How to Address Application Performance in Agile Scrum Teams

Given the nature SCRUM, two quality characteristics that takes back seat and considered as implicit are performance and security. I shall discuss the approach on how to address application performance while working with agile SCRUM teams.

Before I go and list down the tips and techniques, let’s understand some of the constraints:

  • Not all developers working in SCRUM teams are very familiar with application performance aspects
  • It may get difficult to do performance testing at the end of each sprint.
  • It may get difficult to articulate performance related user stories in each sprint.

Given above constraints, it becomes much more important to address performance related issues in SCRUM model. Following is a proposed model which I have found to work and take care of application performance issues on ongoing basis:

  • Create a centralized performance team consisting of appropriate number of performance engineers/testers.
  • Have the performance team work on SCRUM model where performance related stories such as performance testing are entered in their sprint backlogs by different SCRUM teams.
  • The performance stories such as performance testing can be dealt during integration testing phase or so after all the sprints are done and the release readiness is going on.
Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

Share
Published by
Ajitesh Kumar

Recent Posts

Agentic Reasoning Design Patterns in AI: Examples

In recent years, artificial intelligence (AI) has evolved to include more sophisticated and capable agents,…

1 month ago

LLMs for Adaptive Learning & Personalized Education

Adaptive learning helps in tailoring learning experiences to fit the unique needs of each student.…

2 months ago

Sparse Mixture of Experts (MoE) Models: Examples

With the increasing demand for more powerful machine learning (ML) systems that can handle diverse…

2 months ago

Anxiety Disorder Detection & Machine Learning Techniques

Anxiety is a common mental health condition that affects millions of people around the world.…

2 months ago

Confounder Features & Machine Learning Models: Examples

In machine learning, confounder features or variables can significantly affect the accuracy and validity of…

2 months ago

Credit Card Fraud Detection & Machine Learning

Last updated: 26 Sept, 2024 Credit card fraud detection is a major concern for credit…

2 months ago