Mentorship Program

★★★★★

(1,240 ratings) 8,500+ Student

6 Month Mentorship Program in Platform Engineering

From Basic to Advanced. Six specialized tracks, one topic a month — Linux & System Administration | Cloud Computing | DevOps & Python | Containers & Kubernetes | Infrastructure as Code | SRE, Observability & AI. Every track follows the same arc: Fundamentals → Hands-on Labs → Assignments → Mini Projects → Job Scenarios → Troubleshooting → Capstone → Mock Interviews, across 90+ labs, 60+ assignments, 25+ mini projects, 6 major capstones and 1 integrated enterprise capstone. No prior Linux administration experience is required — Month 1 starts at fundamentals and the programme finishes with SRE, AIOps and AI-assisted platform operations.

Radical Technologies

8,500+ English 6 Tracks · 6 Months · 240 Hours

Online / Classroom

From Basic to Advanced | 6 Months | 6 Specialized Tracks

Duration 240 Hours (6 Months)

Batch Type Weekdays / Weekends

Mode of Training Classroom / Online / Corporate

Locations Pune, Bangalore, Kochi

Language English

Certification Mentorship Certificate + Global Certification Roadmap

Tools you'll master

RHEL Rocky Linux Ubuntu Bash SSH systemd LVM SELinux AWS Microsoft Azure Google Cloud Git GitHub GitLab Jenkins GitHub Actions Python Docker Docker Compose Kubernetes Helm Terraform OpenTofu Ansible Checkov OPA Prometheus Grafana Alertmanager OpenTelemetry Jaeger ELK Stack OpenSearch Loki SLO / SLI Error Budgets RCA & Runbooks GenAI APIs AIOps

Next batch: 10/08/2026 · Online

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Why This Course?

6 specialized tracks, one topic a month, across 6 months and 240 hours

Approach: Fundamentals → Hands-on Labs → Assignments → Mini Projects → Job Scenarios → Troubleshooting → Capstone → Mock Interviews

90+ hands-on labs and exercises across the six tracks

60+ assignments and 25+ mini projects

6 major capstones plus 1 integrated enterprise capstone

Production troubleshooting, SRE practice and AI/AIOps applied to platform operations

Mock interviews in every track, from Linux commands through to SLOs and RCA

Prerequisites

Basic Computer Knowledge

Basic Networking Concepts

No Prior Linux Administration Experience Required

Logical and Problem-Solving Skills

Programme Overview

6 specialized tracks, one topic a month — Linux & System Administration, Cloud Computing, DevOps & Python, Containers & Kubernetes, Infrastructure as Code, and SRE, Observability & AI. Each month ends in a major outcome, from Enterprise Linux Administrator through to SRE / Platform Engineer.

240 hrs

Training Hours

Specialized Tracks

Total Modules

4.8★

Average Rating

50K+

Students Trained

Month 1 — Linux & System Administration

Enterprise Linux administration with practical experience in users, permissions, networking, storage, processes, services, security, automation and troubleshooting. Outcome: Enterprise Linux Administrator.

RHEL / Rocky / Ubuntu Permissions & ACLs systemd LVM & Storage SELinux & Firewall Bash Automation

Month 2 — Cloud Computing

Cloud infrastructure fundamentals through advanced deployment and administration using AWS, Azure and GCP concepts. Outcome: Cloud Infrastructure Engineer.

AWS / Azure / GCP VPC & VNet IAM & RBAC Cloud Storage Load Balancing High Availability

Month 3 — DevOps & Python

DevOps principles, Git, CI/CD, Python automation, Linux automation and deployment pipelines. Outcome: DevOps / Automation Engineer.

Git & GitHub Jenkins GitHub Actions Python API Automation Deployment & Rollback

Month 4 — Containers & Kubernetes

Containerization using Docker and enterprise Kubernetes administration, deployment, networking, security and troubleshooting. Outcome: Container & Kubernetes Engineer.

Docker Docker Compose Kubernetes Ingress RBAC & Network Policies Helm

Month 5 — Infrastructure as Code (IaC)

Automated infrastructure provisioning and configuration management using Terraform, Ansible and policy-driven infrastructure practices. Outcome: Infrastructure Automation Engineer.

Terraform State & Remote Backend Modules Ansible Policy as Code Drift Detection

Month 6 — SRE, Observability & AI

Site Reliability Engineering, production reliability, monitoring, observability, incident management, SLOs/SLIs and AI-assisted platform operations. Outcome: SRE / Platform Engineer.

