Exploring Micro Frontends

https://renatocf.xyz/amp25-slides

2025

Renato Cordeiro Ferreira

Institute of Mathematics and Statistics (IME)
University of São Paulo (USP)  Brazil

Jheronimus Academy of Data Science (JADS)
Technical University of Eindhoven (TUe) / Tilburg University (TiU)  – The Netherlands

Paper

Slides

A Case Study Application in E-Commerce

Former Principal ML Engineer at Elo7 (BR)

4 years of industry experience designing, building, and operating ML products with multidisciplinary teams

B.Sc. and M.Sc. at University of São Paulo (BR)

Theoretical and practical experience with Machine Learning and Software Engineering

Scientific Programmer at JADS (NL)

Currently participating in the MARIT-D European project, using ML techniques for more secure seas

Ph.D. candidate at USP + JADS (BR + NL)

Research about SE4AI, in particular about MLOps and the software architecture of ML-Enabled Systems

Renato Cordeiro Ferreira

https://renatocf.xyz/contacts

Renato Cordeiro Ferreira

Luiz Fernando Corte Real

Ricardo Kojo

renatocf@ime.usp.br

sr.saude@alumni.usp.br

ricardo.kojo@alumni.usp.br

Thatiane de Oliveira Rosa

Alfredo Goldman

thatiane@ifto.edu.br

gold@ime.usp.br

Our paper provides insights into when
the adoption of micro frontends
may be worthwhile,
particularly in an industry context,
considering that research
in this area is still evolving

Research Questions

What are the motivations and challenges involved in adopting a micro frontend architecture in the studied company, which already uses microservices?

What are the perceived benefits and drawbacks reported by developers involved in the migration from a monolithic architecture to micro frontends?

RQ1

RQ2

Journey to

Micro Frontends

Back + Front

(Java)

2012

Front

(Node.js)

2016

Aquarelle

Marketplace

The Aquarelle project, built on Node.js, was introduced to implement a reactive chat feature capable of displaying dynamic backend data such as order status and user actions

Backend for Frontend (BFF) pattern handles (1) internal routing, (2) orchestrates data from microservices, and (3) forwards it to a template rendered by an open-source library developed by the Company

1

2

3

Other services

(Java, Python, ...)

2018

Front

(Node.js)

2016

Back + Front

(Java)

2012

API Gateway
(Go)

2021

Survey with
Developers

  • Semi-open questionnaire
  • Employees involved in frontend projects
    • Frontend developers
    • Technical Leads
    • Engineering managers
    • Software architects

Methodology

  • 1 month duration
  • 19 questions (15 open-ended + 4 multiple-choice)
  • Full questionnaire available at Zenodo

8 participants
7 men / 1 women

 

5 participants
>10 years of experience

Many unknowns

Distributed testing expected to be harder

Positives

  • New developers

Negatives

  • Evolution depends on extracting services from the monolith
  • Faster deployments
  • Simpler implementation
  • New technologies
  • More transparency in the
    project understanding
  • Data conversion affects speed
    (formerly done by the monolith)
  • Onboarding can be harder
    (because of complexity)

Trade-offs of the new architecture

Research Questions

What are the motivations and challenges involved in adopting a micro frontend architecture in the studied company, which already uses microservices?

What are the perceived benefits and drawbacks reported by developers involved in the migration from a monolithic architecture to micro frontends?

RQ1

RQ2

While not the only possible solution,
micro frontends turned out to be
the most convenient
within that specific context

Exploring Micro Frontends

https://renatocf.xyz/amp25-slides

2025

Renato Cordeiro Ferreira

Institute of Mathematics and Statistics (IME)
University of São Paulo (USP)  Brazil

Jheronimus Academy of Data Science (JADS)
Technical University of Eindhoven (TUe) / Tilburg University (TiU)  – The Netherlands

Paper

Slides

A Case Study Application in E-Commerce

Research Track - SummerSOC 2025

MLOps with Microservices:
A Case Study on the Maritime Domain

https://renatocf.xyz/ssoc25-paper

Doctoral Symposium - CAIN 2025

A Metrics-Oriented Architectural Model
to Characterize Complexity on
Machine Learning-Enabled Systems

https://renatocf.xyz/cain25-paper