Open in app

Sign In

Write

Sign In

Adarsh Shah
Adarsh Shah

119 Followers

Home

About

Published in

ITNEXT

·Pinned

Principles, Patterns, and Practices for Effective Infrastructure as Code

Deliver Infrastructure and Software running on it Rapidly and Reliably at Scale — Table of contents What is Infrastructure as Code Key Principles - Idempotency - Immutability Patterns and Practices - Everything in Source Control - Modularize and Version - Documentation - Testing - Security and Compliance - Automate Execution from a Shared Environment — Infrastructure as Code Pipeline — GitOps Conclusion

DevOps

11 min read

Principles, Patterns, and Practices for Effective Infrastructure as Code
Principles, Patterns, and Practices for Effective Infrastructure as Code
DevOps

11 min read


Published in

ITNEXT

·Nov 17, 2020

Platform Engineering: Challenges and Solutions

Based on my experience leading Platform Engineering initiative at various organizations — I talked about what Platform Engineering(PE) is, when is it useful, and the challenges I have seen working with it in my previous article. In this article, we will go through solutions that have worked for my teams and me in resolving those challenges. …

Automation

11 min read

Platform Engineering: Challenges and Solutions
Platform Engineering: Challenges and Solutions
Automation

11 min read


Published in

ITNEXT

·Oct 15, 2020

Platform Engineering: Using it to Gain Competitive Advantage

What is it, When is it useful, and Challenges with it — Table of contents What is Platform Engineering? Platform Engineering Team Who are the customers? When is it useful? Challenges with Platform Engineering Conclusion Caution: Platform is a widely used term to define various types of platforms, so be careful about using it. At one place, we chose not to use the term platform…

Platform Engineering

6 min read

Platform Engineering: Using it to Gain Competitive Advantage
Platform Engineering: Using it to Gain Competitive Advantage
Platform Engineering

6 min read


Published in

Towards Data Science

·Sep 23, 2020

Continuous Delivery for Machine Learning Systems

Deploying Machine Learning Systems to Production safely and quickly in a sustainable way — Table of contents What is Continuous Delivery? Continuous Integration Continuous Delivery vs. Continuous Deployment Machine Learning Workflow How does Continuous Delivery help with ML challenges? Data Management - Automated Data Pipeline Experimentation - Training Code - Training Process Production Deployment - Application Code Bringing it all together People Conclusion

Machine Learning

9 min read

Continuous Delivery for Machine Learning Systems
Continuous Delivery for Machine Learning Systems
Machine Learning

9 min read


Published in

Towards Data Science

·Jun 21, 2020

Challenges Deploying Machine Learning Models to Production

MLOps: DevOps for Machine Learning — Table of contents Traditional Software Development vs Machine Learning Machine Learning Workflow Stage #1: Data Management - Large Data Size - High Quality - Data Versioning - Location - Security & Compliance Stage #2: Experimentation - Constant Research and Experimentation Workflow - Tracking Experiments - Code Quality - Training Time & Troubleshooting - Model Accuracy Evaluation - Retraining - Infrastructure Requirements Stage #3: Production Deployment - Offline/Online Prediction - Model Degradation Conclusion…

Machine Learning

7 min read

Challenges Deploying Machine Learning Models to Production
Challenges Deploying Machine Learning Models to Production
Machine Learning

7 min read

Adarsh Shah

Adarsh Shah

119 Followers

Engineering Leader, Independent Consultant, Coach, Public Speaker, Hands-on Architect | Website: shahadarsh.com

Following
  • Pavan Belagatti

    Pavan Belagatti

  • Gary A. Stafford

    Gary A. Stafford

  • Adrian Hornsby

    Adrian Hornsby

  • Kent Beck

    Kent Beck

  • Jez Humble

    Jez Humble

See all (14)

Help

Status

Writers

Blog

Careers

Privacy

Terms

About

Text to speech

Teams