SLI / SLO / SLA Prometheus Grafana OpenTelemetry Incident & RCA AIOps

Who is this programme for?

Whether you're a fresher, a Linux administrator, a Cloud Engineer, a developer or already working in production support — this mentorship is built to take you into a Platform Engineer, Cloud DevOps Engineer, Kubernetes Engineer, Infrastructure Automation Engineer or Site Reliability Engineer role.

Students & Freshers

No prior Linux administration experience needed — Month 1 starts at fundamentals and builds towards Junior Platform Engineer and Linux System Administrator roles.

Linux & System Administrators

Move up into Platform Engineer, Infrastructure Engineer and Cloud Operations Engineer roles with cloud, containers and IaC.

Cloud Engineers

Broaden into Cloud DevOps Engineer and Kubernetes Engineer roles across AWS, Azure and Google Cloud.

Developers & Scripters

Step into DevOps Engineer, Infrastructure Automation Engineer and Terraform Engineer roles through Git, Python and CI/CD.

Production Support Teams

Grow into Site Reliability Engineer and Production Support Engineer roles with SLOs, observability, incident response and RCA.

AI-Focused Engineers

Target DevSecOps, SRE / Observability Engineer and AIOps / Platform Automation Engineer roles with AI-assisted operations.

Course Curriculum

240 total hours · 6 months

6 tracks • 32 modules • one topic a month, with labs, assignments and a capstone in every track

Month 01 of 06 6 Modules Month 1 · Basic to Advanced

Linux & System Administration

Enterprise Linux administration with practical experience in users, permissions, networking, storage, processes, services, security, automation and troubleshooting.

Course Content

— Prerequisites

Prerequisites:

Basic computer knowledge
Basic networking concepts
No prior Linux administration experience required
Logical and problem-solving skills

— Module 1: Fundamentals

Topics:

Linux architecture
Kernel, shell and filesystem
CLI vs GUI
Linux distributions
Boot process
Filesystem hierarchy
Users, groups and permissions
Processes and services
Basic networking
System security fundamentals

— Module 2: Linux Administration

Topics:

RHEL / Rocky Linux / Ubuntu
Installation and VM configuration
Linux filesystem
File and directory management
Users and groups
Permissions and ownership
ACLs
Sudo and privilege management
Package management
RPM / YUM / DNF / APT
Processes and jobs
Systemd and services
Cron and scheduled jobs
Environment variables
Shell configuration

— Module 3: Storage

Topics:

Disk management
Partitions
Filesystems
Mounting
/etc/fstab
LVM
RAID concepts
Disk monitoring
Storage troubleshooting

— Module 4: Networking

Topics:

IP configuration
DNS
DHCP
SSH
SCP/SFTP
Routing
Network troubleshooting
Firewall
NetworkManager

— Module 5: Security

Topics:

SSH hardening
Password policies
Sudo security
File permissions
SELinux fundamentals
Firewall configuration
Security logs
Audit concepts
Patch management

— Module 6: Automation

Topics:

Bash scripting
System administration scripts
Backup automation
Log-management scripts

— Hands-On Labs

Labs:

Linux Server Installation Lab
Linux Filesystem Administration Lab
User & Group Management Lab
Linux Permissions & ACL Lab
Sudo Security Lab
Package Management Lab
Process Management Lab
Systemd Service Management Lab
SSH Configuration & Hardening Lab
Linux Networking Lab
Firewall Configuration Lab
LVM Storage Management Lab
Linux Log Analysis Lab
Bash Automation Lab
Linux Server Hardening Lab

— Assignments

Assignments:

Enterprise Linux installation
User and group administration
Permission management
LVM configuration
SSH hardening
Firewall configuration
Linux performance analysis
Log investigation
Server security checklist
Bash administration automation

— Mini Projects

Mini Projects:

Secure Linux Server Deployment
Linux User & Access Management System
Automated Linux Backup System
Linux Server Monitoring Script

— Capstone Enterprise Linux Infrastructure Deployment & Hardening

Project Focus:

Students deploy multiple Linux servers and implement the full administration stack

Implemented

› Users/groups
› SSH
› Networking
› Firewall
› Storage
› Services
› Monitoring
› Security hardening
› Backup
› Automation
› Troubleshooting documentation

— Real-Time Job Scenarios

Scenarios:

Production server is running out of disk space
SSH access is failing
User cannot access required files
Linux service has stopped
Server CPU utilization is high
DNS resolution is failing
Unauthorized login detected
Application cannot access a mounted filesystem

— Troubleshooting Scenarios

Troubleshooting:

Boot failure
Permission denied
SSH connection failure
DNS failure
Service failure
Disk full
High CPU
High memory
Network interface failure
LVM/storage issue

— Industry Tools

Tools:

Linux
RHEL
Rocky Linux
Ubuntu
SSH
Bash
systemd
LVM
SELinux
firewalld
iptables/nftables
Git
Ansible

— Best Practices

Best Practices:

Least privilege
Secure SSH
Regular patching
Centralized logging
Strong access controls
Backup and recovery
Infrastructure documentation
Monitoring and alerting

Mock Interviews

› Linux commands
› Troubleshooting
› Networking
› Permissions
› Storage
› SSH
› systemd
› Production scenarios

— Certification Names

Certifications:

Red Hat Certified System Administrator (RHCSA)
CompTIA Linux+
LPIC-1
Red Hat Certified Engineer (RHCE)

Month 02 of 06 6 Modules Month 2 · Basic to Advanced

Cloud Computing

Cloud infrastructure fundamentals through advanced deployment and administration using AWS, Azure and GCP concepts.

Course Content

— Prerequisites

— Module 1: Fundamentals

Topics:

Cloud computing
IaaS / PaaS / SaaS
Public/private/hybrid cloud
Regions and availability zones
Virtualization
Cloud networking
IAM
Storage
Compute
High availability
Scalability
Shared responsibility model

— Module 2: Cloud Infrastructure

Topics:

AWS / Azure / GCP architecture
Regions and Availability Zones
Compute services
Virtual machines
Images and snapshots
Instance lifecycle
Auto Scaling

— Module 3: Networking

Topics:

VPC / VNet
Subnets
Route tables
Internet/NAT gateways
Security Groups
Network Security Groups
Load Balancers
DNS
VPN
Private connectivity

— Module 4: IAM

Topics:

Users
Groups
Roles
Policies
RBAC
MFA
Least privilege
Service identities

— Module 5: Storage

Topics:

Object storage
Block storage
File storage
Lifecycle policies
Backup
Encryption

— Module 6: Cloud Operations

Topics:

Monitoring
Logging
Cost management
Backup
High availability
Disaster recovery
Cloud security

— Hands-On Labs

Labs:

AWS Account & IAM Lab
Azure Resource Management Lab
Cloud VM Deployment Lab
VPC/VNet Design Lab
Cloud Subnet Lab
Security Group/NSG Lab
Load Balancer Lab
Cloud Storage Lab
IAM Role Lab
Cloud Monitoring Lab
Cloud Backup Lab
Cloud DNS Lab
Auto Scaling Lab
Cloud Security Lab
Highly Available Application Lab

— Assignments

Assignments:

Cloud architecture design
VPC/VNet design
IAM policy creation
Cloud security assessment
Cloud storage architecture
Load-balancing architecture
Cloud monitoring plan
High-availability design
Cloud cost optimization exercise

— Mini Projects

Mini Projects:

Secure AWS Web Infrastructure
Azure Enterprise Network
Highly Available Cloud Application
Cloud Monitoring & Alerting System

— Capstone Enterprise Cloud Infrastructure Platform

Project Focus:

Build a production-style cloud environment

Containing

› VPC/VNet
› Multiple subnets
› Linux servers
› IAM
› Load balancer
› Auto scaling
› Storage
› Monitoring
› Backup
› Security controls
› High availability

— Real-Time Job Scenarios

Scenarios:

Cloud VM is unreachable
Application is unavailable
Security group blocks traffic
IAM user cannot access resource
Public storage exposure
High cloud infrastructure cost
Load balancer health check failure
Cloud server requires recovery

— Troubleshooting Scenarios

Troubleshooting:

VPC/VNet connectivity
Route-table problems
Security-group issues
DNS failures
IAM access denied
VM boot failure
Load-balancer failure
Storage access problems

— Industry Tools

Tools:

AWS
Microsoft Azure
Google Cloud
AWS CLI
Azure CLI
Cloud Shell
CloudWatch
Azure Monitor
IAM
Entra ID
Terraform

— Best Practices

Best Practices:

Least privilege
Infrastructure segmentation
Multi-AZ design
Encryption
Automated backup
Monitoring
Cost optimization
Infrastructure automation

Mock Interviews

› Cloud architecture
› VPC
› IAM
› Storage
› Networking
› HA
› Troubleshooting
› Cloud scenarios

— Certification Names

Certifications:

AWS Certified Solutions Architect – Associate
Microsoft Azure Administrator Associate
Google Associate Cloud Engineer
AWS Certified Cloud Practitioner

Month 03 of 06 5 Modules Month 3 · Basic to Advanced

DevOps & Python

DevOps principles, Git, CI/CD, Python automation, Linux automation and deployment pipelines.

