Microservices and Efficient Application Development and Multi-Agent Systems
From MicroService pattern “Code Explained for Practical System Design.”
The word “micro” has a certain ring to it that makes an engineer’s spirit of inquiry tingle. And “service,” which obviously means software component. If you are a software engineer, it is obvious that you are interested in software componentization methods. In addition, even if you are not an engineer or not familiar with English, it is obvious that “microservice” means a small service.
However, this easy-to-understand name is also a source of confusion and misunderstanding. When explaining the technical details of microservices, one of the most common questions is “How small is small? is a standard question asked during technical explanations of microservices. Chris Richardson, author of “The Microservices Pattern: A Code Guide for Practical System Design,” proposes the following: “The size of the service is not very important,” and “The problem with naming microservices is that the ‘micro’ is so prominent. The problem with naming microservices is that the “micro” stands out.
The goal of microservices is to develop, release, and maintain applications quickly and frequently. To achieve this, the smaller the target domain for system development, the better, so analytical design methods such as domain-driven design are used to divide the domain. In addition, the smaller the team responsible for development and operation, the easier it is to make quick decisions autonomously. Therefore, team formation and development and operation processes are devised with reference to Conway’s Law and agile methods.
As a result, the size of the “service,” which is the software component of the deliverable, tends to be smaller. Small services” are only the result, not the goal. In some cases, even microservices may be operated as “large services. In other words, Chris Richardson says that it is not good to start from the appearance of a “small service.
So what are microservices? Chris Richardson says, “It is the ability to make an application function as multiple services. It is an architectural style for functionally partitioning an application into multiple services. The “architectural style” is not only the structural design (architecture), but also the development and operation methods, organizational structure and management, and all other aspects of the development and operation of the structure.
It is doubtful that implementing a small service by focusing only on software component design in a waterfall project is really effective for speedy and high-frequency application development, release, and maintenance. To imitate only the design and call it microservices is to misunderstand the meaning of microservices. It is important to think of microservices as an architectural style and apply the most appropriate methods and technologies for analysis, design, development, operations, organizational management, etc.
Chris Richardson’s website “Microservice Architecture” collects and organizes design patterns related to microservices, and publishes them. In addition to a summary of microservice architecture styles for microservices based on these patterns, “Microservice with Clojure” by Anuj Kumar describes the implementation of microservices using Clojure, a functional language. Anuj Kumar describes the implementation of microservices using Clojure, a functional language.
The details are described below.
Theory and Implementations
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. This section provides an overview of the elements that make up these microservices.
Unity is an integrated development environment (IDE) for game and application development developed by Unity Technologies and widely used in various fields such as games, VR, AR, and simulations. This paper describes the integration of Unity with artificial intelligence systems such as CMS, chatbot, ES, machine learning, and natural language processing.
Here you will learn common patterns and practices and how to apply them using the Clojure programming language. You will learn the basic concepts of architectural design and RESTful communication, and be introduced to patterns that provide manageable code that scales during development and in production. It also provides examples of how to put these concepts and patterns into practice with Clojure.
Well-designed monolithic architectures have been key to the success of many software applications. However, microservice-based applications are gaining popularity in the Internet age due to their inherent characteristics of being autonomous and flexible, their ability to scale independently, and their short release cycles.
The ideal enterprise system would be tightly integrated and provide all business functions as a single unit optimized for a particular technology stack and hardware. Such monolithic systems often become more complex over time and difficult to understand as a single unit by a single team. Domain-driven design advocates decomposing such systems into smaller modular components and assigning them to teams that focus on a single business capability in a limited context. Once decomposed, all such components become part of an automated continuous integration (CI) process, avoiding fragmentation. Because these components are built in isolation and often have their own data models and schemas, there must be explicit contracts for interacting with the components to coordinate various business activities.
Here, the term domain-driven design was first coined by Eric J. Evans in 2003 as the title of his book Evans describes the importance of bounded context and continuous integration as the foundation of microservice architecture Evans explains the importance of bounded context and continuous integration as the foundation of microservice architecture.
REST stands for representational state transfer and defines an architectural style of distributed hypermedia systems. applications that support REST do not store any information about the client’s state on the server side. Such applications require the client to maintain state itself and transfer state between the client and server using a REST-style implementation, such as an HTTP API exposed by the application. The client and server can be synchronized by querying the server for the latest state and expressing the same state on the client side.
Pedestal is an API-first Clojure framework, a data-driven extensible framework that provides a set of libraries for building reliable concurrent services with dynamic properties, implemented using protocols to reduce coupling between components.
In this article, we will discuss Datomic, a next-generation database for microservices, which is the foundation for storing and retrieving data reliably for data-oriented applications such as microserpices (data-oriented applications are applications where the volume, complexity, and change of data is an issue). Datomic is a library written in Clojure, a cloud service provided by AWS.
Microservices need to be deployed in isolation and monitored for usage. Monitoring current workloads and processing times can also help determine when to scale them up and when to scale them down. Another important aspect of a microservice-based architecture will be security. One way to secure microservices would be to ensure that each service has its own authentication and authorization module. But this approach quickly becomes problematic. Because each microservice is deployed in isolation, it becomes incredibly difficult to agree on common criteria for authenticating users. Also, in this case, ownership of users and their roles would be distributed among the services. This chapter addresses these issues and describes solutions for securing, monitoring, and extending microservice-based applications.
From “Microservice with Clojure. In this article, we will discuss the use of ElasticStash for monitoring microservice systems. The monitoring system described here can be widely applied to systems other than microservice systems; please refer to “Search Tool Elasticsearch – Startup Procedure” for details.
Microservices need to be packaged as self-contained artifacts that can be replicated and deployed with a single command. The service also needs to have a short startup time and be lightweight so that it can be up and running within seconds. Containers can be deployed quickly due to their inherent implementation compared to setting up a bare-metal machine with a host OS and the necessary dependencies. In addition, packaging microservices within containers allows for a faster and more automated transition from development to production. Therefore, it is recommended that microservices be packaged in containers.
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