PG Diploma

★★★★★

(1,240 ratings) 8,500+ Student

PG Master Diploma in Enterprise Platform Engineering & IT Infrastructure Management

A comprehensive 9-course PG Master Diploma covering Red Hat Linux Administration (RHCSA & RHCE with Ansible), Site Reliability Engineering (SRE), AIOps, AWS Solution Architect, end-to-end DevOps Engineering (Git, Jenkins, Docker, Kubernetes, Terraform, Ansible, GitOps), GenAI & Agentic AI for infrastructure automation, Multi-Cloud Kubernetes (AKS, EKS & GKE), MLOps, and Python Scripting for DevOps & MLOps. 400–430 hours of 90% practical, hands-on training with real-time enterprise scenarios, building job-ready Linux, Cloud, SRE, AIOps, DevOps, AI and MLOps skills through real-world infrastructure projects and placement-oriented training.

Radical Technologies

8,500+ English 9 Courses · Linux, Cloud, DevOps, AI & MLOps

Online / Classroom

PG Master Diploma — Enterprise Platform Engineering

Cloud, DevOps, SRE & AIOps Programme

Duration 400-430 Hours

Batch Type Weekdays / Weekends

Mode of Training Classroom / Online / Corporate

Locations Pune, Bangalore, Kochi

Language English

Certification Globally Recognized PG Diploma

Tools you'll master

Linux Bash Python VS Code Git GitHub Ansible Docker Jenkins Amazon EC2 Amazon S3 Amazon VPC AWS IAM CloudWatch Prometheus Grafana ELK Stack Terraform Kubernetes Kafka Pandas/NumPy Moogsoft Dynatrace Splunk ITSI AKS EKS GKE Helm ArgoCD Istio Packer HashiCorp Vault Maven SonarQube Nexus Scikit-learn DVC boto3 pytest LangChain OpenAI GPT

Next batch: 10/08/2026 · Online

Call Now

100% placement assistance

Why This Course?

Industry-oriented curriculum for enterprise Linux, Cloud, SRE & AIOps careers

Covers RHCSA, RHCE (Ansible), Python Scripting, AWS Fundamentals, DevOps Basics, Site Reliability Engineering (SRE) and AIOps Engineering

Combo pack of RHEL 8, RHEL 9 & RHEL 10 — SA1, SA2 & SA3 topics covered in detail, basic to advanced

250+ real-time scenarios across L1 (Basic), L2 (Intermediate) and L3 (Advanced) levels

90% Practical, 10% Theory — trainers from real-time industry

Complete RHCSA & RHCE exam preparation with our Individual Exam Delivery System (KOALA) — appear for the Global Certification exam at your convenience, no waiting for a Red Hat schedule

Gain 3–4+ years of experienced Linux System Administrator knowledge — work confidently from Day 1

RHCSA-certified candidates are placed with our clients at a minimum salary of ₹4.5 Lakhs per annum — none of them stay jobless

Master Site Reliability Engineering — SLIs/SLOs/SLAs, error budgets, observability (Prometheus, Grafana, ELK), Kubernetes, Terraform and incident management

Master AIOps Engineering — AI-driven monitoring, Machine Learning-based anomaly detection, and self-healing automation for enterprise IT operations

Build enterprise-ready Linux, Cloud, DevOps, SRE and AIOps automation skills through real-world troubleshooting assignments, configuration tasks and infrastructure projects

Prepare for high-demand Linux Administrator, DevOps Engineer, SRE, AIOps Engineer and Cloud roles

Placement-oriented training with interview preparation

Prerequisites

Basic Computer Knowledge

Logical Thinking

Basic Networking Concepts (Recommended)

Basic Operating System Knowledge

No Prior Cloud Experience Required

Suitable for Freshers & Working Professionals

Programme Overview

9 courses covering Red Hat Linux (RHCSA & RHCE), Site Reliability Engineering (SRE), AIOps, AWS Solution Architect, DevOps Engineering, GenAI & Agentic AI, Multi-Cloud Kubernetes and MLOps — a single, progressive learning arc for enterprise Linux, Cloud, DevOps, AI & MLOps careers.

400-430

Training Hours

Courses

114

Total Modules

4.6★

Average Rating

50K+

Students Trained

RHCSA — Core Linux Administration

Master Linux fundamentals, users & permissions, process management, package management, storage/LVM, networking, firewall and SELinux — RH124 + RH134.

Linux RHCSA LVM SELinux

RHCE — Automation with Ansible

Automate infrastructure using Ansible — playbooks, roles, variables, conditionals and handlers — RH294.

Ansible RHCE Automation

Python Scripting for Linux Admins

Automate day-to-day system administration tasks — disk monitoring, log analysis and backup automation — using Python.

Python Scripting Automation

AWS Cloud Fundamentals

Work hands-on with Amazon EC2, S3, VPC and IAM, and deploy a Linux web server on AWS cloud.

AWS EC2 S3 IAM

DevOps Basics for Linux Admins

Learn Git version control, Docker containerization and CI/CD pipeline concepts with Jenkins.

Git Docker Jenkins

SRE — Site Reliability Engineering

Master SLIs/SLOs/SLAs and error budgets, Kubernetes, Terraform, Prometheus/Grafana/ELK observability, and incident management with RCA.

SRE Kubernetes Terraform Observability

AIOps — AI for IT Operations

Apply Machine Learning to IT operations — anomaly detection, predictive analytics, AI-driven root cause analysis and self-healing automation.

AIOps Machine Learning Automation

AWS Solution Architect

Master advanced VPC/networking, EC2, storage & databases, serverless & containers, IaC and HA/DR — job-ready enterprise cloud architecture skills.

AWS VPC Serverless IaC

DevOps Engineering

End-to-end DevOps toolchain — Git, Maven, Jenkins CI/CD, Docker, Kubernetes, Terraform, Ansible, GitOps with ArgoCD, plus Istio, Packer, ELK and Vault.

Jenkins Kubernetes GitOps

GenAI & Agentic AI

Build AI agents for infrastructure — prompt engineering, LangChain, AI-generated Terraform/Kubernetes configs, and autonomous DevOps assistants.

GenAI LLMs AI Agents

Kubernetes Multi-Cloud

Run production Kubernetes across AKS, EKS and GKE — networking, IAM/RBAC, Helm, GitOps, observability and multi-cloud DR strategies.

AKS EKS GKE

MLOps for Infrastructure Engineers

Deploy and operate ML systems in production — model serving on Kubernetes, ML CI/CD, drift detection and automated retraining.

MLOps Kubernetes CI/CD

Who is this programme for?

Whether you're a fresher, a Linux/System Administrator, a developer or already working in IT — this programme is built to take you into a high-demand Cloud, DevOps, SRE, AIOps or Platform Engineering role.

Students & Freshers

Build strong Linux, Cloud & DevOps foundations, gain practical enterprise experience, and improve employability from day one.

Linux Administrators

Earn your RHCSA & RHCE, learn Ansible automation, and transition confidently into DevOps and Cloud roles.

System Administrators

Modernize your infrastructure management skills, learn AWS cloud fundamentals, and automate daily operations with Python and Ansible.

Developers

Learn Git workflows, Docker containerization, and CI/CD pipeline basics with Jenkins.

