Overview of Microservices system

Microservices system

Microservices is an approach to software development architecture that is characterized by the division of an application into multiple small independent services (microservices). Each microservice can be developed, deployed, extended, and maintained individually and has its own unique functionality. The features and benefits of microservices are described below.

• Service Partitioning: By partitioning the application into multiple smaller services, each service is responsible for a specific business function or area of responsibility. This avoids a monolithic structure for the entire application and improves flexibility and maintainability.
• Independence and Scalability: Because microservices are developed and deployed independently, each service can have its own schedule and technology stack. Only individual services can be scaled up or down as needed.
• Loosely coupled services: Microservices communicate via an API (Application Programming Interface). Each service is loosely coupled, hiding internal implementation details. This allows each service to use its own technology stack and database, and to develop and evolve independently.
• Polyglot pattern: In microservices, individual services can use their own databases and technology stacks. This approach is called polyglot and allows for the selection of the most appropriate database and technology to fit the requirements of each individual service.
• Team Independence: The microservices approach allows for the assignment of specialized teams to each service. Each team has its own responsibilities and authority, allowing for rapid development and deployment. In addition, teams for different services can proceed independently.

Microservices architecture is well suited for developing large systems and applications with complex business requirements. However, care must be taken in applying it, as proper service partitioning and communication coordination are important.

Components used in microservices

In a microservice architecture, multiple independent microservices work in concert. The following describes the general components used in microservices.

<Services>

In a microservices architecture, an application is divided into a number of small independent services. Each service is responsible for a specific business function and can be developed, deployed, scaled, and maintained independently. The following describes the characteristics of services and considerations for microservices.

• Single responsibility: Each service is responsible for a specific business function or responsibility. For example, a service may be responsible for user management, payment processing, product catalog, etc. By focusing on its responsibilities, the service improves code maintainability and understandability.
• Loose Coupling: Loose coupling between services is an important factor. Since each service is developed and deployed independently, it should not depend on the internal implementation details of other services. Communication between services is via APIs, and each service can have its own data model and technology stack.
• Scalability: Microservices will be individually scalable, allowing only the most heavily loaded services to be scaled up as needed. This flexibility allows for optimal use of resources and improved performance.
• Proprietary Database: Each service can have its own database as needed. This allows for independent management of relevant data within a service and the selection of the appropriate data model and database technology for each service.
• Distributed development and independence: In a microservices architecture, each service can be assigned to a separate development team. This distributed development approach allows for rapid iteration and agility.
• Monitoring and Troubleshooting: Monitoring and troubleshooting each service will be a critical function. This will specifically involve tools and mechanisms such as logging, metrics, dashboards, and tracing to monitor the status of each service, as well as troubleshooting and performance tuning.
• Version Control and Deployment: A version control and deployment process should be established for each service as an independent deployable unit. Each service is deployed on a different schedule and can be upgraded and rolled back independently.

Services in microservices have their own independence and responsibilities, allowing for flexible scaling and maintainability. However, appropriate service partitioning and communication coordination are important, and care must be taken to ensure data integrity and consistency.

<API (Application Programming Interface)>

In microservice architecture, APIs play an important role in achieving communication and interaction between different services. APIs are interfaces that enable data to be sent, received, and manipulated between services. Below we discuss some key points regarding the role and design of APIs in microservices.

• Communication between services: In a microservices architecture, since each service operates independently, communication between services is done through APIs, which exchange data in the form of requests and responses to enable coordination and cooperative behavior between services.
• REST or GraphQL: The design of APIs in microservices typically involves the use of architectural styles and protocols such as Representational State Transfer (REST) and GraphQL. methods to expose data and support common CRUD operations, while GraphQL uses a query language and schema to provide flexible data retrieval.
• API Gateway: In a microservices architecture, an API gateway may be used, which is responsible for receiving external requests and routing them to the appropriate service. It may also provide authentication, authorization, security, traffic control, and other functions.
• API Design: The design of the API is an important element in ensuring smooth communication between services; it is recommended that conventions such as RESTful URL structures, endpoint naming conventions, and data representation formats (e.g., JSON and XML) be followed, and that API versioning and error handling, etc. should also be considered in the design.
• Documentation and self-descriptiveness: API documentation provides developers with information on how to use the API, endpoints, parameters, response format, etc. Documentation should be clear and detailed, and should typically be generated automatically using self-descriptive tools such as Swagger or OpenAPI.
• Testing and Mocking: Testing and mocking of the API will be an important element. Since each service will be developed independently, unit and integration testing should be performed on each service’s API, and it is also recommended that mocking services be used to test integration with other services.
• API Security: API security is also an important consideration. Security measures such as authentication, authorization, access control, and data encryption are necessary, and it is common to implement security mechanisms such as API gateways and token-based authentication.

