DevOps

DevOps Maturity Model – Telstra DevOps Implementation

In this post, you will get a quick glimpse of how Telstra successfully rolled out DevOps across the entire organization (170 teams). The details have been taken from this post. You could use the details given below to lay out the maturity model for DevOps implementation in your organization.

The following is the DevOps Maturity Model which Telstra team looks to have worked upon:

Here are the key aspects of the DevOps practice (implementation) vis-a-vis maturity model:

  • Ad-hoc implementations
    • Teams across the organization doing ad-hoc implementations
    • Different tools & framework used across different teams
    • Different processes followed
    • Teams do not seem to have a proper understanding of what is DevOps, benefits of DevOps etc.
  • Proof-of-concept implementations
    • DevOps implementation planned
    • Tools & processes chosen
    • 3-4 teams chosen
    • Teams mentored
    • Implementation is done and lessons learned
  • Org-wide Adoption
    • Mentoring sessions across the organization
    • DevOps rolled out for all the teams
    • DevOps implementations governed & reported
  • Sustained & Repeatable DevOps
    • Sustained DevOps implementation across different teams
    • DevOps Governance
    • Tracking & reporting
  • Optimized DevOps
    • Lessons learned using continuous feedback is incorporated back to improve the DevOps implementations
    • The appropriate mix of tools & frameworks used for optimized outcomes
    • Development processes updated to optimize DevOps outcomes

References

Summary

In this post, you learned about a sample DevOps maturity model which looks to have been implemented at Telstra. The DevOps implementation faces several challenges such as doing POC, training & mentoring, convincing executive management, making sustained & repeatable DevOps. Most importantly, there must be put a governance framework to monitor/track ongoing DevOps implementation across the organization to achieve sustainability and repeatability.

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
Tags: devops

Recent Posts

Retrieval Augmented Generation (RAG) & LLM: Examples

Last updated: 25th Jan, 2025 Have you ever wondered how to seamlessly integrate the vast…

1 month ago

How to Setup MEAN App with LangChain.js

Hey there! As I venture into building agentic MEAN apps with LangChain.js, I wanted to…

2 months ago

Build AI Chatbots for SAAS Using LLMs, RAG, Multi-Agent Frameworks

Software-as-a-Service (SaaS) providers have long relied on traditional chatbot solutions like AWS Lex and Google…

2 months ago

Creating a RAG Application Using LangGraph: Example Code

Retrieval-Augmented Generation (RAG) is an innovative generative AI method that combines retrieval-based search with large…

2 months ago

Building a RAG Application with LangChain: Example Code

The combination of Retrieval-Augmented Generation (RAG) and powerful language models enables the development of sophisticated…

2 months ago

Building an OpenAI Chatbot with LangChain

Have you ever wondered how to use OpenAI APIs to create custom chatbots? With advancements…

2 months ago