Cloud Engineers

Build a strong AWS foundation — EC2, S3, VPC, IAM — and pair it with Linux and DevOps automation skills.

Working Professionals

Upskill with globally recognized RHCSA & RHCE certifications, accelerate career growth, and prepare for senior infrastructure roles.

Course Curriculum

400–430 total hours

9 courses • 114 modules • 90% practical, hands-on training

Course 01 of 09 28 Modules RHCSA + RHCE + Python + AWS + DevOps

Red Hat Linux Training

Combo pack of RHEL 8, RHEL 9 & RHEL 10 — Linux Administration, Automation, Scripting, Cloud Fundamentals and DevOps Basics.

Course Content

RHCSA — Red Hat Certified System Administrator RH124 + RH134

Focus: Core Linux Administration Skills

— Module 1: Linux Basics and Command Line Tools

Topics:

Linux architecture
File system hierarchy
Command-line usage
Text processing tools
File compression and archiving
Input/output redirection

Hands-On / Demo

› Lab: Navigate the file system
› Lab: Search files
› Lab: Compress and extract archives
› Assignment: Find files larger than 200MB and archive them into a backup file
› Job Scenario: A developer accidentally deleted logs — recover compressed backup files from archive

— Module 2: User and Group Administration

Topics:

Creating users
Managing groups
Password policies
Default user settings
Privilege delegation using sudo

Hands-On / Demo

› Lab: Create users
› Lab: Assign groups
› Lab: Configure sudo access
› Assignment: Create users for HR, Finance, and IT departments
› Job Scenario: A developer needs temporary administrative access — configure secure sudo access

— Module 3: File Permissions and Access Control

Topics:

File permissions
Ownership
Special permissions (SUID, SGID, Sticky bit)
Access Control Lists (ACL)

Hands-On / Demo

› Lab: Configure permissions for shared directories
› Lab: Implement ACL rules
› Assignment: Create a shared project directory accessible by multiple teams
› Job Scenario: Allow read access to one user without changing file ownership

— Module 4: Process Management

Topics:

Process monitoring
Process lifecycle
Background jobs
Resource usage monitoring
Commands: ps, top, kill, nice, renice

Hands-On / Demo

› Lab: Identify high CPU processes
› Lab: Manage background jobs
› Assignment: Write a command sequence to identify the top memory-consuming process
› Job Scenario: Production server is slow — find the process causing CPU overload

— Module 5: Package Management

Topics:

RPM package system
Repository configuration
Installing software packages
Updating packages
Querying packages

Hands-On / Demo

› Lab: Install packages
› Lab: Configure a local repository
› Assignment: Install web server packages from a repository
› Job Scenario: Server cannot access the internet repository — create a local package repository

— Module 6: Storage Management (Important RHCSA Topic)

Topics:

Disk partitions
File systems
Mounting storage
Persistent mounts
Logical Volume Manager (LVM)
Disk quotas

Hands-On / Demo

› Lab: Create partitions
› Lab: Create logical volumes
› Lab: Extend storage
› Assignment: Create a 10GB logical volume and mount it permanently
› Job Scenario: Database server storage is full — extend the logical volume without downtime

— Module 7: Networking Configuration

Topics:

Configure IP addresses
Configure hostname
DNS configuration
Network troubleshooting

Hands-On / Demo

› Lab: Configure static IP
› Lab: Configure hostname
› Assignment: Configure two servers to communicate over the network
› Job Scenario: Users cannot access the server due to incorrect network configuration

— Module 8: Firewall and Security

Topics:

Firewall configuration
Allow and block ports
Secure shell configuration

Hands-On / Demo

› Lab: Configure firewall rules
› Lab: Enable SSH access
› Assignment: Allow web server traffic through the firewall
› Job Scenario: Application is running but users cannot access it due to firewall rules

— Module 9: SELinux Administration

Topics:

SELinux modes
SELinux policies
File context management
Troubleshooting SELinux issues

Hands-On / Demo

› Lab: Restore SELinux contexts
› Lab: Modify SELinux rules
› Assignment: Fix a web server access issue caused by SELinux
› Job Scenario: Application fails after SELinux policy enforcement

— Module 10: Log Monitoring and Troubleshooting

Topics:

System log files
Log monitoring
Troubleshooting system failures

Hands-On / Demo

› Lab: Analyze logs
› Lab: Identify errors
› Assignment: Identify the reason for a service failure using log files

— Capstone RHCSA Capstone Project — Enterprise Linux Server Deployment

Tasks:

Install Linux server
Configure users
Configure storage using LVM
Configure networking
Configure firewall and SELinux
Deploy web server

Deliverables

› Server documentation
› Configuration scripts

RHCE — Red Hat Certified Engineer RH294

Focus: Automation using Ansible

— Module 1: Introduction to Automation

Topics:

Automation concepts
Infrastructure automation
Configuration management
Ansible architecture

Hands-On / Demo

› Lab: Install Ansible
› Lab: Configure inventory
› Assignment: Run commands on multiple servers using Ansible ad-hoc commands

— Module 2: Ansible Playbooks

Topics:

YAML syntax
Playbook structure
Tasks and modules
Variables

Hands-On / Demo

› Lab: Write playbooks
› Lab: Execute automation tasks
› Assignment: Create a playbook to install a web server on multiple machines

— Module 3: Managing Files with Ansible

Topics:

Copy files
Manage configuration files
Template management

Hands-On / Demo

› Lab: Deploy configuration files to servers
› Assignment: Deploy an application configuration file to 5 servers

— Module 4: User Management with Ansible

Topics:

Create users
Manage groups
Manage SSH keys

Hands-On / Demo

› Lab: Automate user creation
› Assignment: Create 10 users across servers using a playbook

— Module 5: Service Management with Ansible

Topics:

Start and stop services
Enable services
Restart services

Hands-On / Demo

› Lab: Manage services across multiple servers
› Assignment: Ensure the web server service is running on all nodes

— Module 6: Ansible Roles

Topics:

Role structure
Role variables
Reusable automation roles

Hands-On / Demo

› Lab: Create reusable roles
› Assignment: Create a role for installing the Apache web server

— Module 7: Advanced Ansible Automation

Topics:

Loops
Conditionals
Handlers
Error handling

Hands-On / Demo

› Lab: Implement conditional automation
› Assignment: Automate full server configuration using playbooks

— Capstone RHCE Capstone Project — Automated Infrastructure Deployment

Tasks (using Ansible):

Deploy web servers
Configure firewall
Create users
Deploy application configuration
Start services

Deliverables

› Automation scripts
› Server configuration reports

Python for Linux System Administrators Duration: 7 Hours

Objective: Enable Linux admins to automate system administration tasks using Python scripts.