APIs enable communication between different services in a microservice architecture, increasing flexibility and scalability, and proper API design and management are critical to the success of microservices.

<Database>

In a microservice architecture, it is common for each service to have its own database. This allows each service to manage its own data and optimize database selection and schema design for each service. The following sections describe the key elements of databases in microservices. For details on the database technology on which they are based, please refer to “Database Technology“.

• Service-specific databases: In microservices, it is common for each service to have its own database, allowing the selection of the database technology best suited to the responsibilities and data model of the service. In this section, we use relational databases, document stores, caches, graph databases, and other databases depending on the intended use.
• Database Patterns: Database patterns in microservices include methods for each service to ensure data integrity and consistency. Patterns include patterns in which each service updates data independently and patterns in which data is copied and synchronized.
• Data Sharing and Consistency: Microservices need to manage data sharing and consistency. Data sharing can be achieved by notifying other services of changes via event-driven or messaging, and integrity can be maintained using techniques such as distributed transactions, event sourcing, and CQRS (Command Query Responsibility Segregation). Database Migration: Database migration is a key component of microservices.
• Database Migration: As microservices are developed and modified, database schemas are frequently changed or migrated. Since each service has its own database schema, schema changes are made for individual services.
• Database Protection and Security: Database protection and security are also important elements of microservices. Each service’s database requires security measures such as access control, encryption, and vulnerability protection, and backup and restore strategies are also an important part of database management.
• Database Monitoring and Scaling: In a microservices architecture, monitoring and scaling the database for each service is critical. Database performance, capacity, and query optimization can be monitored and scaled as needed to ensure service performance and availability.

Database design and management in microservices is a key element in ensuring that each service manages its data independently. Database considerations such as data integrity and consistency, handling database schema changes, and implementing security and monitoring will impact the success of a microservices architecture.

<Messaging and Event-Driven>

Messaging and event-driven approaches are widely used in microservice architectures. These techniques are used to enable communication and interaction between microservices. An overview of messaging and event-driven approaches and their advantages are described below.

• Messaging: Messaging provides an asynchronous communication method between microservices. It involves one service generating a message and another service receiving it, and messages are sent and received via a message broker, such as a queue or topic.
  • Event-driven messaging: In event-driven messaging, communication occurs when a service generates an event and another service subscribes to it. This increases loose coupling between services, events are processed asynchronously, and message brokers receive and deliver events to subscribers.
  • Request-Response Messaging: In request-response messaging, a service generates a request and other services respond to it. The message broker receives the request, sends it to the corresponding service, and returns a response. This technique is used when exchanging requests and responses between different services.
• Event-driven: In an event-driven architecture, services operate in response to specific events. An event is information that indicates that something has happened, and in an event-driven approach, whenever an event occurs, the associated service responds to it and performs the necessary processing.
  • Event Sourcing: Event sourcing would be a method of capturing data state changes as events and maintaining a history of changes. Each service subscribes to the event stream and updates the necessary data, thereby tracking the history of data state changes.
  • CQRS (Command Query Responsibility Segregation): CQRS is an architectural pattern in which data updates (commands) and data retrieval (queries) are handled in separate models. Data updating is event-driven, while data retrieval is performed in an optimized query model. This allows for flexible data manipulation and improved query performance.

The advantages of messaging and event-driven are as follows

• Loose Coupling and Scalability: Messaging and event-driven provide greater loose coupling between services and the flexibility to scale each service individually. This allows each service to receive information via messages and events and perform the necessary processing.
• Maintainability and Scalability: The messaging and event-driven approach improves maintainability and scalability because each service can be developed, deployed, and maintained independently. This makes it easy to add new services or modify existing ones.
• Flexible Integration: Messaging and event-driven allows flexible integration of microservices built using different technology stacks and programming languages. This allows each service to communicate and interact according to event and message formats.

Messaging and event-driven are powerful techniques for achieving flexibility, loose coupling, and scalability in microservice architectures. However, care must be taken in design and management, including selection of an appropriate messaging platform, design of events, and implementation of messaging patterns.

<Monitoring and Tracing>

In a microservices architecture, monitoring and tracing each service plays an important role. Because microservices run in a distributed environment, the performance, availability, and troubleshooting of each service must be tracked. Below is an overview of monitoring and tracing and its benefits.

