мікросервісна архітектура

Collaborative filtering algorithms for a job recommendation system built with a microservice architecture

This article presents the development of a recommender system for recruiting personnel and vacancies to improve the efficiency of the hiring process. The proposed system has integrated collaborative and hybrid filtering methods to provide personalized job recommendations. Collaborative filtering model has analyzed historical data, identifying patterns by detecting connections between user information and job content.

Evaluating small quantized language models on apple silicon

This study examines the capabilities and limitations of small, 4-bit quantized language models that run locally on Apple Silicon. Four models have been benchmarked on a dataset of natural language prompts, with runtime metrics including inference time, memory usage, and token throughput, as well as output behavior. The study provides an empirical assessment of the feasibility of deploying language models on resource-constrained devices.

Methodology of Implementation of Information Systems Using Micro Interfaces to Increase the Quality and Speed of Their Development

Microservices represent a software development approach, a variation of service-oriented architecture, that structures an application as a collection of loosely connected services. The aim of this work is to explore the design and implementation methodology for information systems using micro-interfaces to enhance development quality and speed while simplifying their usage. This work proposes a method for transitioning from a monolithic software architecture to a microservice architecture.

Serverless Ai Agents in the Cloud

Integrating AI agents within serverless architectures offers a modern approach to deploying and executing intelligent applications. Leveraging the advantages of serverless computing, AI agents can dynamically respond to varying workloads without the overhead of managing the underlying infrastructure. This article explores the concept of scalable serverless AI agents in the cloud, detailing their architecture, benefits and drawbacks, challenges, and real-world applications. The paper provides advantages and drawbacks of the serverless approach.

Distributed Transactions in Microservice Architecture: Informed Decision-making Strategies

The emergence of microservice architecture has revolutionized software development practices by decentralizing components, facilitating scalability, and enabling agility in system design and deployment. There are some benefits of incorporating microservices instead of a single server, however, distributed components introduce extra constraints and complexities in maintaining data consistency as well. As microservices interact independently, coordinating data updates across multiple services becomes challenging, particularly in scenarios where transactional integrity is required.