— Module 1: Introduction to Python (1 Hour)

Topics:

Introduction to Python
Why Python is popular for DevOps and system administration
Installing Python on Linux
Python interpreter and script execution
Writing first Python program

Hands-On / Demo

› Lab: Write a script to print hostname, current date and system uptime
› Assignment: Create a Python script that displays CPU, memory and disk usage

— Module 2: Python Basics for Automation (2 Hours)

Topics:

Variables and data types
Lists, tuples, dictionaries
Conditional statements (if/else)
Loops (for / while)
Functions

Hands-On / Demo

› Lab: Write scripts to check disk space and list running processes
› Assignment: Create a script that monitors disk space and alerts when usage exceeds 80%

— Module 3: File Handling and System Interaction (2 Hours)

Topics:

Reading and writing files
Log file analysis
Using the OS module
Running Linux commands from Python
Working with environment variables

Hands-On / Demo

› Lab: Create a script to analyze Linux system logs
› Assignment: Write a Python script to check log files, detect error messages and generate a report

— Module 4: Automation Scripts for Linux Admins (2 Hours)

Topics:

Automating user creation
Backup automation
Monitoring scripts
Scheduling scripts using cron

Hands-On / Demo

› Mini Project: Create a server health monitoring script

AWS Fundamentals for Linux Administrators Duration: 7 Hours

— Module 1: Introduction to Cloud Computing (1 Hour)

Topics:

Cloud computing concepts
Benefits of cloud
Types of cloud models
Infrastructure as a Service
Overview of Amazon Web Services

Hands-On / Demo

› Assignment: Compare on-premise infrastructure vs cloud infrastructure

— Module 2: AWS Core Services (3 Hours)

Topics:

AWS Global Infrastructure
Compute: Amazon EC2
Storage: Amazon S3
Networking: Amazon VPC
Identity and Access Management: AWS IAM

Hands-On / Demo

› Lab: Create an EC2 Linux instance, connect using SSH, upload files to S3
› Assignment: Launch a Linux web server on EC2

— Module 3: AWS for Linux Administrators (3 Hours)

Topics:

Key pairs and security groups
Elastic IP
Storage options (EBS)
Monitoring with Amazon CloudWatch
Auto scaling concept

Hands-On / Demo

› Lab: Configure a web server on an EC2 instance
› Mini Project: Deploy a Linux Apache web server on AWS cloud

DevOps Fundamentals for Linux System Administrators Duration: 6 Hours

— Module 1: Introduction to DevOps (1 Hour)

Topics:

What is DevOps
DevOps lifecycle
Continuous Integration
Continuous Delivery
Role of Linux administrators in DevOps

Hands-On / Demo

› Assignment: Explain how DevOps improves software deployment speed

— Module 2: Version Control with Git (2 Hours)

Topics:

Introduction to Git
Repository
Commit
Branch
Merge
Git workflow

Hands-On / Demo

› Lab: Create a Git repository and push code to a Git server
› Assignment: Maintain automation scripts in a Git repository

— Module 3: Containerization Basics (2 Hours)

Topics:

Introduction to Docker
What is containerization
Containers vs virtual machines
Docker architecture
Docker images and containers
Running containers

Hands-On / Demo

› Lab: Run a Linux container using Docker
› Assignment: Deploy a web application inside a Docker container

— Module 4: CI/CD Basics (1 Hour)

Topics:

Introduction to Jenkins
CI/CD pipeline concept
Automated builds
Integration with Git
Deployment automation overview

Hands-On / Demo

› Lab: Understand basic CI/CD workflow

— Capstone Final Mini Project — Linux DevOps Automation Project

Students will:

Write a Python script for system monitoring
Store code in a Git repository
Deploy the application on AWS EC2
Run the application using a Docker container

Skills Gained

› Linux automation using Python
› Basic cloud infrastructure deployment
› Version control with Git
› Containerization with Docker
› Understanding of DevOps workflows

Course 02 of 09 14 Modules SRE Track

Site Reliability Engineering (SRE)

Focus: Production Reliability, Observability & Incident Response

Course Content

— Module 1: SRE Foundations & Principles

Topics:

SRE philosophy — origin (Google model), why SRE exists, DevOps vs SRE
Reliability engineering concepts — availability, durability, performance trade-offs
SLIs, SLOs & SLAs — availability, latency, error rate; SLO design; SLA vs SLO
Error budgets — allowable failure, release control, burn rate
Toil & automation — identifying and converting repetitive manual work

Hands-On / Demo

› Assignment: Define SLOs for a banking app and an e-commerce system

— Module 2: Linux & System Engineering for SRE

Topics:

File system hierarchy, users/groups/permissions, package management
Process management — lifecycle, foreground/background jobs, monitoring tools
Memory & CPU — RAM/swap usage, CPU load, performance bottlenecks
Disk & file systems — partitions, I/O performance, usage analysis
System logs — log locations, systemd logs, log rotation

Hands-On / Demo

› Lab: Analyze a high-CPU issue
› Lab: Analyze a disk-full issue

— Module 3: Networking for SRE

Topics:

Networking basics — TCP/IP model, IP addressing, ports & protocols
HTTP/HTTPS — request-response lifecycle, status codes, REST APIs
DNS — domain resolution process, DNS failures
Load balancing — L4 vs L7, round robin, least connections
Reverse proxy and traffic routing
Troubleshooting — ping, traceroute, packet loss, latency

Hands-On / Demo

› Assignment: Debug a slow API response

— Module 4: Programming & Automation (Python for SRE)

Topics:

Python basics — variables, loops, functions, file handling, exception handling
Automation use cases — server monitoring scripts, log parsing, API automation
Shell scripting — Bash scripts, cron jobs
API integration — REST API calls, JSON handling

Hands-On / Demo

› Assignment: Build a server health monitoring script
› Assignment: Build a log analyzer

— Module 5: Version Control & CI/CD

Topics:

Git — repositories, commits, branches, merge conflicts, workflows
CI/CD concepts — Continuous Integration, Delivery vs Deployment
Jenkins pipeline — build stages, automated testing, deployment automation
Rollback strategies — Blue-Green deployment, canary releases

Hands-On / Demo

› Assignment: Build a CI/CD pipeline with rollback

— Module 6: Containers & Kubernetes

Topics:

Docker — images, containers, Dockerfile creation, container lifecycle
Kubernetes — pods, deployments, services (ClusterIP, NodePort), ingress
Scaling & self-healing — Horizontal Pod Autoscaler, restart policies

Hands-On / Demo

› Lab: Deploy an application on Kubernetes
› Lab: Implement auto-scaling

— Module 7: Infrastructure as Code (Terraform)

Topics:

IaC concepts — declarative vs imperative, benefits of automation
Terraform — providers, resources, state file
Modules & reusability — creating reusable infra code

Hands-On / Demo

› Assignment: Provision a cloud VM + network with Terraform

— Module 8: Observability & Monitoring

Topics:

Observability concepts — logs, metrics, traces, golden signals
Monitoring tools — Prometheus, Grafana
Alerting — threshold alerts, alert fatigue, alert tuning

Hands-On / Demo

› Lab: Build a monitoring dashboard
› Lab: Configure alerts

— Module 9: Logging & Log Management

Topics:

Centralized logging — why centralized logs, log aggregation
ELK Stack — Elasticsearch (storage), Logstash (processing), Kibana (visualization)

Hands-On / Demo

› Assignment: Set up a log pipeline

— Module 10: Incident Management & RCA

Topics:

Incident lifecycle — detection, response, recovery
Root cause analysis — 5 Whys, Fishbone diagram
Postmortems — blameless culture, documentation

Hands-On / Demo

› Assignment: Perform RCA on an outage scenario

— Module 11: Reliability Engineering & Performance

Topics:

Capacity planning — traffic forecasting, resource allocation
Performance testing — load testing, stress testing
Optimization — CPU and memory tuning