• Monitoring:
  • Logging: Each microservice service generates logs and sends them to a centralized logging system. The logs record application behavior, errors, critical events, etc., to help identify and troubleshoot problems.
  • Metrics: Each service collects performance metrics (CPU utilization, memory usage, number of requests, etc.) and sends them to the monitoring system. Metrics provide visibility into the state of the system and help provide early warning of load or failure.
  • Dashboard: The monitoring system provides a dashboard to visualize the status and metrics for each service. The dashboard displays real-time status and serves as a centralized control point for service performance and availability.
• Tracing:
  • Distributed Tracing: Distributed tracing can be used to track the flow and timing of requests across microservices. Each service adds tags and context to requests, which are then tracked by tracers, enabling the identification of request paths, latency, bottlenecks, etc.
  • Performance optimization: Tracing data provides visibility into communications and dependencies between services and helps identify bottlenecks and performance degradation. This allows bottlenecks to be identified and optimized to improve overall system performance and response time.
  • Troubleshooting Errors and Failures: Tracing data can help identify and troubleshoot problems when errors or failures occur. By tracking the flow and timing of requests, the cause of errors and failures can be identified and promptly addressed.

The benefits of monitoring and tracing include

• Performance Visibility: Monitoring and tracing provides real-time visibility into the performance and availability of microservices. This allows for early detection and response to problems by analyzing metrics, logs, and trace data.
• Rapid troubleshooting: Monitoring and tracing can help identify and troubleshoot problems. Analysis of log and trace data can identify the cause of errors and failures and enable rapid response.
• Performance Optimization: Monitoring and tracing provides insight to identify and optimize specific bottlenecks or poor performance of the system.
• Visualization and Reporting: Monitoring and tracing provides visibility into service status and trends through dashboards and reports to inform operations teams and developers.

Monitoring and tracing is a critical component to improving the operation and availability of a microservices architecture. Selecting and configuring the right tools and platforms, monitoring critical metrics and events, and collecting and analyzing tracing data are key requirements.

<Load Balancing and Scaling>

Load balancing and scaling are also important elements in a microservices architecture. These techniques help improve application performance and ensure availability. The following sections provide an overview of load balancing and scaling and their benefits.

• Load Balancing:
  • Load Balancing: Load balancing can be achieved by using a load balancer, which is responsible for taking requests and distributing them evenly across multiple service instances on the backend. The load balancer forwards requests to the appropriate service based on a load balancing algorithm (round robin, weighted, etc.).
  • Availability and Scalability: Load balancers improve application availability and scalability by distributing heavily loaded traffic. When load increases, new service instances are added and the load balancer distributes requests to the new instances.
  • Health Check: The load balancer periodically performs health checks (health probes) on back-end services and only forwards requests to services that are in good health. Health checks help maintain availability by avoiding requests from services that have failed.
• Scaling:
  • Horizontal scaling: In a microservice architecture, each service can be scaled out individually. As load increases, new service instances are added to increase request throughput. Horizontal scaling provides evenly distributed load, high availability, and improved performance.
  • Auto-scaling: Auto-scaling will be the ability to automatically increase or decrease the number of service instances based on load. Based on monitoring and thresholds, services are scaled to keep load within a certain range, thereby ensuring efficient resource use and adequate performance.
  • Containerization and Orchestration: Microservice scaling is more effective when combined with containerization and orchestration platforms (such as Kubernetes). Containerization allows services to be packaged independently and scaled out flexibly, while orchestration platforms manage container deployment and scaling, optimizing resources and enabling automated scaling. Kubernetes Overview and Configuration,” etc.

The benefits of load balancing and scaling include

• High availability: Load balancing distributes the load of requests across the system, reducing the impact of individual service failures. Scaling also increases request throughput and improves response times.
• Efficient resource utilization: Scaling allows resources to be automatically added or subtracted as load increases. This ensures efficient resource utilization and cost optimization.
• Flexible Scalability: Microservices architecture allows each service to be scaled out individually, so that only the services that are needed can be scaled. This allows for flexible use of resources.

<Service Discovery and Configuration Management>

Service discovery and configuration management are key elements in microservice architecture. Using these techniques, it is possible to know the location and state of each service and manage its settings and configuration.

