DevOps Zero to Hero Programs

What You'll Become

Not Just Trained.
Production-Ready.

We don’t teach you DevOps tools in isolation. We put you inside real production scenarios — broken deployments, failing pipelines, scaling issues — and train you to fix them. By the time you finish, you’ll have done the actual job.

01

⚙️

CI/CD & Automation

Design, build, and debug real CI/CD pipelines using GitHub Actions, Jenkins, and Azure Pipeline CI. Automate build, test, and deployment workflows — including failure handling, rollback strategies, and production-grade pipeline design.

02

🐳

Containers & Kubernetes

Containerize applications using Docker and deploy them on Kubernetes clusters. Work with real cluster issues — pod failures, scaling problems, networking, ingress, and debugging production incidents aligned with CKA-level scenarios.

03

☁️

Cloud Engineering (AWS & Azure)

Deploy and manage infrastructure on AWS and Azure — VMs, networking, IAM, load balancers, and storage. Handle real-world cloud scenarios like high availability, cost optimization, and secure deployments aligned with AWS SAA & AZ-104.

04

🏗️

Infrastructure as Code

Provision complete infrastructure using Terraform — from networks to Kubernetes clusters. Build reusable modules, manage state, and deploy scalable environments exactly like real DevOps teams do in production.

◈ Roles you'll qualify for after this track

⚙️

DevOps Engineer

₹6L – ₹18L

☁️

Cloud Engineer

₹8L – ₹20L

📦

Platform Engineer

₹12L – ₹25L

📈

Site Reliability Engineer

₹10L – ₹24L

🔄

Release / Build Engineer

₹6L – ₹16L

Curriculum

8 Modules.
Real Production Scenarios.

Every module is built around real DevOps situations — broken pipelines, failed deployments, scaling issues, and cloud outages. You won’t follow tutorials — you’ll debug, fix, and deploy systems the way engineers do in production.

01

⚙️

Linux, Networking & Git — Production-Grade DevOps Foundations

⏱ 5 sessions🔬 Labs: Production Debugging + Git Failure Recovery

+

Linux deep fundamentals — file system hierarchy, permissions, processes, services (systemd), package management

Process & resource troubleshooting — CPU, memory, disk, ports, process kill & recovery

Networking for DevOps — DNS flow, HTTP/HTTPS lifecycle, ports, reverse proxy, load balancing concepts

SSH, secure access, key management, and remote server hardening basics

Git & GitHub — branching strategies (feature, release, hotfix), PR workflow, merge conflicts, revert/reset

How applications run in real systems — runtime, environment variables, dependencies, logs

Intro to DevOps lifecycle — developer → CI → CD → infra → monitoring (mental model building)

🏭

Scenario Lab 1 (Production Debugging): You join a startup where a Node.js application is crashing randomly on a Linux server. Investigate logs, check running processes, analyze memory/CPU usage, identify root cause (permissions, port conflict, or dependency issue), and restore the application — exactly like a real on-call DevOps engineer.

🔥

Scenario Lab 2 (Git Disaster Recovery): A developer force-pushed broken code to the main branch, causing production failure. Use Git history, logs, and branching strategies to identify the issue, perform rollback, and restore a stable version — simulating real production incident handling.

🌐

Scenario Lab 3 (Networking Failure Debugging): Application is running but not accessible via browser. Debug DNS resolution, port binding, firewall/security group issues, and reverse proxy misconfiguration to restore access — real-world production issue simulation.

🎯

Certification Lab (AZ-104 / Cloud Foundations): Set up a Linux VM, configure SSH access, open required ports, deploy an application, and verify connectivity — aligned with Azure VM, networking, and compute fundamentals required for AZ-104 and real cloud environments.

02

🔄

CI/CD Engineering — Multi-Platform Pipelines, Release Strategies & DevSecOps

⏱ 6 sessions🔬 Labs: Multi-Tool Pipelines + Production Failures

+

CI/CD deep dive — build, test, artifact, deploy lifecycle (real production flow)

Azure DevOps Pipelines — YAML pipelines, stages, approvals, environments, service connections

Jenkins — pipeline as code (Jenkinsfile), agents, plugins, distributed builds

GitHub Actions — workflows, runners, secrets, reusable workflows

Multi-stage pipelines — dev → staging → production with approvals & gates

Artifact management & versioning — build once, deploy everywhere principle

Secrets management — environment variables, secure storage, key vault basics

Deployment strategies — rolling, blue-green, canary deployments

Pipeline debugging — logs, failed stages, dependency issues, retry strategies

Intro to DevSecOps — integrating SAST (SonarQube), SCA, and basic security checks in pipeline

🏭

Scenario Lab 1 (Pipeline Failure Debugging): A production pipeline is failing after a recent commit. Analyze pipeline logs across stages (build/test/deploy), identify failure root cause (dependency issue, test failure, or config error), fix it, and successfully deploy — simulating a real DevOps incident.