Hands-On / Demo

› Assignment: Analyze performance bottlenecks

— Module 12: Security for SRE

— Module 13: Cloud & Distributed Systems

Topics:

High availability architecture
Multi-region deployment
Failover strategies

Hands-On / Demo

› Assignment: Deploy a highly available system

— Module 14: Automation & Self-Healing

Topics:

Auto-remediation
Event-driven automation
Runbooks

Hands-On / Demo

› Assignment: Build an auto-healing system

— Capstone SRE Capstone Project — Production-Grade Reliability Platform

Students Build:

Kubernetes-based application
Monitoring system (Prometheus + Grafana)
CI/CD pipeline with rollback
Auto-healing scripts

Real Job Scenarios Covered

› Production outage simulation
› High-latency debugging
› Deployment failure handling
› Alert-noise reduction
› Scaling failure resolution

Course 03 of 09 12 Modules AIOps Track

AIOps Engineering

Focus: AI-Driven Monitoring, Observability & Self-Healing Automation

Course Content

— Module 1: AIOps Fundamentals

Topics:

What is AIOps & why it matters
Evolution: Monitoring → Observability → AIOps
Core capabilities: event correlation, noise reduction, root cause analysis (RCA), predictive analytics
AIOps architecture (data → AI → action)

Hands-On / Demo

› Assignment: Analyze sample logs — identify anomalies manually and categorize alerts into incidents

— Module 2: DevOps, SRE & Observability Foundations

Topics:

DevOps lifecycle
SRE principles: SLI, SLO, SLA
Observability pillars: logs, metrics, traces
Golden signals: latency, traffic, errors, saturation

Hands-On / Demo

› Assignment: Define SLOs for a web application — availability & latency

— Module 3: Monitoring & Data Collection Stack

Topics:

Metrics collection using Prometheus
Visualization using Grafana
Log management using ELK Stack
Distributed tracing basics

Hands-On / Demo

› Lab: Set up monitoring — collect system & app metrics
› Lab: Build dashboards

— Module 4: Data Engineering for AIOps

Topics:

Log ingestion pipelines
Data normalization & enrichment
Time-series databases
Streaming basics (Kafka concepts)

Hands-On / Demo

› Assignment: Build a log ingestion + parsing pipeline

— Module 5: Python for AIOps Automation

Topics:

Scripting for automation
Log parsing & regex
API integration
Data processing (Pandas, NumPy)

Hands-On / Demo

› Assignment: Develop a script to parse logs & detect anomalies

— Module 6: Machine Learning for AIOps

Topics:

ML fundamentals for operations
Supervised vs unsupervised learning
Anomaly detection techniques: Isolation Forest, clustering
Time-series forecasting

Hands-On / Demo

› Assignment: Build a CPU anomaly detection model

— Module 7: AI Techniques in AIOps

Topics:

Event correlation algorithms
Root cause analysis using AI
Predictive failure detection
NLP for log analysis

Hands-On / Demo

› Assignment: Correlate multiple alerts into a single root cause

— Module 8: AIOps Tools & Platforms

Topics:

Overview of Moogsoft
Overview of Dynatrace
Overview of Splunk ITSI
Tool comparison & architecture

— Module 9: Automation & Self-Healing Systems

Topics:

Auto-remediation concepts
Runbooks automation
Integration with CI/CD tools

Hands-On / Demo

› Assignment: Build an auto-restart service script on failure

— Module 10: Cloud & Kubernetes AIOps

Topics:

Cloud monitoring concepts
Kubernetes observability
Container metrics & logs

Hands-On / Demo

› Assignment: Monitor a Kubernetes cluster & detect anomalies

— Module 11: Incident Management & RCA

Topics:

Incident lifecycle
RCA frameworks
Alert prioritization
Noise reduction techniques

Hands-On / Demo

› Assignment: Perform root cause analysis for an outage

— Module 12: Security & Compliance

— Capstone AIOps Capstone Projects — Enterprise-Level (5 Projects)

Projects:

Intelligent Monitoring & Alerting System
AI-Based Incident Prediction
Self-Healing Infrastructure
Log Analytics with NLP
Kubernetes AIOps Platform

Real Enterprise Job Scenarios

› Alert Storm → AI-based noise reduction & correlation
› Unknown Production Failure → AI-driven root cause analysis
› Predictive Maintenance → ML models to predict failures
› Auto-Healing Systems → Automated remediation scripts
› Multi-Cloud Monitoring → Unified observability platform

Course 04 of 09 10 Modules Job-Oriented

AWS Solution Architect

Real-time enterprise scenarios, architectures, troubleshooting and DevOps + Cloud integrations used in top MNCs.

Course Content

— Module 1: Cloud Basics & AWS Foundation

Topics:

Cloud computing fundamentals — IaaS, PaaS, SaaS models
AWS Global Infrastructure — Regions, AZs, Edge Locations
Shared Responsibility Model
AWS Well-Architected Framework (all 6 pillars)
Billing & cost fundamentals
IAM basics — Users, Groups, Policies

Hands-On / Demo

› Lab: Create AWS account, configure billing alerts
› Lab: IAM users + MFA setup

— Module 2: Identity & Access Management (IAM) — Deep Dive

Topics:

IAM policies & policy evaluation logic
Roles, STS, access keys, permission boundaries
Resource policies, trust policies, cross-account access
Organizations & SCPs (Service Control Policies)
Identity Center (SSO) integration, IAM Access Analyzer

Hands-On / Demo

› Lab: Create IAM roles with cross-account access
› Lab: Create SCPs to restrict admin users
› Lab: IAM Access Analyzer to detect over-permissioned roles

— Module 3: VPC & Networking (Advanced Level)

Topics:

VPC core concepts — subnets, route tables, IGW, NAT, NACL vs SG
VPC endpoints (Gateway + Interface), DHCP options
Transit Gateway, VPC peering (inter/intra-region)
Hybrid networking — Site-to-Site VPN, Direct Connect
Route53 DNS deep dive — private hosted zones, failover & geolocation routing

Hands-On / Demo

› Lab: Build a multi-AZ VPC
› Lab: Create a PrivateLink endpoint; connect 2 VPCs via peering; configure Transit Gateway
› Job Scenario: Intermittent packet loss from a private subnet
› Job Scenario: Hybrid network outage RCA

— Module 4: EC2 & Compute Mastery

Topics:

EC2 instance families, Nitro architecture
Launch Templates, Auto Scaling Groups, Placement Groups
Spot instances — diversification, capacity handling
EBS performance tuning (PIOPS), EC2 metadata IMDSv2
Elastic Load Balancing (ALB, NLB, GLB), advanced autoscaling

Hands-On / Demo

› Lab: Create an Auto-Scaling group with ALB; configure NLB + PrivateLink
› Lab: EC2 rescue for a failed boot; AMI building & automation
› Job Scenario: ASG not scaling during high load; root volume corruption recovery

— Module 5: Storage & Databases

Topics:

EBS (GP3/IO2), EFS and FSx optimization
S3 internals & security — Object Lock, lifecycle, replication
RDS (Multi-AZ, read replicas), Aurora Serverless v2
DynamoDB (streams, DAX, on-demand), ElastiCache, Redshift

Hands-On / Demo

› Lab: S3 bucket policy & encryption; deploy Aurora with automatic failover
› Lab: DynamoDB with autoscaling
› Job Scenario: RDS failover troubleshooting; DynamoDB throttling issues