Course Content

— Prerequisites

— Module 1: Fundamentals

Topics:

DevOps culture
SDLC
Agile
CI/CD
Version control
Infrastructure automation
Continuous testing
Continuous deployment
DevOps lifecycle

— Module 2: Git

Topics:

Git fundamentals
Repository management
Branching
Merging
Rebasing
Pull requests
Git workflows
GitHub/GitLab

— Module 3: CI/CD

Topics:

Pipeline architecture
Jenkins
GitHub Actions
GitLab CI/CD
Build automation
Testing
Artifact management
Deployment strategies
Rollback

— Module 4: Python

Topics:

Python fundamentals
Variables
Data types
Conditions
Loops
Functions
Modules
Exception handling
Files
JSON/YAML
APIs
Requests
Automation scripts
SSH automation
Cloud automation

— Module 5: DevOps Automation

Topics:

Linux automation
API automation
Cloud automation
Deployment automation
Monitoring automation

— Hands-On Labs

Labs:

Git Repository Lab
Branching & Merge Lab
GitHub Workflow Lab
Jenkins Installation Lab
Jenkins CI Pipeline
GitHub Actions Pipeline
Python Fundamentals Lab
Python File Automation
Python API Automation
Python Linux Automation
Cloud Automation with Python
Automated Deployment Lab
CI/CD Security Lab
Pipeline Notification Lab
Automated Rollback Lab

— Assignments

Assignments:

Git branching strategy
Git conflict resolution
Jenkins pipeline
GitHub Actions workflow
Python automation script
REST API automation
Linux automation
Cloud automation
CI/CD pipeline design

— Mini Projects

Mini Projects:

Python Server Automation Toolkit
Automated Application Deployment
Jenkins CI/CD Pipeline
Cloud Infrastructure Automation Script

— Capstone Enterprise CI/CD & Automation Platform

— Real-Time Job Scenarios

Scenarios:

Failed production deployment
Git merge conflict
Pipeline failure
Build failure
Deployment rollback
API authentication failure
Automated server provisioning
Application deployment automation

— Troubleshooting Scenarios

Troubleshooting:

Git conflicts
Jenkins agent failure
Pipeline failure
Credentials failure
Python dependency issue
API timeout
Deployment failure
Rollback failure

— Industry Tools

Tools:

Git
GitHub
GitLab
Jenkins
GitHub Actions
Python
PyCharm/VS Code
Docker
AWS CLI
Azure CLI
Ansible

— Best Practices

Best Practices:

Version control everything
Automated testing
Pipeline security
Secrets management
Code review
Small deployments
Automated rollback
Infrastructure automation

Mock Interviews

› Git
› CI/CD
› Jenkins
› Python
› Automation
› Deployment
› DevOps troubleshooting

— Certification Names

Certifications:

AWS Certified DevOps Engineer
Microsoft DevOps Engineer Expert
Certified Jenkins Engineer
GitHub Foundations
Python certifications

Month 04 of 06 4 Modules Month 4 · Basic to Advanced

Containers & Kubernetes

Containerization using Docker and enterprise Kubernetes administration, deployment, networking, security and troubleshooting.

Course Content

— Prerequisites

Prerequisites:

Linux
Networking
Git
Basic cloud knowledge

— Module 1: Fundamentals

Topics:

Containers
Virtual machines vs containers
Container architecture
Docker architecture
Kubernetes architecture
Cluster components
Pods
Services
Deployments
Container networking

— Module 2: Docker

Topics:

Docker architecture
Images
Containers
Dockerfile
Docker Compose
Volumes
Networks
Registry
Image optimization
Container security

— Module 3: Kubernetes

Topics:

Control plane
Worker nodes
Pods
ReplicaSets
Deployments
Services
Namespaces
ConfigMaps
Secrets
Volumes
StatefulSets
DaemonSets
Jobs/CronJobs
Ingress

— Module 4: Advanced Kubernetes

Topics:

Scheduling
Resource limits
HPA
RBAC
Network Policies
Persistent Volumes
Helm
Rolling updates
Blue/green deployments
Cluster troubleshooting
Kubernetes security

— Hands-On Labs

Labs:

Docker Installation Lab
Docker Image Lab
Dockerfile Lab
Docker Networking Lab
Docker Volume Lab
Docker Compose Lab
Private Registry Lab
Kubernetes Cluster Lab
Pod Deployment Lab
Kubernetes Service Lab
ConfigMap & Secret Lab
Persistent Storage Lab
Ingress Lab
RBAC Security Lab
Kubernetes Troubleshooting Lab

— Assignments

Assignments:

Build Docker image
Optimize Dockerfile
Docker Compose deployment
Kubernetes deployment
Kubernetes service
ConfigMap/Secret
Ingress configuration
Persistent storage
RBAC implementation
Kubernetes troubleshooting

— Mini Projects

Mini Projects:

Containerized Web Application
Three-Tier Docker Application
Kubernetes Microservices Platform
Secure Kubernetes Cluster

— Capstone Enterprise Kubernetes Application Platform

Project Focus:

Develop a production-style containerized platform end to end

Develop

› Containerized applications
› Kubernetes cluster
› Microservices
› Ingress
› Load balancing
› Secrets
› Persistent storage
› Autoscaling
› RBAC
› Monitoring
› Security

— Real-Time Job Scenarios

Scenarios:

Pod stuck in Pending
Container continuously restarting
Service unavailable
Image pull failure
Kubernetes node failure
Ingress not working
Application requires scaling
Persistent volume unavailable

— Troubleshooting Scenarios

Troubleshooting:

CrashLoopBackOff
ImagePullBackOff
Pending pods
DNS issues
Service connectivity
Node NotReady
Storage problems
RBAC errors

— Industry Tools

Tools:

Docker
Docker Compose
Kubernetes
kubectl
Helm
Minikube
Kind
EKS
AKS
GKE
Harbor
Prometheus
Grafana

— Best Practices

Best Practices:

Minimal images
Image scanning
Resource limits
RBAC
Network policies
Secrets management
Health probes
Autoscaling
Rolling deployments
Cluster monitoring

Mock Interviews

› Docker
› Kubernetes
› Pods
› Services
› Networking
› Storage
› RBAC
› Troubleshooting

— Certification Names

Certifications:

Certified Kubernetes Administrator (CKA)
Certified Kubernetes Application Developer (CKAD)
Certified Kubernetes Security Specialist (CKS)
Docker certifications

Month 05 of 06 5 Modules Month 5 · Basic to Advanced

Infrastructure as Code (IaC)

Automated infrastructure provisioning and configuration management using Terraform, Ansible and policy-driven infrastructure practices.

Course Content

— Prerequisites

Prerequisites:

Linux
Cloud fundamentals
Git
Basic networking

— Module 1: Fundamentals

Topics:

Infrastructure as Code
Declarative vs imperative
Configuration management
Immutable infrastructure
Infrastructure lifecycle
State management
Idempotency
Infrastructure version control

— Module 2: Terraform

Topics:

Terraform architecture
Providers
Resources
Variables
Outputs
Data sources
Modules
State
Remote state
Workspaces
Backend
Dependency management
Terraform Cloud concepts

— Module 3: Terraform Advanced

Topics:

Reusable modules
Environment management
Multi-cloud IaC
CI/CD integration
Security scanning
Policy as Code

— Module 4: Ansible

Topics:

Inventory
YAML
Playbooks
Tasks
Variables
Roles
Templates
Handlers
Vault
Configuration management

— Module 5: IaC Security

Topics:

Secrets
Terraform security
Misconfiguration detection
Policy enforcement
Drift detection
Compliance automation

— Hands-On Labs

Labs:

Terraform Installation Lab
AWS Infrastructure Provisioning Lab
Azure Infrastructure Provisioning Lab
Terraform Variables Lab
Terraform State Lab
Remote Backend Lab
Terraform Modules Lab
Multi-Environment Lab
Terraform CI/CD Lab
Terraform Security Scanning Lab
Ansible Installation Lab
Ansible Inventory Lab
Ansible Playbook Lab
Ansible Roles Lab
Automated Infrastructure Deployment Lab

— Assignments

Assignments:

Terraform cloud infrastructure
Terraform variables
Remote state
Terraform modules
Multi-environment infrastructure
Ansible server configuration
Ansible roles
Infrastructure security scan
IaC CI/CD pipeline
Infrastructure drift investigation

