# Cloud-Native Computing: A Survey from the Perspective of Services

arXiv: https://arxiv.org/abs/2306.14402 · HTML: https://mlsanity.com/paper/2306.14402/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jun 2023.

## Built on by (most cited first, 6 of 6)

- [Agentic Services Computing](https://mlsanity.com/paper/2509.24380/) (2025)
- [Edge Large AI Models: Revolutionizing 6G Networks](https://mlsanity.com/paper/2505.00321/) (2025)
- [Hierarchical Learning and Computing over Space-Ground Integrated Networks](https://mlsanity.com/paper/2408.14116/) (2024)
- [Scalable and Cost-Efficient ML Inference: Parallel Batch Processing with Serverless Functions](https://mlsanity.com/paper/2502.12017/) (2025)
- [Rethinking Inference Placement for Deep Learning across Edge and Cloud Platforms: A Multi-Objective Optimization Perspective and Future Directions](https://mlsanity.com/paper/2510.22909/) (2025)
- [STLGT: A Scalable Trace-Based Linear Graph Transformer for Tail Latency Prediction in Microservices](https://mlsanity.com/paper/2604.26422/) (2026)

## Abstract (arXiv)

The development of cloud computing delivery models inspires the emergence of cloud-native computing. Cloud-native computing, as the most influential development principle for web applications, has already attracted increasingly more attention in both industry and academia. Despite the momentum in the cloud-native industrial community, a clear research roadmap on this topic is still missing. As a contribution to this knowledge, this paper surveys key issues during the life-cycle of cloud-native applications, from the perspective of services. Specifically, we elaborate the research domains by decoupling the life-cycle of cloud-native applications into four states: building, orchestration, operate, and maintenance. We also discuss the fundamental necessities and summarize the key performance metrics that play critical roles during the development and management of cloud-native applications. We highlight the key implications and limitations of existing works in each state. The challenges, future directions, and research opportunities are also discussed.