— Module 6: Containers, Serverless & Modern Architecture

Topics:

ECS architecture — EC2 vs Fargate launch types, ECR lifecycle policies
Lambda — versions, aliases, layers; Step Functions
EventBridge advanced patterns, API Gateway (REST/HTTP/WebSocket)
SQS/SNS patterns, Kinesis Data Streams + Firehose

Hands-On / Demo

› Lab: Deploy a serverless API (API Gateway → Lambda → DynamoDB)
› Lab: Deploy an ECS service with ALB; build CI/CD for ECR + ECS
› Job Scenario: Lambda timeout debugging; ECS task stuck in PENDING

— Module 7: Infrastructure as Code — Terraform & CloudFormation

Topics:

CloudFormation nested stacks, drift detection
Terraform — modules, workspaces, state management, remote backends
Terraform + AWS integration patterns

Hands-On / Demo

› Lab: Build a VPC using Terraform; automate ALB + ASG infra using IaC
› Job Scenario: Terraform state corruption fix; drift between manual & IaC deployment

— Module 8: Monitoring & Logging

Topics:

CloudWatch metrics, logs, alarms; Container Insights
CloudTrail advanced logging
OpenSearch for log analytics, X-Ray tracing for distributed apps

Hands-On / Demo

› Lab: Create metric alarms for ASG & RDS
› Lab: Centralized logging using CloudWatch + OpenSearch; trace latency using X-Ray

— Module 9: Security, Compliance & Governance

Topics:

KMS CMKs & auto-key rotation, Secrets Manager & Parameter Store
Inspector, GuardDuty, Macie; WAF + Shield Advanced
Zero Trust in AWS, IAM Access Analyzer, Config + Security Hub
AWS Organizations & governance

Hands-On / Demo

› Lab: Encrypt EC2, RDS and S3 with KMS; WAF rules for OWASP Top 10; enable GuardDuty
› Job Scenario: Breached IAM keys rotation & containment; S3 accidental public exposure fix

— Module 10: High Availability, DR & Migration Strategies

Topics:

Multi-AZ vs Multi-Region design
Pilot Light, Warm Standby, Multi-Site DR; RPO/RTO calculations
AWS Backup strategies; migration tools (SMS, DMS, Application Migration Service)
Blue/Green & Canary deployments, Global Accelerator

Hands-On / Demo

› Lab: Multi-region failover using Route53; DMS for database migration
› Lab: Lift & shift migration of an on-prem application
› Job Scenario: Application outage in one region — failover to another; database migration with zero downtime

— Capstone AWS Solution Architect Capstone — Enterprise Cloud Architecture

Skills Delivered:

Real-world Solution Architect skills
Enterprise architecture design capability
Advanced VPC / networking mastery
Serverless + containers production-level skills
IaC automation (Terraform + CloudFormation)
DR, migration and HA expertise

Deliverables

› Multi-tier VPC architecture
› Serverless + container workloads
› IaC templates (Terraform / CloudFormation)
› DR & failover runbook

Course 05 of 09 12 Modules 70 Hours

DevOps Engineering

Git, Jenkins, Docker, Kubernetes, Terraform, Ansible, Observability and GitOps — 100% practical.

Course Content

— Module 1: Development Environment & Version Control

Topics:

Dev environment setup — Java, Maven, Git, VS Code, IntelliJ, AWS CLI
Git — DVCS fundamentals, branching strategies (feature/release/hotfix)
GitHub — repositories, branch permissions, webhooks, code reviews

Hands-On / Demo

› Assignment: Setup a complete DevOps developer environment
› Project: Implement a GitFlow strategy for a microservices project

— Module 2: Monolith to Microservices

Topics:

Developing microservices from scratch using Java
Compiling, packaging and running microservices with Maven
Converting a monolithic app into microservices

Hands-On / Demo

› Project: Build E-commerce microservices (Product + Order Service)
› Job Scenario: Migrating a legacy banking application to microservices

— Module 3: Build Tools & Artifact Repositories

Topics:

Maven — build automation using pom.xml, dependencies, plugins, repositories
Docker Hub, AWS ECR and Nexus artifact management

Hands-On / Demo

› Project: Automate build & packaging for microservices; centralized artifact management system
› Job Scenario: Fixing build failures due to dependency conflicts

— Module 4: Core CI/CD with Jenkins

Topics:

Jenkins installation on AWS EC2, plugins & secrets configuration
Declarative pipelines, parameterized pipelines, build triggers
Jenkins Master-Slave architecture, user administration

Hands-On / Demo

› Project: Build an end-to-end CI pipeline (Code → Build → Test → Package)
› Job Scenario: Fix a broken CI pipeline in production

— Module 5: Containerization with Docker

Topics:

Dockerfile creation, images, containers, registry, daemon
Docker network, volume and container operations
Linux kernel features — namespace, cgroup, iptables

Hands-On / Demo

› Project: Containerize a microservices application
› Job Scenario: Debug a container crash in production

— Module 6: Continuous Code Inspection

Topics:

SonarQube installation & configuration on AWS EC2
Integrating quality gates into the Jenkins CI pipeline

Hands-On / Demo

› Project: Integrate quality gates in CI/CD
› Job Scenario: Reject a deployment due to code vulnerabilities

— Module 7: Infrastructure as Code with Terraform

Topics:

Terraform providers, blocks (provider/resource/variable/data/output)
Aliases, tfvars, implicit & explicit dependencies
Modules & remote state backend (S3), Jenkins integration

Hands-On / Demo

› Project: Build reusable Terraform modules
› Job Scenario: Provision infrastructure for 10 environments (dev/QA/prod)

— Module 8: Configuration Management with Ansible

Topics:

Ansible architecture and components
Ad-hoc commands, playbooks for complex automation workflows
Roles for reusable automation components

Hands-On / Demo

› Project: Automated server configuration (Web + DB servers)
› Job Scenario: Patch 100 servers automatically

— Module 9: Container Orchestration with Kubernetes

Topics:

Kubernetes architecture — control plane, worker nodes, etcd, kubelet, kube-proxy
Cluster setup on AWS EKS (eksctl, kops, Terraform)
Objects — Namespace, Service, Ingress, Deployment, ConfigMap, PV/PVC
HPA, Cluster Autoscaler, Karpenter and KEDA

Hands-On / Demo

› Project: Deploy microservices on AWS EKS
› Job Scenario: Fix pod crashloop / memory issues

— Module 10: Observability & Monitoring

Topics:

Prometheus installation on AWS EKS using Helm 3
Grafana dashboards and ingress configuration

Hands-On / Demo

› Project: End-to-end monitoring dashboard
› Job Scenario: Detect a CPU spike and alert the SRE team

— Module 11: Advanced DevOps Tooling — Istio, Packer, ELK, Vault + ESO

Topics:

Service mesh with Istio — traffic management, mTLS, canary deployments
HashiCorp Packer — golden AMI builds, multi-cloud image builds
ELK Stack — centralized logging, Logstash pipelines, Kibana dashboards
HashiCorp Vault secrets management + External Secrets Operator (ESO) for Kubernetes

