely related.



Scalability Considerations


Design services to scale out, adding more instances as needed, rather than scaling up. This approach is more efficient and cost-effective in cloud environments.



Environment and Configuration Management


Manage configurations and environments separately using tools like AWS Parameter Store or AWS Secrets Manager.



Security Practices


Incorporate strong security measures using AWS IAM for access control and Amazon VPC for network security.





Be mindful of costs, leveraging pricing models such as reserved or spot instances for optimal resource utilization.



API First Design


Prioritize API design to delineate service boundaries and facilitate effective communication between services.



What services from AWS can be used for microservice architecture


AWS offers a comprehensive suite of services that are well-suited for building and managing a microservice architecture. These services provide the necessary tools for development, deployment, monitoring, and scaling of microservices. 


Key AWS services used in microservice architectures:


Amazon EC2 (Elastic Compute Cloud)


Provides scalable virtual servers to run microservice applications.



AWS Lambda


A serverless computing service that runs code in response to events, ideal for microservices that are event-driven and require no permanent server.



Amazon ECS (Elastic Container Service)


A highly scalable container management service that supports Docker containers and allows you to run applications on a managed cluster of Amazon EC2 instances.



Amazon EKS (Elastic Kubernetes Service)


A managed service to run Kubernetes on AWS, ideal for microservices that use Kubernetes for orchestration.



AWS Fargate


A serverless compute engine for containers that works with both Amazon ECS and EKS, allowing you to run containers without managing servers or clusters.



AWS API Gateway


Allows you to create, publish, maintain, monitor, and secure APIs at any scale. It acts as a “front door” for applications to access data, business logic, or functionality from your backend services.



Amazon S3 (Simple Storage Service)


Provides scalable object storage for data storage and backup, ideal for storing static files and assets.



Amazon RDS (Relational Database Service)


Simplifies setting up, operating, and scaling a relational database. It supports various database engines.



Amazon DynamoDB


A fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale.



AWS Step Functions


Coordinates multiple AWS services into serverless workflows so you can build and update apps quickly.



Amazon SQS & Amazon SNS


Provide messaging and notification services to decouple and scale microservices, distributed systems, and serverless applications.



AWS CloudFormation


Allows you to model and provision AWS and third-party application resources with Infrastructure as Code.



AWS CodePipeline, AWS CodeBuild, AWS CodeDeploy


These services are part of AWS’s continuous integration and continuous deployment (CI/CD) offerings, helping automate the software release process.



AWS CloudWatch


Provides monitoring and observability of your microservices and applications. It collects and tracks metrics, collects and monitors log files, and sets alarms.





Helps developers analyze and debug distributed applications, such as those built using a microservices architecture.



AWS Elastic Load Balancing (ELB)


Automatically distributes incoming application traffic across multiple targets, such as Amazon EC2 instances, containers, and IP addresses.



AWS Cloud Map & Amazon Route 53


For service discovery, allowing services to discover and connect with each other.





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