(Linux, Git, Google Cloud Platform, Terraform, Docker, Kubernetes, Jenkins, Prometheus, Grafana, SRE, MLOps & AI-Assisted Security Engineering)
A complete, hands-on path from Linux and Git fundamentals through Google Cloud, Terraform, Docker, Kubernetes, CI/CD, monitoring, SRE and AI-assisted security engineering.
Linux fundamentals, shell scripting, permissions and troubleshooting, plus Git & GitHub workflows for CI/CD.
IAM, VPC networking, Compute Engine, Cloud Storage, Cloud SQL, monitoring and a full GCP architecture project.
Providers, state, modules and a real GCP infrastructure provisioning project using Terraform.
Docker images, multi-stage builds, Kubernetes deployments, services, Helm and a production deployment project.
Jenkinsfiles, Maven and Docker integration, deploying to Kubernetes through a full pipeline project.
Metrics, PromQL, alerting and production-grade observability dashboards for infrastructure and applications.
Shift-left security, SAST, SCA, DAST, container & secrets security, and secure CI/CD pipelines.
ML lifecycle, model training, packaging, deployment, monitoring and secure MLOps workloads on GCP.
AI-assisted vulnerability triage, SAST/DAST analysis, secure coding and building a small AI-powered SRE assistant.
Whether you're starting out or upskilling, this course is designed to take you from the basics to a confident GCP SRE engineer.
Start from Linux and Git basics and build up to a production-grade SRE and AI-assisted security skill set — fully guided, module by module.
Every module is anchored by real, hands-on labs and projects on Google Cloud, Kubernetes and CI/CD pipelines — not just slides and theory.
Learn how to apply AI tooling to vulnerability triage, SAST/DAST analysis and secure coding, and build a small AI-powered SRE assistant.
Linux, GCP, Terraform, Docker, Kubernetes, Jenkins, Prometheus, Grafana, SRE tooling and MLOps — the full modern platform stack.
Every live session is recorded and shared, with a full year of access so you can revisit any topic at your own pace.
Combine GCP, Kubernetes, SRE and AI-assisted tooling into a small, real-world SRE assistant project by the end of the course.
Experience the trainer's hands-on teaching style before enrolling — completely free, no commitment required.
A comprehensive, progressive curriculum — from Linux and Git fundamentals to GCP, Terraform, Kubernetes, CI/CD, monitoring, SRE, MLOps and AI-assisted security engineering.
| Topic | What You'll Learn |
|---|---|
| Fundamentals & File Management | Linux fundamentals · File & directory management · File viewing and text processing |
| Text Processing | grep, regular expressions & sed · Pipes, redirection & command chaining |
| System Administration | Users, groups & file permissions · Processes & system management |
| Storage & Networking | Disk & filesystem management · Networking fundamentals |
| Remote Access & Services | SSH & remote access · Services, systemd & logs |
| Scripting & Troubleshooting | Basic shell scripting · Linux troubleshooting |
| Topic | What You'll Learn |
|---|---|
| Git Fundamentals | Repository, working tree & staging · Basic Git commands |
| Collaboration | Branching, merging & conflict resolution · GitHub repositories & pull requests |
| CI/CD & Troubleshooting | Git workflow for CI/CD · Basic Git troubleshooting |
| Topic | What You'll Learn |
|---|---|
| Cloud & Resource Fundamentals | Cloud computing & Google Cloud fundamentals · Resource hierarchy |
| IAM & Identity | IAM · Service accounts & least privilege |
| Networking | VPC networking · Subnets, routes & firewall rules · Cloud NAT · DNS fundamentals · Load balancing fundamentals |
| Compute & Storage | Compute Engine · Persistent disk · Cloud Storage buckets · Storage classes, versioning & lifecycle |
| Databases & Observability | Cloud SQL · Cloud Monitoring & Logging |
| Reliability & Project | High availability & GCP reliability · GCP architecture project |
| Topic | What You'll Learn |
|---|---|
| IaC Fundamentals | Infrastructure as Code & Terraform fundamentals · Terraform configuration & core blocks |
| Providers & Data | Providers, resources & data sources · Variables, outputs & locals |
| Logic & Expressions | Expressions, functions & collections · count & for_each · Conditional expressions & for expressions |
| State & Modules | Dependencies & lifecycle · Terraform state & remote state · Terraform modules |
| Workflow & Project | Terraform workflow & best practices · GCP infrastructure provisioning project |
| Topic | What You'll Learn |
|---|---|
| Maven Basics | Maven fundamentals · Project structure & pom.xml |
| Build Lifecycle | Dependencies & Maven lifecycle · Build, test & package |
| CI/CD Integration | Maven integration with CI/CD |
| Topic | What You'll Learn |
|---|---|
| Container Fundamentals | Container fundamentals & Docker architecture · Docker images & containers |
| CLI & Dockerfile | Docker CLI & image lifecycle · Dockerfile · Docker build context & .dockerignore |
| Advanced Builds | Multi-stage Docker builds · Docker networking |
| Storage & Registries | Docker volumes & persistent data · Container registries |
| Troubleshooting | Container troubleshooting |
| Topic | What You'll Learn |
|---|---|
| Kubernetes Fundamentals | Architecture · Pods |
| Workloads | Deployments & ReplicaSets · Services & service discovery · Ingress & ingress controllers |
| Configuration | ConfigMaps & Secrets · Deployment strategies |
| Resource Management | Resource requests, limits & QoS · Health checks & probes · Horizontal Pod Autoscaling |