• Service Discovery:
  • Service Registry: The Service Registry will be a central database and service for managing microservice registration and discovery. Each service registers itself in the Service Registry at startup, and other services retrieve service location and connection information from the Service Registry.
  • Service Discovery Protocols: Different protocols are used for service discovery. Common protocols include Eureka, Consul, etcd, and ZooKeeper. These protocols provide functions such as service registration, discovery, health checks, and load balancing.
  • Client-side load balancing: Client-side load balancing is common when using service discovery. The client obtains a list of all available services from service discovery and selects services based on load balancing algorithms when sending requests.
• Configuration Management:
  • External Configuration Store: Microservice configuration is stored in an external configuration store. The configuration store holds configuration information in the form of environment variables, configuration files, databases, etc. Each service retrieves the necessary configuration from the configuration store at startup and uses it at runtime.
  • Dynamic configuration updates: Microservice configurations can change dynamically. Using the configuration store, configuration changes and updates can be reflected in real-time, and each service periodically polls the configuration store to detect and apply changes.
  • Secure configuration management: Configuration information may contain sensitive information. The configuration store should provide encryption and access control for sensitive information to achieve secure configuration management.

The benefits of service discovery and configuration management include

• Dynamic service discovery and connection: Using service discovery, microservices can start and stop independently and establish connections to other services. This ensures that if a service’s location or connection information changes, other services are automatically kept up-to-date.
• Load Balancing and Failover: Service Discovery is also used for load balancing and failover. This ensures that requests for each service are load balanced and evenly distributed among the available services. In the event of a failure, the service is automatically switched to another available service.
• Centralized configuration management and flexibility: Configuration management centralizes settings and configuration information for each service, increasing consistency and flexibility. Configuration changes and updates are made in a central configuration store, and each service retrieves the necessary configuration and configures itself.
• Security and Access Control: The configuration store provides security measures to ensure confidentiality and access control of configuration information. This allows encryption of sensitive information and access policies to be set and maintained at appropriate security levels.

Service discovery and configuration management are essential to improve flexibility and scalability in a microservices architecture. Therefore, it is important to select appropriate service discovery protocols and configuration stores and to implement appropriate security measures.

Tools and platforms used to build microservice systems

Various tools and platforms are used to build microservice systems. The following is a list of some of the most common ones.

<Container orchestration tools>

• Kubernetes: Kubernetes will be an open source container orchestration platform developed by Google. It provides various functions such as container deployment, scaling, rolling updates, automatic recovery, load balancing, and security management, as well as high availability and fault tolerance through clustering.
• Docker Swarm: Docker Swarm is a Docker-native container orchestration tool based on the Docker engine that allows you to group Docker containers into a single cluster for easy scaling and high availability. Docker Swarm allows you to combine Docker containers into a single cluster for easy scaling and high availability.
• Amazon ECS(Elastic Container Service): Amazon ECS will be a fully managed container orchestration service provided by Amazon Web Services (AWS). This allows for easy deployment, management, and scaling of Docker containers on AWS.
• Microsoft Azure Kubernetes Service(AKS): AKS will be a service that provides a managed Kubernetes cluster running on Microsoft Azure. This makes it easy to deploy and use Kubernetes on Azure.
• Google Kubernetes Engine(GKE): GKE will be a service that provides managed Kubernetes clusters on Google Cloud, simplifying Kubernetes deployment and management.

<API Gateway>

• Kong: It will be an open source API gateway that is flexible and extensible, and can leverage plug-ins to add various functions.
• Apigee: It will be an API management platform provided by Google Cloud that simplifies API management and security measures for microservice systems.
• Tyk: A lightweight, high-performance API gateway, available in open source and enterprise versions.
• AWS API Gateway: It will be an AWS managed API gateway that will allow users to easily publish and manage microservices on AWS.

<load balancer>

• NGINX: NGINX is characterized by high performance and flexibility.
• HAProxy: They will be fast, lightweight load balancers that operate over the TCP and HTTP protocols. They allow for flexible configuration and customization.
• Envoy: A project of the Cloud Native Computing Foundation (CNCF), it will be a load balancer and proxy designed for modern microservices applications.
• Amazon ELB(Elastic Load Balancing): The AWS Managed Load Balancer service will be an easy way to perform load balancing in an AWS environment.

<service discovery>

• consul: Consul will be an open source service discovery and key/value store solution from HashiCorp, Inc. Consul offers advanced features such as multi-data center support and health checks, and in addition to service discovery, it provides distributed configuration management and security features are also provided.
• etcd: etcd will be an open source distributed key-value store developed by CoreOS, widely used in projects such as Kubernetes for service discovery, configuration management, and leader election.