— Mini Projects

Mini Projects:

AWS Infrastructure Using Terraform
Azure Infrastructure Using Terraform
Linux Configuration Using Ansible
Multi-Environment IaC Platform
Secure IaC Pipeline

— Capstone Enterprise Infrastructure Automation Platform

— Real-Time Job Scenarios

Scenarios:

Terraform state conflict
Infrastructure drift
Failed provisioning
Cloud resource dependency
Ansible playbook failure
Configuration inconsistency
Secret exposed in code
Infrastructure rollback

— Troubleshooting Scenarios

Troubleshooting:

Terraform authentication failure
State locking
Provider error
Dependency error
Resource creation failure
Ansible SSH failure
YAML syntax error
Permission issue
Configuration drift

— Industry Tools

Tools:

Terraform
Terraform Cloud
OpenTofu
Ansible
Git
GitHub
GitLab
Jenkins
AWS
Azure
GCP
Checkov
OPA

— Best Practices

Best Practices:

Version-controlled infrastructure
Remote state
Reusable modules
Code review
Secrets management
Automated validation
Policy as Code
Drift detection
Immutable infrastructure

Mock Interviews

› Terraform
› State
› Modules
› Ansible
› IaC architecture
› Automation
› Troubleshooting

— Certification Names

Certifications:

HashiCorp Terraform Associate
Red Hat Certified Specialist in Ansible Automation
AWS Solutions Architect
Azure Administrator

Month 06 of 06 6 Modules Month 6 · Basic to Advanced

SRE, Observability & AI

Site Reliability Engineering, production reliability, monitoring, observability, incident management, SLOs/SLIs and AI-assisted platform operations.

Course Content

— Prerequisites

Prerequisites:

Linux
Cloud
DevOps
Kubernetes
Python fundamentals

— Module 1: Fundamentals

Topics:

SRE principles
DevOps vs SRE
Reliability engineering
SLIs
SLOs
SLAs
Error budgets
Incident management
Observability
Monitoring vs observability
Automation
Toil reduction

— Module 2: SRE

Topics:

SRE principles
Service reliability
SLIs/SLOs/SLAs
Error budgets
Availability
Reliability
Capacity planning
Performance engineering
Incident management
Postmortems
Disaster recovery
Business continuity

— Module 3: Observability

Topics:

Metrics
Logs
Traces
Distributed tracing
Application monitoring
Infrastructure monitoring
Kubernetes monitoring
Alerting
Dashboards

— Module 4: Monitoring Stack

Topics:

Prometheus
Grafana
Alertmanager
ELK/OpenSearch
OpenTelemetry
Jaeger

— Module 5: Incident Management

Topics:

Incident detection
Triage
Severity
Escalation
Incident response
Root-cause analysis
RCA documentation
Postmortems

— Module 6: AI for Platform Engineering

Topics:

GenAI fundamentals for infrastructure
AI-assisted troubleshooting
Log analysis with AI
Incident summarization
AI-assisted RCA
AIOps concepts
Anomaly detection
Predictive monitoring
AI-assisted automation
Intelligent alert correlation
AI agents for platform operations
Human approval and operational safety

— Hands-On Labs

Labs:

SRE Fundamentals Lab
SLI/SLO Design Lab
Error Budget Lab
Prometheus Installation Lab
Grafana Dashboard Lab
Alertmanager Lab
Linux Monitoring Lab
Kubernetes Monitoring Lab
Centralized Logging Lab
OpenTelemetry Lab
Distributed Tracing Lab
Incident Response Lab
Root Cause Analysis Lab
AI-Assisted Log Analysis Lab
AI-Assisted Incident Investigation Lab
AIOps Anomaly Detection Lab
AI Platform Automation Lab

— Assignments

Assignments:

Define SLIs and SLOs
Design an SRE dashboard
Create Prometheus alerts
Grafana dashboard
Incident-response plan
Production RCA
Capacity-planning exercise
Error-budget calculation
AI-assisted log investigation
AIOps architecture design

— Mini Projects

Mini Projects:

Enterprise Infrastructure Monitoring Platform
Kubernetes Observability Platform
Automated Incident Detection System
AI-Assisted Log Analysis Platform
SRE Reliability Dashboard

— Capstone Project 1 — Enterprise SRE & Observability Platform

— Capstone Project 2 — AI-Assisted Platform Operations

— Real-Time Job Scenarios

Scenarios:

Production application outage
High CPU/memory
Kubernetes pod failures
Increased application latency
API response degradation
Database connection problems
Alert storm
Service-level objective breach
Repeated production incidents
AI-assisted incident investigation

— Troubleshooting Scenarios

Troubleshooting:

Prometheus target unavailable
Grafana dashboard missing metrics
Alert not triggering
High application latency
Memory leak
Kubernetes performance degradation
Log ingestion failure
Distributed trace missing
Alert fatigue
Incorrect AI-generated diagnosis

— Industry Tools

Tools:

Prometheus
Grafana
Alertmanager
ELK Stack
OpenSearch
Fluent Bit
Loki
OpenTelemetry
Jaeger
Kubernetes
Datadog
New Relic
Splunk
Python
GenAI/AIOps platforms

— Best Practices

Best Practices:

Define measurable SLOs
Monitor user-impacting metrics
Reduce alert noise
Automate repetitive work
Conduct blameless postmortems
Maintain runbooks
Practice disaster recovery
Monitor capacity
Secure observability data
Keep humans in control of high-impact automated actions

Mock Interviews

› SRE
› SLI/SLO
› SLA
› Error budget
› Prometheus
› Grafana
› Incidents
› RCA
› Observability
› AIOps

— Certification Names

Certifications:

Google Professional Cloud DevOps Engineer
AWS Certified DevOps Engineer
Microsoft DevOps Engineer Expert
Certified Kubernetes Administrator
SRE-related professional certifications
Prometheus/Grafana ecosystem training certifications

Tools & Technologies

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

Linux & Infrastructure

RHEL / Rocky Linux

Enterprise Linux

Ubuntu

Linux Distribution

Bash

Shell Scripting & Automation

SSH

Secure Remote Access

systemd

Service Management

LVM

Logical Volume Storage

Cloud

AWS

EC2, VPC, IAM, S3, CloudWatch

Microsoft Azure

VNet, Entra ID, Azure Monitor

Google Cloud

Compute, Networking, IAM

DevOps

Git

Version Control

GitHub / GitLab

Repositories & Workflows

Jenkins

CI/CD Pipelines

GitHub Actions

Pipeline Automation

Python

Automation & API Scripting

Containers

Docker

Containerization

Docker Compose

Multi-Container Applications

Kubernetes

Container Orchestration

Helm

Kubernetes Packaging

Infrastructure as Code

Terraform

Infrastructure Provisioning

OpenTofu

Open-Source IaC

Ansible

Configuration Management

Checkov

IaC Security Scanning

OPA

Policy as Code

Observability

Prometheus

Metrics & Alerting

Grafana

Dashboards & Visualization

Alertmanager

Alert Routing

OpenTelemetry

Traces, Metrics & Logs

Jaeger

Distributed Tracing

ELK / OpenSearch / Loki

Centralized Logging

SRE

SLO / SLI

Reliability Targets

Error Budgets

Reliability Budgeting

Incident Management

Detection to Resolution

RCA & Runbooks

Postmortems & Operations

AI / AIOps

GenAI APIs

AI-Assisted Troubleshooting

AI Log Analysis

Incident Summarization

Anomaly Detection

Predictive Monitoring

Intelligent Alerting

Alert Correlation

39+

Tools & Libraries

32+

Hands-On Modules

Specialized Tracks

240

Training Hours

Six months, six outcomes — and a Platform Engineering portfolio you can walk an interviewer through.

A major capstone every month, two in Month 6, and one integrated final capstone — from a hardened Linux estate and a highly available cloud platform to a CI/CD pipeline, a Kubernetes application platform, Terraform and Ansible automation, an SRE observability platform and AI-assisted operations.

PROJECT // 01

Enterprise Linux Infrastructure Deployment & Hardening

→Users / Groups → SSH → Networking

→Firewall → Storage → Services

→Monitoring → Backup → Hardening

Month 1 Capstone Foundation

Outcome: Enterprise Linux Administrator

Deploy multiple Linux servers and implement the full administration stack, from users and networking through to backup, automation and troubleshooting documentation.

Users/groups, SSH and networking

Firewall, storage and services

Monitoring and security hardening

Backup, automation and troubleshooting documentation

Stack Linux Bash systemd

PROJECT // 02

Enterprise Cloud Infrastructure Platform

→VPC / VNet → Subnets → Linux Servers

→IAM → Load Balancer → Auto Scaling

→Storage → Monitoring → Backup

Month 2 Capstone Intermediate

Outcome: Cloud Infrastructure Engineer

Build a production-style cloud environment with segmented networking, identity, scaling, storage, monitoring and high availability.