🚀

Scenario Lab 2 (Multi-Stage Pipeline with Approval Gates): Build a complete CI/CD pipeline using Azure DevOps — code commit triggers build → test → deploy to staging → manual approval → production deployment. Implement environment-based configurations and secure secrets.

🔁

Scenario Lab 3 (Blue-Green Deployment & Rollback): Deploy a new version of an application using blue-green strategy. Route traffic to new version, simulate failure, and perform instant rollback to stable version — exactly how production releases are managed.

🔐

Scenario Lab 4 (DevSecOps Integration): Integrate SonarQube and dependency scanning into pipeline. Pipeline should fail if vulnerabilities are detected. Fix issues and re-run pipeline to pass security checks — introducing real DevSecOps workflow.

⚙️

Scenario Lab 5 (Multi-Tool CI/CD Setup): Implement the same pipeline using Jenkins and GitHub Actions. Compare workflows, execution, and debugging across tools — giving real industry flexibility.

🎯

Certification Lab (AZ-400 Prep): Create an Azure DevOps pipeline with multi-stage deployment, approvals, artifact management, and secure variables — aligned with Azure DevOps Engineer (AZ-400) certification requirements.

03

🐳

Docker & Container Engineering — Build, Optimize, Secure & Debug Production Containers

⏱ 6 sessions🔬 Labs: Real Container Failures, Optimization & Security

+

Containerization fundamentals — images vs containers, namespaces, isolation, runtime lifecycle

Docker deep dive — images, containers, volumes, networks, logs, exec & troubleshooting

Writing production-grade Dockerfiles — multi-stage builds, layer optimization, caching

Containerizing real applications — Node.js / Python with environment variables & configs

Docker Compose — multi-container applications (app + database + cache)

Container networking — bridge, host, service-to-service communication

Container debugging — logs, crash analysis, dependency failures, port conflicts

Image optimization — reducing size, improving build time, secure base images

Container security basics — image scanning (Trivy), vulnerabilities, secrets handling

Container registry workflows — pushing/pulling images (Docker Hub / Azure Container Registry)

🏭

Scenario Lab 1 (Container Crash Debugging): A containerized application is failing in production. Analyze container logs, inspect runtime issues (missing dependencies, incorrect entrypoint, environment variables), fix the Dockerfile, and redeploy a working container.

🧩

Scenario Lab 2 (Multi-Container System Failure): Convert a monolithic application into a multi-container setup using Docker Compose (app + database + cache). Resolve service communication issues, networking problems, and startup dependencies — just like real microservices environments.

⚡

Scenario Lab 3 (Image Optimization & Performance): A container image is too large and slow to deploy. Refactor Dockerfile using multi-stage builds, optimize layers, reduce size, and improve build speed — simulating real production optimization.

🔐

Scenario Lab 4 (Container Security & Vulnerability Fix): Scan container images using Trivy, identify vulnerabilities, fix insecure dependencies/base images, and rebuild secure containers — introducing real DevSecOps practices.

📦

Scenario Lab 5 (Registry & Deployment Workflow): Build Docker images, tag versions properly, push to Docker Hub / Azure Container Registry, and pull from registry for deployment — simulating real CI/CD integration flow.

🎯

Certification Lab (CKA / Cloud Prep): Build, run, and manage containerized applications, optimize images, and troubleshoot issues — aligned with Kubernetes environments and real-world DevOps workflows.

04

☸️

Kubernetes — Production Orchestration, Scaling, Security & Cluster Debugging

⏱ 7 sessions🔬 Labs: Real Cluster Failures, Scaling & Traffic Management

+

Kubernetes architecture — control plane, nodes, scheduler, etcd (how cluster actually works)

Core resources — Pods, Deployments, ReplicaSets, Services (ClusterIP, NodePort, LoadBalancer)

kubectl mastery — debugging, logs, exec, describe, troubleshooting workflow

YAML deep dive — writing production-ready manifests (labels, selectors, probes, resources)

ConfigMaps & Secrets — managing configuration securely in production

Ingress & traffic routing — NGINX ingress controller, path-based routing, domain mapping

Auto-scaling — HPA (Horizontal Pod Autoscaler), resource tuning, load testing basics

Persistent storage — volumes, PersistentVolumes, PersistentVolumeClaims

Helm — package management for Kubernetes (deploying real applications)

RBAC & security basics — roles, role bindings, service accounts

Rolling updates, rollout strategies & zero-downtime deployments

Cluster troubleshooting — crash loops, image pull errors, networking failures

🏭

Scenario Lab 1 (CrashLoopBackOff Debugging): A production application is stuck in CrashLoopBackOff. Investigate logs, check environment variables, config issues, and resource limits. Fix the deployment and restore application availability.