<Monitoring and logging>

• Prometheus: Prometheus is an open source monitoring tool developed as part of the Cloud Native Computing Foundation (CNCF) that can collect, store, and query metrics data, typically combined with Grafana for visualization. Prometheus features a simple and flexible design and is well suited for containerized applications and microservices.
• Grafana: Grafana is an open source tool for visualization that allows metrics taken from Prometheus and other data sources to be visually displayed in dashboards.
• ELK Stack: ELK Stack is a combination of Elasticsearch, Logstash, and Kibana. Kibana is a pipeline tool that visualizes log data stored in Elasticsearch and displays it as a dashboard, and ELK Stack is a tool for centralized logging management and visualization.
• Jaeger: Jaeger is a CNCF tracing project that will provide request tracing between microservices; Jaeger will help visualize the flow of requests and identify bottlenecks and performance issues.
• Zipkin: Zipkin is another tracing tool that will provide a distributed tracing system; Zipkin collects request tracing information and displays a timeline of requests to help understand the request flow of microservices.

<Service Mesh>

• Istio: Istio will be an open source service mesh tool developed by companies such as Google, IBM, and Lyft that runs on orchestration platforms such as Kubernetes to control traffic between services, apply security policies, traffic monitoring, load balancing, and traffic partitioning.
• Linkerd: Linkerd is a project of the Cloud Native Computing Foundation (CNCF) and will be an open source service mesh tool. linkerd provides a lightweight, high-performance mesh that allows microservice applications to network transparent control.
• Consul Connect: Consul Connect is part of HashiCorp’s Consul project, which provides service mesh capabilities along with service discovery.Consul Connect provides a security-focused mesh that encrypts communications between services to Secure.

<Database>

• RDBMS (Relational Database Management System): Traditional relational databases support schema and transaction processing and are suitable when data integrity is important. Examples include PostgreSQL and MySQL, which are microservices that use relational databases to manage data.
• NoSQL databases: NoSQL databases are highly scalable and suitable for processing large amounts of data due to their schema-less and flexible data model. Examples include MongoDB (document-based), Cassandra (column-oriented), and Redis (key/value store). These databases may be used by certain microservices.
• Graph databases: Graph databases are specialized for analyzing network structures and relationships and are suitable for complex queries on related data. Examples include Neo4j, BlazeGraph, Datomic. These are used by certain microservices to manage network structures.
• Object Storage: Object storage is suitable for storing unstructured data (files, images, etc.). Examples include Amazon S3 and Google Cloud Storage, which are used by certain microservices to handle large amounts of unstructured data.

About Microservices Application Cases

Microservices architecture is effective in the following applications

• Large-scale system development: In large-scale system development, multiple development teams need to work together. Microservices architecture allows each service to be developed and deployed independently, facilitating the division of labor and parallel work among development teams. It is also flexible because the technology stack and database for each service can be freely selected.
• High scalability and availability requirements: Microservices allow each service to be scaled individually, so that only the most heavily loaded services can be scaled up. This improves overall system performance and availability, and in the event of a failure, the scope of impact can be limited and failover can be achieved between services.
• Integration of heterogeneous systems: Microservice architectures are well suited for integration with different technology stacks and legacy systems. Since each service is developed independently, new functionality can be added or integrated with external systems without relying on existing systems.
• Deployment of sustained delivery and DevOps: Microservice architecture is well suited for deployment of sustained delivery and DevOps because it allows for independent development and deployment of services. Each service is tested, built, and deployed independently, and automated processes ensure short release cycles.
• Business Flexibility and Innovation: Microservices provide the flexibility and innovation to respond quickly to changing business requirements. Because each service is developed and deployed independently, it is easy to add new functionality and business processes, and can also be a scalable architecture and development methodology for small teams and start-ups.

These specific applications include the following

• Internet shopping applications: services can be created for each different domain, such as customer management, product management, order management, and payment processing. Each service communicates via a RESTful API and is specialized for a particular role. For example, the customer service would be responsible for user registration and authentication, the product service would provide product information, the order service would process and track orders, etc.
• Social media platform: functions such as user management, post management, and feed display can be implemented as microservices. The user service manages user information and authentication, the posting service stores user posting information, the feed service builds user timelines, etc.
• Messaging applications: User management, message management, and notification functions can be implemented as microservices. Each service communicates using asynchronous messaging, with the messaging service managing user messages, the notification service sending notifications to users, and so on.
• Microservice development tools: The microservice architecture itself can also be built with microservices. For example, microservices such as API gateway services, authentication services, and monitoring and tracing services can be combined to build a development foundation for microservice architecture.

Reference Information and Reference Books

Detailed information on microservices, including specific implementations, can be found in “Microservices, Efficient Application Development, and Multi-Agent Systems. Please refer to that as well.

reference book is “Building Microservices: Designing Fine-Grained Systems”

“Microservices with Go: Building scalable and reliable microservices with Go“

“Hands-On Microservices with Rust: Build, test, and deploy scalable and reactive microservices with Rust“

“Microservices with Clojure: Develop event-driven, scalable, and reactive microservices with real-time monitoring”等がある。