# Microservices: yesterday, today, and tomorrow

arXiv: https://arxiv.org/abs/1606.04036 · HTML: https://mlsanity.com/paper/1606.04036/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2016.

## Built on by (most cited first, 22 of 22)

- [Deep Learning for Time Series Anomaly Detection: A Survey](https://mlsanity.com/paper/2211.05244/) (2022)
- [AutoEDA: Enabling EDA Flow Automation through Microservice-Based LLM Agents](https://mlsanity.com/paper/2508.01012/) (2025)
- [Optimizing Travel Itineraries with AI Algorithms in a Microservices Architecture: Balancing Cost, Time, Preferences, and Sustainability](https://mlsanity.com/paper/2410.17943/) (2024)
- [Reinforced Workload Distribution Fairness](https://mlsanity.com/paper/2111.00008/) (2021)
- [Novel Architecture for Distributed Travel Data Integration and Service Provision Using Microservices](https://mlsanity.com/paper/2410.24174/) (2024)
- [Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies](https://mlsanity.com/paper/2103.05245/) (2021)
- [Disease Progression Modeling Workbench 360](https://mlsanity.com/paper/2106.13265/) (2021)
- [Multi-Agent Reinforcement Learning for Network Load Balancing in Data Center](https://mlsanity.com/paper/2201.11727/) (2022)
- [Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game](https://mlsanity.com/paper/2206.01451/) (2022)
- [Software Engineering for Collective Cyber-Physical Ecosystems](https://mlsanity.com/paper/2406.04780/) (2024)
- [AOI: Context-Aware Multi-Agent Operations via Dynamic Scheduling and Hierarchical Memory Compression](https://mlsanity.com/paper/2512.13956/) (2025)
- [AI Techniques in the Microservices Life-Cycle: A Systematic Mapping Study](https://mlsanity.com/paper/2305.16092/) (2023)
- [Machine learning-based cloud resource allocation algorithms: a comprehensive comparative review](https://mlsanity.com/paper/2511.11603/) (2025)
- [Can AI Agents Generate Microservices? How Far are We?](https://mlsanity.com/paper/2603.09004/) (2026)
- [GALA: Graph-Augmented LLM Agents for Root Cause Analysis and Incident Response in Microservices](https://mlsanity.com/paper/2608.08968/) (2026)
- [Towards Intelligent Load Balancing in Data Centers](https://mlsanity.com/paper/2110.15788/) (2021)
- [A Document-based Knowledge Discovery with Microservices Architecture](https://mlsanity.com/paper/2407.00053/) (2024)
- [Moving From Monolithic To Microservices Architecture for Multi-Agent Systems](https://mlsanity.com/paper/2505.07838/) (2025)
- [Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation](https://mlsanity.com/paper/2508.01635/) (2025)
- [A Human-Centred Architecture for Large Language Models-Cognitive Assistants in Manufacturing within Quality Management Systems](https://mlsanity.com/paper/2603.16325/) (2026)
- [LogNEO: A GPT-Neo Reinforcement Learning Framework for Accurate Real-Time Log Anomaly Detection](https://mlsanity.com/paper/2606.08153/) (2026)
- [From Textual Requirements to Microservice Architectures - A Comprehensive Evaluation of LLM-Based Design Synthesis](https://mlsanity.com/paper/2607.28307/) (2026)

## Abstract (arXiv)

Microservices is an architectural style inspired by service-oriented computing that has recently started gaining popularity. Before presenting the current state-of-the-art in the field, this chapter reviews the history of software architecture, the reasons that led to the diffusion of objects and services first, and microservices later. Finally, open problems and future challenges are introduced. This survey primarily addresses newcomers to the discipline, while offering an academic viewpoint on the topic. In addition, we investigate some practical issues and point out some potential solutions.