🌐

Scenario Lab 2 (Service Not Accessible): Application is running inside cluster but not accessible externally. Debug service type, ingress configuration, port mapping, and DNS routing to restore access.

📈

Scenario Lab 3 (Auto-Scaling Under Load): Application fails under high traffic. Configure HPA, define resource limits, simulate load, and ensure system scales automatically without downtime.

🔐

Scenario Lab 4 (Secrets & Config Fix): Application fails due to missing environment variables or secrets. Implement ConfigMaps and Secrets properly, update deployment, and restore functionality.

📦

Scenario Lab 5 (Helm Deployment): Deploy a production-grade application using Helm charts. Customize values, manage releases, and upgrade application safely.

⚠️

Scenario Lab 6 (RBAC Misconfiguration): A service is failing due to permission issues. Debug RBAC roles and bindings, fix access control, and restore service communication.

🎯

Certification Lab (CKA Prep): Deploy, expose, scale, and troubleshoot applications using kubectl and YAML — covering real exam scenarios including debugging pods, managing resources, and cluster operations.

05

☁️

Cloud Engineering (Azure-Focused) — Production Architecture, Networking & Cost Optimization

⏱ 7 sessions🔬 Labs: Real Cloud Deployment, Outage Debugging & Cost Control

+

Azure core services — Virtual Machines, Storage Accounts, Networking (AZ-104 alignment)

Azure networking deep dive — VNets, subnets, NSG, route tables, private vs public access

Secure access — Azure AD basics, RBAC, managed identities, key vault integration

Compute & scaling — VMSS (Virtual Machine Scale Sets), load balancer, high availability

Application architecture — multi-tier deployment (web + app + database)

Ingress & traffic flow — Application Gateway, reverse proxy, DNS mapping

Storage & data — blob storage, disks, backups, redundancy strategies

Monitoring basics — Azure Monitor, metrics, logs, alerts

Cost optimization (FinOps) — resource sizing, budgeting, cost alerts, avoiding over-provisioning

AWS mapping (quick reference) — EC2, VPC, IAM vs Azure equivalents (for multi-cloud awareness)

🏭

Scenario Lab 1 (Production Deployment on Azure): Deploy a production-grade application on Azure — create VM, configure NSG, open required ports, attach public IP, and ensure secure and scalable access.

🌐

Scenario Lab 2 (Networking Failure Debugging): Application is deployed but not accessible. Debug NSG rules, subnet configurations, routing issues, and DNS mapping to restore connectivity — simulating real cloud outage.

📈

Scenario Lab 3 (Scaling & High Availability): Application receives heavy traffic and fails. Configure load balancer and VM scale sets, ensure high availability, and validate system stability under load.

🔐

Scenario Lab 4 (IAM & Access Issue): A service fails due to permission issues. Debug RBAC roles, assign correct permissions, and restore access using managed identities — real enterprise scenario.

💸

Scenario Lab 5 (Cost Optimization & Leak Detection): Cloud bill spikes unexpectedly. Analyze resources, identify unused/over-provisioned services, optimize sizing, and implement cost alerts — simulating real FinOps responsibility.

🧩

Scenario Lab 6 (Multi-Tier Architecture): Design and deploy a 3-tier architecture (frontend + backend + database) with proper network segmentation, secure communication, and controlled access.

🎯

Certification Lab (AZ-104 Prep): Configure Azure VM, networking, storage, RBAC, and monitoring — aligned with Azure Administrator (AZ-104) certification scenarios and real cloud engineering roles.