VPC/VNet with multiple subnets

Linux servers and IAM

Load balancer and auto scaling

Storage, monitoring and backup

Security controls and high availability

Stack AWS Azure GCP

PROJECT // 03

Enterprise CI/CD & Automation Platform

→Git → Build → Test → Security Scan

→Package → Deploy

→Monitor → Rollback

Month 3 Capstone Intermediate

Outcome: DevOps / Automation Engineer

A complete delivery pipeline from commit to production, with security scanning, packaging, deployment, monitoring and automated rollback.

Python Server Automation Toolkit

Automated Application Deployment

Jenkins CI/CD Pipeline

Cloud Infrastructure Automation Script

Stack Git Jenkins Python

PROJECT // 04

Enterprise Kubernetes Application Platform

→Containerized Apps → Kubernetes Cluster

→Microservices → Ingress → Load Balancing

→Secrets → Storage → Autoscaling → RBAC

Month 4 Capstone Advanced

Outcome: Container & Kubernetes Engineer

Containerized microservices running on a secured Kubernetes cluster with ingress, persistent storage, autoscaling, RBAC and monitoring.

Containerized applications and Kubernetes cluster

Microservices, ingress and load balancing

Secrets, persistent storage and autoscaling

RBAC, monitoring and security

Stack Docker Kubernetes Helm

PROJECT // 05

Enterprise Infrastructure Automation Platform

→Git → Terraform → Cloud Infrastructure

→Ansible → Application Deployment

→Security Scan → Monitoring

Month 5 Capstone Advanced

Outcome: Infrastructure Automation Engineer

Version-controlled infrastructure provisioned by Terraform, configured by Ansible, then security scanned and monitored — the whole path from Git to running platform.

AWS Infrastructure Using Terraform

Azure Infrastructure Using Terraform

Linux Configuration Using Ansible

Multi-Environment IaC Platform

Secure IaC Pipeline

Stack Terraform Ansible Checkov

PROJECT // 06

Enterprise SRE & Observability Platform

→Infrastructure → Kubernetes

→Metrics → Logs → Traces → Alerts

→Incident → RCA → SLO

Month 6 — Capstone 1 Advanced

Metrics, logs and traces tied back to a service-level objective

Instrument infrastructure and Kubernetes end to end, route alerts, run the incident through to root-cause analysis, and measure it against an SLO.

Enterprise Infrastructure Monitoring Platform

Kubernetes Observability Platform

Automated Incident Detection System

SRE Reliability Dashboard

Stack Prometheus Grafana OpenTelemetry

PROJECT // 07

AI-Assisted Platform Operations

→Monitoring → Alert → AI Analysis

→Log Correlation → Root Cause Suggestions

→Remediation → Human Approval → Automation

Month 6 — Capstone 2 Advanced

AI correlates the logs and proposes the fix — a human approves it

An alert triggers AI analysis and log correlation, producing root-cause suggestions and a remediation recommendation that only runs after human approval.

AI-Assisted Log Analysis Platform

AI-assisted incident investigation

AIOps anomaly detection

Human-approved automated remediation

Stack Python GenAI APIs AIOps

PROJECT // 08

Enterprise Platform Engineering & Intelligent Operations Platform

→Linux → Cloud → Git → Python → CI/CD

→Docker → Kubernetes → Terraform → Ansible

→Monitoring → Observability → SRE → AI-Assisted Operations

Integrated Final Capstone Flagship

Every track combined into one production-style platform

Linux through cloud, Git, Python, CI/CD, Docker, Kubernetes, Terraform, Ansible, monitoring, observability and SRE, finishing with AI-assisted operations.

Enterprise architecture diagram, Linux infrastructure and cloud architecture

Git repository, Python automation and CI/CD pipeline

Dockerized applications, Kubernetes cluster, Terraform modules and Ansible automation

Monitoring dashboards, centralized logging and distributed tracing

SLO/SLI definitions, incident-response process and RCA report

AI-assisted troubleshooting workflow and production runbooks

Disaster-recovery plan and final technical presentation

Stack Kubernetes Terraform Prometheus

All 8 projects go directly into your portfolio & resume — reviewed by mentors before you graduate.

See Sample Project Reports

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