| Storage & Scheduling | Kubernetes storage · Scheduling & node selection · Node affinity & pod anti-affinity · Topology spread constraints · Taints & tolerations |
| Security & Packaging | Service accounts & RBAC · Helm |
| Troubleshooting & Project | Kubernetes troubleshooting · Production Kubernetes deployment project |
| Topic | What You'll Learn |
|---|---|
| CI/CD Fundamentals | Jenkins fundamentals & architecture · CI/CD fundamentals |
| Pipelines | Jenkins pipelines · Jenkinsfile & declarative pipeline · Credentials & environment variables |
| Integrations | Maven integration · Docker build & image push · Kubernetes integration |
| Deployment & Project | Deploying applications to Kubernetes · CI/CD pipeline project |
| Topic | What You'll Learn |
|---|---|
| Monitoring Fundamentals | Monitoring & observability fundamentals · Prometheus architecture |
| Metrics & Discovery | Metrics & metric types · Targets, service discovery & exporters · Node Exporter |
| Kubernetes Monitoring | Kubernetes monitoring · kube-state-metrics |
| PromQL & Alerting | PromQL fundamentals · Application & infrastructure metrics · Alerting fundamentals |
| Project | Prometheus monitoring project |
| Topic | What You'll Learn |
|---|---|
| Grafana Basics | Grafana fundamentals · Prometheus integration · Data sources & queries |
| Dashboards | Dashboards & panels · Variables & dashboard design |
| Monitoring Dashboards | Infrastructure, Kubernetes & application monitoring dashboards |
| Alerting & Project | Grafana alerting · Production observability project |
| Topic | What You'll Learn |
|---|---|
| SRE Foundations | Introduction to SRE · SRE Principles · DevOps vs SRE · Reliability Engineering |
| SLI, SLO & Error Budgets | SLI, SLO & SLA · Error Budgets · Toil & Automation |
| Reliability Metrics | Golden Signals & RED Methodology · Availability · Scalability · Resilience & Fault Tolerance |
| Capacity & Production Reliability | Capacity Planning · Production Reliability & Troubleshooting |
| Incident Management | Incident Management & On-Call · Incident Response · Root Cause Analysis |
| Postmortems & Disaster Recovery | Blameless Postmortems · Disaster Recovery & Business Continuity |
| Topic | What You'll Learn |
|---|---|
| MLOps Fundamentals | Introduction to MLOps · MLOps Fundamentals · ML Lifecycle & Architecture |
| ML Lifecycle & Versioning | Data, Model & Experiment Lifecycle · Model Training and Versioning |
| Model Packaging & Deployment | Model Packaging and Deployment |
| Model Monitoring & Reliability | Model Monitoring · ML Reliability |
| MLOps Infrastructure | MLOps Workloads on Cloud and Kubernetes |
| Topic | What You'll Learn |
|---|---|
| AI Fundamentals for SRE | AI Fundamentals for SRE |
| AI-Assisted Alert & Incident Analysis | AI-assisted Alert and Incident Analysis · AI-assisted Log and Metric Analysis |
| AI-Assisted Observability | AI-assisted PromQL Assistance · AI-assisted SLO Analysis |
| AI-Assisted RCA & Troubleshooting | AI-assisted RCA · AI-assisted Runbooks and Troubleshooting |
| AI-Assisted Postmortems & SRE Assistant | AI-assisted Postmortems · Building a Small AI-powered SRE Assistant |
| Responsible AI | Responsible AI and Human Validation |
Capstone Focus: Build a small AI-powered SRE Assistant for alert analysis, log and metric analysis, RCA, troubleshooting, SLO analysis, runbooks, and postmortems.
Cloud & DevOps Engineer with over 10 years of experience in cloud infrastructure automation and SRE.
Gopi has designed and implemented cloud infrastructure and automation solutions across Google Cloud Platform, Kubernetes/GKE, Terraform, Docker and Jenkins, with hands-on expertise in CI/CD pipelines, SRE practices and cloud infrastructure automation.
As a trainer, Gopi has mentored over 200 students, bringing a practical, project-driven teaching style that helps learners tackle real GCP and SRE challenges with confidence.
Feedback from learners who completed the AI-Assisted SRE Engineer program.
The way the course builds from Linux and Git fundamentals up to GCP and Kubernetes made everything click. The SRE and AI-assisted modules were the highlight for me.
Coming from a QA background, the Terraform and GCP sections took time to click, but the hands-on labs made the concepts stick. Gopi explains everything with real project context.
The AI-assisted SRE module was genuinely useful — seeing how AI tooling fits into vulnerability triage and secure coding gave me a real edge in interviews.
I switched from a networking role and was worried about keeping up, but the daily hands-on labs on Kubernetes and Jenkins pipelines built my confidence step by step.
The live sessions on Prometheus and Grafana monitoring were exactly what I needed for my current job. Doubt-clearing over WhatsApp between classes was a big help too.
Solid, structured curriculum — Terraform and GCP concepts were explained with real infrastructure examples instead of just slides. The certificate helped me negotiate a better offer.
Every participant who successfully completes the training receives a Course Completion Certificate from Isha Training Solutions.
Sample certificate — your name will be printed upon completion
To maintain the quality of our training and ensure a smooth learning experience for all participants, we do not allow batch repetition or switching between courses.
Moving from one course to another, or shifting from one trainer to another, is not possible once a batch has started. Changing batches or trainers in any form is strictly not permitted.
We request all learners to attend the scheduled sessions regularly and make the most of their learning journey. Thank you for your understanding and continued support.