06

🏗️

Infrastructure as Code (Terraform) — Scalable, Secure & Production-Ready Automation

⏱ 6 sessions🔬 Labs: Multi-Env Infra, Drift Fixing & CI/CD Integration

+

Terraform fundamentals — providers, resources, variables, outputs, dependency graph

State management — local vs remote state, backend (Azure Storage), state locking

Provisioning Azure infrastructure using Terraform — VM, networking, load balancer

Modular architecture — reusable modules for scalable infrastructure design

Workspaces & environments — dev, staging, production separation

Terraform lifecycle — plan, apply, destroy, refresh, import

Handling drift — detecting and fixing infrastructure mismatch

Secrets & sensitive data — variables, key vault integration, secure practices

CI/CD integration — running Terraform in Azure Pipelines / GitHub Actions

Best practices — idempotency, naming conventions, versioning, folder structure

🏭

Scenario Lab 1 (Multi-Environment Setup): A company needs dev, staging, and production environments. Design Terraform modules, use workspaces, and provision infrastructure consistently across environments — ensuring scalability and maintainability.

🔁

Scenario Lab 2 (Drift Detection & Fix): Infrastructure was manually modified in Azure causing drift. Use Terraform plan to detect differences, fix inconsistencies, and bring infrastructure back to desired state — simulating real production issue.

🔐

Scenario Lab 3 (Secure Infrastructure Provisioning): Avoid hardcoding secrets. Integrate Terraform with Azure Key Vault, manage sensitive variables securely, and deploy infrastructure following security best practices.

⚙️

Scenario Lab 4 (CI/CD Integration): Integrate Terraform with Azure DevOps pipeline. Automate infrastructure provisioning with approval gates and ensure controlled deployments — real enterprise workflow.

📦

Scenario Lab 5 (Module Refactoring & Optimization): Refactor a poorly structured Terraform project into reusable modules. Improve readability, maintainability, and scalability — simulating real enterprise refactoring.

🎯

Certification Lab (Terraform Associate Prep): Write Terraform configurations, manage remote state, use modules, and provision infrastructure — aligned with HashiCorp Terraform Associate certification requirements.

07

📊

Monitoring, Logging & SRE — Observability, Alerting & Production Incident Response

⏱ 6 sessions🔬 Labs: Real Incident Debugging, Alerting & Root Cause Analysis

+

Observability fundamentals — metrics, logs, traces (how systems are monitored in production)

Prometheus — metrics collection, exporters, querying with PromQL

Grafana — dashboards, visualization, alert rules, real-time monitoring

Centralized logging — ELK stack (Elasticsearch, Logstash, Kibana)

Kubernetes monitoring — cluster health, pod metrics, node-level monitoring

Alerting strategy — thresholds, alert fatigue, escalation policies

SRE concepts — SLA, SLO, SLIs, error budgets

Incident management — detection → response → RCA (root cause analysis)

Distributed tracing basics — request flow across services (intro to modern observability)

Integrating monitoring with CI/CD & cloud (Azure Monitor basics)

🚨

Scenario Lab 1 (High Latency Incident): Application is slow and users are complaining. Use Prometheus metrics and Grafana dashboards to identify bottlenecks (CPU, memory, DB latency), fix the issue, and restore performance.

🔎

Scenario Lab 2 (Log-Based Debugging): System is failing intermittently. Use ELK stack to analyze logs across services, correlate events, identify root cause, and fix the issue — simulating real production debugging.

📉

Scenario Lab 3 (Alert Misconfiguration & Noise): Too many alerts are firing causing alert fatigue. Optimize alert rules, set proper thresholds, and design meaningful alerts — real SRE challenge.

☸️

Scenario Lab 4 (Kubernetes Monitoring Failure): Pods are restarting but no one knows why. Monitor pod metrics, check logs, correlate events, and fix underlying issue — real cluster debugging scenario.

📊

Scenario Lab 5 (SLO & Error Budget Design): Define SLA/SLO for an application, track SLIs using metrics, and calculate error budget. Decide when to stop releases due to instability — real SRE decision-making.

🎯

Certification Lab (CKA / SRE Practices): Monitor Kubernetes cluster health, configure alerts, and troubleshoot issues using metrics and logs — aligned with real DevOps and SRE responsibilities.

08

🚀

Capstone Project, War Room Simulation & Career Conversion — From Learner to DevOps Engineer

⏱ 8 sessions🔬 Labs: End-to-End System + Production Incident Simulation

+

Designing a real-world DevOps architecture — CI/CD → Docker → Kubernetes → Terraform → Azure

System design basics — high availability, scalability, fault tolerance

End-to-end pipeline integration — code → build → scan → deploy → monitor

DevSecOps in practice — integrating security checks into full workflow

Production deployment strategies — blue-green, rolling updates, rollback

Incident management lifecycle — detection → debugging → RCA → resolution

How real DevOps teams work — tickets, releases, incidents, ownership

Portfolio building — GitHub projects, documentation, architecture diagrams

Interview preparation — real DevOps scenarios, system questions, troubleshooting rounds

Resume, LinkedIn & job strategy — positioning as DevOps engineer

🏗️

Capstone Lab (End-to-End Production System): Build a complete DevOps system — containerize an application, create CI/CD pipeline (Azure/Jenkins/GitHub), integrate security scans, provision infrastructure using Terraform, deploy on Kubernetes (AKS), and monitor using Prometheus/Grafana. This becomes your portfolio project.

