Step-by-Step Guide: Getting Started with AWS DevOps and AI

   AWS DevOps with AI Course in Hyderabad – Hamsini Tech Solutions

Hamsini Tech Solutions offers one of the best AWS DevOps with AI courses in Hyderabad, designed for graduates, postgraduates, working professionals, and career switchers. The program blends hands-on learning with a real-time internship, ensuring you become job-ready in a short period.

Our expert-led training goes beyond just theory. With live projects guided by certified AWS DevOps professionals, you gain practical knowledge of automation, CI/CD, cloud monitoring, and AI-driven DevOps practices. Even if you are from a non-IT background, our structured curriculum makes it easy to transition into cloud and DevOps roles.

The course also includes labs, real-time projects, mock interviews, and resume-building sessions to increase placement success and industry readiness.

Why Choose Us?

Live Instructor-Led Training

Real-Time Internship Projects

Resume & Interview Preparation

Placement Assistance

Career Transition Support

By joining Hamsini Tech Solutions, you can unlock a rewarding career in AWS DevOps with AI. Our alumni have successfully secured roles in top companies such as TCS, Infosys, Deloitte, Accenture, and Capgemini.

Note: AWS DevOps integrates with AI to automate monitoring, deployment, and error handling, making cloud applications more scalable and intelligent

Step-by-Step Guide: Getting Started with AWS DevOps and AI

1) Set your goal: Pick a simple app (e.g., REST API) and define KPIs—deploy time, rollback time, error rate.

2) Create AWS foundation: Open an AWS account, enable MFA, set up IAM users/roles with least-privilege, and create separate Dev/Test/Prod accounts.

3) Version control: Use Git with GitHub or CodeCommit; adopt trunk or GitFlow and protect main with PR reviews.

4) CI/CD pipeline: Build with CodePipeline + CodeBuild + CodeDeploy. Run unit tests, build artifacts, and enable blue/green or canary deployments.

5) Infrastructure as Code: Provision everything via CloudFormation or Terraform; store templates in Git and use parameterized, reusable modules.

6) Containerize: Dockerize the app; push images to ECR and run on ECS Fargate or EKS. Add autoscaling policies.

7) Observability: Use CloudWatch metrics/logs, X-Ray traces, alarms, and dashboards; tag resources for cost and ownership.

8) Security & cost: Encrypt with KMS, scan images, enforce guardrails with AWS Config and IAM SCPs; watch Cost Explorer and Budgets.

9) Add AI for DevOps: Turn on CloudWatch Anomaly Detection, use Amazon DevOps Guru for predictive insights, CodeWhisperer for developer productivity, and (optionally) SageMaker/Bedrock to forecast incidents or capacity.

10) Practice project: Ship a microservice through Dev→Prod with automated tests, health checks, and auto-rollback.

For guided learning, consider AWS DevOps Training in Hyderabad at the Best AWS DevOps Institute. Enroll in an AWS DevOps with AI Course—perfect as AWS DevOps with AI for Students—and unlock AWS DevOps Jobs for Freshers.

Read More

How Artificial Intelligence is Changing DevOps on AWS

Top 10 Reasons to Learn AWS DevOps with AI in 2025

What is AWS DevOps? – A Beginner’s Guide for Students

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