Hands-On / Demo

› Lab: Deploy Istio on Kubernetes & configure traffic routing
› Lab: Create a machine image (AMI) using Packer
› Lab: Implement a centralized logging system with ELK
› Lab: Store secrets in Vault and consume them in Kubernetes using ESO

— Module 12: GitOps with ArgoCD

Topics:

GitOps continuous delivery concepts
Deploying ArgoCD on an AWS EKS cluster
Synchronizing Kubernetes applications with Git repositories

Hands-On / Demo

› Lab: Deploy ArgoCD on AWS EKS and configure an ingress endpoint

— Capstone DevOps Capstone — 4 Industry-Level Projects

Projects:

End-to-End DevOps Pipeline (Git → Jenkins → Docker → ECR → Kubernetes → Monitoring)
Terraform + Jenkins Automation (infra provisioning via pipeline)
Multi-branch CI/CD for Kubernetes Microservices
Production Simulation Project (high traffic, DB tuning, auto-scaling, incident handling)

Deliverables

› Resume-ready 4 projects
› CI/CD pipeline templates
› Terraform modules
› Kubernetes YAMLs
› Incident runbook
› Monitoring dashboards

Course 06 of 09 9 Modules AI-Enabled Ops

GenAI & Agentic AI for Infrastructure Engineers

Focus: AI automation, troubleshooting and autonomous agents for real DevOps/Cloud workflows.

Course Content

— Module 1: Foundations of Generative AI

Topics:

What is Generative AI, LLMs (Large Language Models)
Tokens, prompts, embeddings; prompt engineering & context handling
Hallucinations & limitations
OpenAI GPT models, LangChain overview

Hands-On / Demo

› Assignment: Build a prompt to generate Linux commands

— Module 2: Agentic AI Fundamentals

Topics:

AI agents vs traditional scripts, autonomous decision-making
Agent architecture — planning, memory, tool usage
Frameworks — LangChain, AutoGPT

Hands-On / Demo

› Assignment: Build a basic AI agent for system tasks

— Module 3: AI for Linux System Administration

Topics:

AI-driven bash command & script generation
Log analysis using AI — parse system logs, detect anomalies
Root-cause suggestions using AI

Hands-On / Demo

› Assignment: Build an AI tool to analyze /var/log

— Module 4: AI for DevOps Automation

Topics:

AI-generated CI/CD pipelines, auto-debugging pipelines
Generating Terraform scripts and Kubernetes YAML
Tools integration — Jenkins, Git

Hands-On / Demo

› Assignment: Generate a CI/CD pipeline using AI

— Module 5: AI for Cloud Engineering

Topics:

Auto-generating cloud architecture
Cost optimization using AI
Multi-cloud AI-based recommendations

Hands-On / Demo

› Assignment: Design an AI-generated cloud architecture

— Module 6: AI for Kubernetes & Containers

Topics:

Generating Kubernetes manifests using AI
Debugging cluster issues with AI

Hands-On / Demo

› Assignment: Build an AI assistant for Kubernetes debugging

— Module 7: AIOps + GenAI Integration

Topics:

AI-based anomaly detection, alert summarization
AI-driven root cause analysis

Hands-On / Demo

› Assignment: Build an AI tool for alert analysis

— Module 8: Building AI Agents for Infrastructure

Topics:

Agent design — task planning, multi-step execution
Tool integration — shell commands, APIs
Memory systems — short-term vs long-term memory

Hands-On / Demo

› Assignment: Build an AI agent to monitor and fix server issues

— Module 9: Security, Governance & Advanced Topics

— Capstone GenAI Capstone Projects — Enterprise-Level (5 Projects)

Projects:

AI-Powered DevOps Assistant
AI-Based Log Analyzer
Autonomous Infrastructure Agent
AI Kubernetes Troubleshooter
AI Cloud Optimization Tool

Real Enterprise Job Scenarios

› Production Outage → AI agent detects, suggests fix, executes remediation
› CI/CD Failure → AI debugs pipeline & suggests correction
› Alert Storm → AI summarizes alerts & identifies root cause
› Cloud Cost Spike → AI analyzes usage & suggests optimization
› Kubernetes Failure → AI diagnoses pod failure & suggests fix

Course 07 of 09 7 Modules Multi-Cloud Platform

Kubernetes Multi-Cloud (AKS | EKS | GKE)

Managed Kubernetes across Azure, AWS & GCP — basics to production to multi-cluster/multi-cloud.

Course Content

— Module 1: Kubernetes & Container Foundations

Topics:

Containers vs VMs, image lifecycle, registries
Kubernetes architecture — control plane, nodes
Core objects — Pods, Deployments, ReplicaSets
Services (ClusterIP/NodePort/LoadBalancer), Ingress, ConfigMaps/Secrets/PV/PVC
Health checks (liveness/readiness), HPA autoscaling

Hands-On / Demo

› Lab: Build & push an image; deploy to a cluster
› Lab: Expose an app via Service + Ingress; enable CPU-based autoscaling

— Module 2: Azure Kubernetes Service (AKS)

Topics:

AKS architecture, node pools (system/user), scaling
Azure CNI vs Kubenet, private clusters, ingress (NGINX/App Gateway)
Azure AD, RBAC, Managed Identities
Azure Disks/Files CSI drivers, Azure Monitor & Container Insights

Hands-On / Demo

› Lab: Create AKS with multi-node pools; deploy app with Ingress + TLS; integrate AAD for RBAC
› Job Scenario: Pod pending due to IP exhaustion; AAD auth failures; Ingress 502 errors

— Module 3: AWS Kubernetes (EKS)

Topics:

EKS control plane, managed vs self-managed nodes, Fargate
VPC/subnets/security groups & CNI plugin, IAM roles for service accounts (IRSA)
EBS/EFS CSI drivers, ALB/NLB ingress controllers
CloudWatch observability, Cluster Autoscaler, Karpenter (intro)

Hands-On / Demo

› Lab: Create EKS (eksctl/Terraform); configure IRSA for S3 access; deploy behind ALB Ingress
› Job Scenario: Nodes not joining cluster; service unreachable; cost spike

— Module 4: GCP Kubernetes (GKE)

Topics:

GKE Standard vs Autopilot
VPC-native networking (alias IP), private clusters, Workload Identity
Persistent Disks, Filestore, HTTP(S) load balancing & NEG
Cloud Operations monitoring, node auto-provisioning, HPA/VPA

Hands-On / Demo

› Lab: Create a private GKE cluster; enable Workload Identity for GCS access; HTTPS ingress with autoscaling
› Job Scenario: Image pull errors; Ingress misrouting; pod OOMKilled

— Module 5: Advanced Kubernetes — Production Engineering

Topics:

Helm charts — templating, values, releases
CI/CD with Jenkins (build → scan → push → deploy), GitOps (Argo CD/Flux concepts)
Observability — Prometheus + Grafana; logging with ELK Stack
RBAC, NetworkPolicies, Pod Security, secrets management, service mesh basics

Hands-On / Demo

› Lab: Package an app with Helm; build a CI/CD pipeline to AKS/EKS/GKE; set up metrics dashboards & alerts
› Job Scenario: Failed rollout & rollback strategy; high-latency bottleneck; security audit (RBAC/policies)

— Module 6: Multi-Cloud & Platform Engineering

Topics:

Multi-cluster strategies (per cloud/region)
Traffic management & failover (DNS/ingress strategies)
Portable manifests, environment overlays, cross-cloud cost optimization
DR strategies and backups (etcd snapshots, Velero concepts)

Hands-On / Demo

› Lab: Deploy the same app to AKS, EKS and GKE; implement blue/green or canary across clusters; simulate a region failure
› Job Scenario: Cloud outage → route traffic to a healthy cluster; config drift → GitOps reconciliation

— Module 7: Infrastructure as Code for Multi-Cloud

Topics:

Provisioning clusters with Terraform
Reusable modules for AKS/EKS/GKE
Secrets/variables management, CI pipelines for infra changes

Hands-On / Demo

› Lab: Write Terraform to create VPC/VNet + clusters; parameterize modules for multi-cloud reuse; plan/apply with approvals

— Capstone Multi-Cloud Kubernetes Capstone — 4 Enterprise Projects

Projects:

Multi-Cloud Microservices Platform (same app on AKS, EKS, GKE)
CI/CD + GitOps Platform (Helm/Argo CD, dev → staging → prod)
Observability Stack (metrics, dashboards, alerts, centralized logs, SLOs/SLIs)
DR & Failover (simulate failure, backup/restore cluster state)

Real Enterprise Scenarios

› Pods Pending → resource quota / node capacity / CNI issues
› CrashLoopBackOff → app config, secrets, probes
› Service not reachable → Service/Ingress/DNS/SG rules
› High costs → rightsizing, autoscaling, spot/preemptible
› Security gaps → RBAC, network policies, secrets rotation

Course 08 of 09 12 Modules ML as a System

MLOps for Infrastructure & DevOps Engineers

Minimal theory, maximum production use cases — ML lifecycle, deployment & monitoring for infrastructure engineers.

Course Content

— Module 1: MLOps Fundamentals

Topics:

MLOps vs DevOps vs AIOps
ML lifecycle — Data → Training → Deployment → Monitoring
Challenges — data drift, model drift, reproducibility
ML Engineer vs MLOps Engineer roles

Hands-On / Demo

› Assignment: Draw an end-to-end ML pipeline architecture

— Module 2: Python & Data Handling for Ops Engineers

Topics:

Python essentials for automation, file handling & APIs
CSV/JSON data processing
Pandas & NumPy basics

Hands-On / Demo

› Assignment: Build a data preprocessing script

— Module 3: Version Control for ML

Topics:

Git workflows for ML code
Data & model versioning — why it is critical
DVC concepts (data version control tools)

Hands-On / Demo

› Assignment: Version an ML project with code + data

— Module 4: Data Engineering for MLOps

Topics:

Batch vs streaming pipelines
ETL pipelines, data lakes vs databases
Pipeline automation & scheduling

Hands-On / Demo

› Assignment: Build an ETL pipeline

— Module 5: Machine Learning Basics (Practical)

Topics:

Supervised vs unsupervised learning, training vs inference
Regression & classification models
Evaluation — accuracy, precision, recall

Hands-On / Demo

› Assignment: Train a basic ML model

— Module 6: Containerization & Environment Management

Topics:

Dockerfile for ML apps, packaging models
Dependency management & reproducibility

Hands-On / Demo

› Assignment: Containerize an ML model

— Module 7: Kubernetes for MLOps

Topics:

Kubernetes basics — Pods, Deployments, Services
ML deployment on Kubernetes — model serving, scaling
Rolling updates & auto-scaling

Hands-On / Demo

› Lab: Deploy an ML model on Kubernetes

— Module 8: CI/CD for Machine Learning

Topics:

CI/CD differences for ML, continuous training
Pipeline using Jenkins — Build → Train → Test → Deploy
Automated model retraining

Hands-On / Demo

› Assignment: Build an ML CI/CD pipeline

— Module 9: Model Deployment & Serving

Topics:

REST API serving vs batch inference
API creation, scaling endpoints

Hands-On / Demo

› Assignment: Deploy an ML model as an API

— Module 10: Monitoring & Observability for ML

Topics:

Model performance monitoring, data drift detection
Prometheus & Grafana for ML monitoring
Prediction logs & error tracking

Hands-On / Demo

› Assignment: Monitor model accuracy

— Module 11: Infrastructure as Code & Governance

Topics:

Provisioning ML infrastructure using Terraform
Infrastructure pipelines
Model security, data privacy, access control

Hands-On / Demo

› Assignment: Provision an ML environment

— Module 12: Advanced MLOps — Lifecycle & Experiment Tracking

— Capstone MLOps Capstone Projects — Enterprise-Level (5 Projects)

Projects:

End-to-End ML Pipeline
ML CI/CD Pipeline
Scalable Model Deployment (Kubernetes)
ML Monitoring System (drift detection)
Self-Retraining System

Real Enterprise Job Scenarios

› Model Accuracy Drops → detect drift, retrain model
› Deployment Failure → fix CI/CD pipeline
› Scaling Issues → Kubernetes auto-scaling
› Data Pipeline Failure → debug ETL pipeline
› Slow Predictions → optimize model serving

Course 09 of 09 10 Modules Automation Track

Python Scripting for DevOps & MLOps

Industry-ready Python for system automation, cloud, Kubernetes, IaC and ML pipelines.

Course Content

— Module 1: Python Fundamentals for Engineers

Topics:

Variables, data types, operators
Control flow (if, loops)
Functions & modular programming
Error handling (try/except)

Hands-On / Demo

› Assignment: Build a CLI script to check server status and print CPU/memory usage

— Module 2: Python for System Administration

Topics:

File system operations, process management
Working with shell commands
Environment variables

Hands-On / Demo

› Assignment: Script to monitor disk usage and clean old logs automatically

— Module 3: Python for Networking & APIs

Topics:

HTTP concepts (GET, POST, PUT)
API calls using requests, JSON parsing
Authentication — tokens, headers

Hands-On / Demo

› Assignment: Script to call an API, fetch system metrics and store results in a file

— Module 4: Automation with Python

Topics:

Task automation scripts, scheduling (cron jobs)
Email automation, log parsing

Hands-On / Demo

› Assignment: Automate a daily log report with email alerts on failure

— Module 5: Python + DevOps Tools Integration

Topics:

Integrating Python with Git and Jenkins
Triggering builds via API, automating CI/CD tasks

Hands-On / Demo

› Assignment: Python script to trigger a Jenkins job and monitor build status

— Module 6: Python for Cloud & Container Automation

Topics:

Cloud SDK usage — AWS boto3 basics
Automating EC2 instances & S3 storage
Interacting with Docker & Kubernetes — automating deployments, managing pods via API

Hands-On / Demo

› Assignment: Launch an EC2 instance and upload a file to S3; deploy a container and monitor pod status

— Module 7: Python for Infrastructure as Code

Topics:

Working with Terraform from Python
Generating dynamic configs, automating provisioning

Hands-On / Demo

› Assignment: Generate a Terraform config using Python

— Module 8: Python for MLOps & Data Processing

Topics:

Basics of ML workflows, model lifecycle management
Data pipelines; Pandas/NumPy for cleaning & transformation

Hands-On / Demo

› Assignment: Process server logs into structured data; build a simple ML pipeline automation script

— Module 9: Python + ML Integration

Topics:

Model training basics using Scikit-learn
Saving & loading models
MLOps pipeline automation — training → deployment, versioning

