Gartner Research

Integrate DevOps and Artificial Intelligence to Accelerate IT Solution Delivery and Business Value

Published: 22 August 2017

ID: G00327076

Analyst(s): Carlton Sapp

Summary

DevOps and AI have a symbiotic relationship. Integration of DevOps and AI will play a significant role in shaping how technical professionals manage and deploy systems. This report assesses the current state of AI combined with DevOps, and explores the strengths and weaknesses of this integration.

Table Of Contents

Analysis

  • The Role of AI in DevOps
    • Using AI to Improve DevOps Automation
    • Using AI in Continuous Integration, Delivery and Deployment
    • Using AI in Quality Control and Continuous Improvement
    • Using AI for Coordination and Collaboration Among Teams
    • Deploying AI in Software Engineering Tasks
  • The Role of DevOps in AI
    • Enforcing a Consistent Approach to Building, Evaluating and Deploying AI/ML Services
    • Extending the ML Model Development Life Cycle With a Highly Iterative Process
    • Enabling Continuous Deployment for ML Models
    • Supporting Continuous Monitoring and Auditing of Deployed ML Models
    • Promoting Team Integration and Collaboration to Improve AI Delivery
  • Strengths
  • Weaknesses

Guidance

  • Guidance for the DevOps Community
    • Begin Investing in AI Capabilities and AI Training Now, but Start Small
    • Don't Try to Develop or Code AI/ML Algorithms From the Ground Up
    • Look to Use AI Services for Decision Support, in Addition to Automation
  • Guidance for the AI Community
    • Use DevOps Practices to Focus on Reducing the Current Timelines Around Building and Deploying AI Models and Services
    • Use DevOps Principles to Focus More on Operationalizing AI Tools and Services
    • Use an Incremental MDLC to Establish a Comprehensive Process for Deploying AI Technologies

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