Hands-On / Demo

› Assignment: Train a simple model to predict system failure

— Module 10: Logging, Testing & Security

Topics:

Logging frameworks & monitoring integration
Unit testing (pytest), code linting, debugging techniques
Secure coding practices, secrets management, API security

Hands-On / Demo

› Assignment: Build a monitoring script with alerts; write tests for automation scripts

— Capstone Python Automation Capstone Projects (4 Projects)

Projects:

DevOps Automation Toolkit (server monitoring, Jenkins integration, auto alerts)
Cloud Automation System (EC2 provisioning, S3 automation, resource cleanup)
MLOps Pipeline Automation (data pipeline, model training, deployment)
Kubernetes Deployment Automation (auto deployment, pod monitoring, scaling)

Real Enterprise Work Scenarios

› CI/CD Automation → automate build triggers, monitor failures
› Infrastructure Provisioning → create cloud infra dynamically
› Model Deployment Pipeline → train, deploy, monitor ML models
› Log Monitoring System → parse logs, detect anomalies
› Auto-Healing Systems → detect failure, restart services automatically

Tools & Technologies

Every tool and library listed here is installed, configured and used in a hands-on lab session.

Linux & Scripting

Linux

OS & Administration

Bash

Shell Scripting

Python

Automation Scripting

VS Code

Development IDE

Automation & Version Control

Ansible

Configuration Management

Git

Version Control

GitHub

Code Collaboration

Containers & CI/CD

Docker

Containerization

Jenkins

CI/CD Basics

AWS Cloud Fundamentals

Amazon EC2

Compute

Amazon S3

Storage

Amazon VPC

Networking

AWS IAM

Identity & Access Management

CloudWatch

Monitoring

SRE: Monitoring & Observability

Prometheus

Metrics Collection & Alerting

Grafana

Monitoring Dashboards

ELK Stack

Log Management

SRE: Infrastructure as Code & Kubernetes

Terraform

Infrastructure as Code

Kubernetes

Container Orchestration

AIOps & Machine Learning

Pandas / NumPy

Data Processing & ML

Moogsoft / Dynatrace / Splunk ITSI

AIOps Platforms

Multi-Cloud Kubernetes

AKS / EKS / GKE

Managed Kubernetes

Helm

Kubernetes Package Manager

ArgoCD

GitOps Continuous Delivery

Istio

Service Mesh

Build Tools & Artifact Management

Maven

Build Automation

SonarQube

Code Quality

Nexus

Artifact Repository

Packer

Golden Image Builds

HashiCorp Vault

Secrets Management

GenAI & Agentic AI

OpenAI GPT

Large Language Models

LangChain

AI Agent Framework

MLOps & Data Science

Scikit-learn

Model Training

DVC

Data & Model Versioning

boto3

AWS SDK for Python

pytest

Testing & Code Quality

41+

Tools & Libraries

114+

Hands-On Modules

Courses

400-430

Training Hours

You don't just learn Linux. You build enterprise infrastructure.

Five capstone-style projects, each mirroring how enterprise Linux, DevOps, SRE and AIOps teams actually deploy, automate and operate real infrastructure — from RHCSA server deployment and Ansible automation to a production-grade Kubernetes reliability platform and an AI-driven self-healing monitoring system.

PROJECT // 01

Enterprise Linux Server Deployment

→Linux Server Install

→User & Storage Configuration (LVM)

→Networking, Firewall & SELinux

→Web Server Deployment

RHCSA Capstone Intermediate

Install, configure and secure a production-style enterprise Linux server end to end

Install a Linux server, configure users and groups, set up storage using LVM, configure networking, lock down the firewall and SELinux, and deploy a web server — the same tasks a Linux Administrator handles on day one.

Server documentation

Configuration scripts

LVM-based storage layout

Hardened firewall & SELinux configuration

Stack Linux RHCSA LVM SELinux

PROJECT // 02

Automated Infrastructure Deployment with Ansible

→Ansible Playbooks & Roles

→Multi-Server Web Deployment

→Automated User & Firewall Config

→Service Management

RHCE Capstone Advanced

Automate a full multi-server deployment using Ansible playbooks and roles

Use Ansible to deploy web servers, configure the firewall, create users, push application configuration and start services across multiple nodes — without touching each server by hand.

Automation scripts (playbooks & roles)

Server configuration reports

Multi-node deployment via Ansible

Stack Ansible YAML Linux

PROJECT // 03

Linux DevOps Automation Project

→Python System Monitoring

→Git Version Control

→AWS EC2 Deployment

→Docker Container

Python + AWS + DevOps Advanced

Build a system-monitoring script, version it in Git, and deploy it on AWS using Docker

Write a Python script for system health monitoring, store the code in a Git repository, deploy the application on an AWS EC2 instance, and run it inside a Docker container — a complete mini DevOps workflow for Linux admins.

Linux automation script using Python

Code maintained in a Git repository

Application deployed on AWS EC2

Application running in a Docker container

Stack Python Git AWS EC2 Docker

PROJECT // 04

Production-Grade Reliability Platform

→Kubernetes Deployment (Terraform)

→Prometheus + Grafana + ELK Observability

→CI/CD Pipeline with Rollback

→Auto-Healing Runbooks

SRE Capstone Advanced

Build a Kubernetes-based, self-healing platform with full observability and automated incident response

Deploy a Kubernetes application with Terraform-provisioned infrastructure, build a Prometheus/Grafana/ELK observability stack, wire up a CI/CD pipeline with rollback, and implement auto-healing runbooks — the same reliability workflow a Site Reliability Engineer runs in production.

Monitoring dashboard & alerting rules

CI/CD pipeline with blue-green/canary rollback

Auto-remediation runbook scripts

RCA report for a simulated outage

Stack Kubernetes Terraform Prometheus Grafana

PROJECT // 05

AI-Based Intelligent Monitoring & Auto-Healing Platform

→Log & Metric Collection

→ML-Based Anomaly Detection

→AI-Driven Root Cause Correlation

→Auto-Remediation Scripts

AIOps Capstone Advanced

Design an AIOps system that detects anomalies with ML and auto-remediates production incidents

Collect logs and metrics, apply ML-based anomaly detection to reduce alert noise, correlate alerts into a single root cause using AI, and trigger auto-remediation scripts — a complete AIOps monitoring-to-healing pipeline.

ML anomaly detection model

Intelligent alerting with reduced noise

Auto-remediation runbook scripts

Project documentation & portfolio

Stack Python Prometheus Grafana Scikit-learn

All 5 projects go directly into your portfolio & resume — reviewed by mentors before you graduate.

See Sample Project Reports

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Radical Technologies is the leading IT certification institute in Pune, offering globally recognized certifications across various domains. With expert trainers and comprehensive materials, we ensure students gain in-depth knowledge and hands-on experience to excel in their careers. Our certification programs are tailored to meet industry standards — from Red Hat Linux Administration (RHCSA & RHCE) to AWS Cloud, DevOps, Site Reliability Engineering (SRE) and AIOps — empowering individuals to stay ahead in the ever-evolving enterprise technology landscape.

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At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance programme ensures you are equipped with industry-relevant Cloud, DevOps and Infrastructure skills and guided through the full placement process — with personalised resume building, interview preparation, and access to our network of 850+ hiring partners, until you get placed.