🔥

War Room Simulation 1 (Production Outage): System goes down during peak traffic. Identify issue (pod crash, infra failure, or pipeline bug), debug using logs & metrics, fix the system, and restore service — real incident handling simulation.

⚠️

War Room Simulation 2 (Broken Deployment): A new release breaks production. Perform rollback using blue-green strategy, stabilize system, and analyze what went wrong — exactly like real DevOps release failure.

🔐

War Room Simulation 3 (Security Failure): Pipeline fails due to detected vulnerability. Fix code/config, update dependencies, and pass security gates — simulating real DevSecOps enforcement.

💸

War Room Simulation 4 (Cost Spike Incident): Cloud bill increases drastically. Analyze infrastructure usage, identify resource leak, optimize cost, and implement budget alerts — real FinOps scenario.

🧠

War Room Simulation 5 (RCA Presentation): After fixing incidents, prepare a Root Cause Analysis report and present it like a real DevOps engineer — including timeline, issue, fix, and prevention steps.

🎯

Career Lab (Interview + Portfolio + Certification Strategy): Prepare your GitHub portfolio, present architecture, solve real DevOps interview scenarios, and get roadmap for AZ-104, AZ-400, and Terraform Associate certifications.

Engineering Progress

8 modules · 45+ sessions · 14 weeks

Transformation Journey100%

01 ⚙️ DevOps Foundations

○

02 🔄 CI/CD Engineering

○

03 🐳 Container Engineering

○

04 ☸️ Kubernetes

○

05 ☁️ Cloud Engineering

○

06 🏗️ Infrastructure as Code

○

07 📊 Observability & SRE

○

08 🚀 Capstone & War Room

○

Enroll Now →

Next cohort · Sep 08, 2026 · 22 seats left

Lab Environment

Production-Realistic.
Browser-Based.

No VPN. No local VM. No hardware requirements. Your entire enterprise lab runs in the browser — including the tools, the targets, and the terminal.

bash — Eduvoxy Lab Terminal · Module 04

● LIVE

Industry Tools & Platforms You’ll Use in Labs

⚙️Linux (System Debugging, Process Monitoring, Server Management)

🔗Git & GitHub (Branching Strategy, PR Workflow, Production Rollbacks)

🔄Azure Pipelines / GitHub Actions / Jenkins (Multi-Stage CI/CD, Approvals, Release Strategies)

🐳Docker (Multi-Stage Builds, Image Optimization, Runtime Debugging)

☸️Kubernetes (Scaling, Ingress, Secrets, Helm, Cluster Debugging)

☁️Azure (VMs, Networking, RBAC, AKS, Production Architecture)

🌐AWS (EC2, VPC, IAM, S3 — Cross-Cloud Mapping)

🏗️Terraform (Modules, Remote State, Workspaces, CI/CD Integration)

🔐DevSecOps (SonarQube, Trivy, Dependency Scan, Secrets Detection)

📊Prometheus (Metrics, Alerting, Performance Monitoring)

📈Grafana (Dashboards, Visualization, Alert Management)

🗂️ELK Stack (Centralized Logging, RCA, Incident Debugging)

🚀NGINX / Load Balancers (Traffic Routing, Reverse Proxy, High Availability)

Production System Simulation — Build, Secure, Deploy, Monitor & Debug (Module 08 Capstone)

GitHub Repo · Code Commit, Branching & PR Workflow

CI/CD Pipeline · Build, Test, Security Scan (Azure / Jenkins / Actions)

Docker Registry · Image Build, Optimization & Versioning

Terraform · Infrastructure Provisioning (VM, Network, AKS)

Kubernetes Cluster · Deployment, Scaling, Secrets & Helm

Load Balancer / Ingress · Traffic Routing & High Availability

Azure Cloud · Production Architecture, Networking & RBAC

Monitoring Stack · Prometheus, Grafana, Alerts & RCA

War Room Simulation · Incident Debugging, Rollback & Recovery

Certifications

Clear the Cert.
Already Think Like an Engineer.

Our curriculum is deeply aligned with real DevOps certifications — but we go beyond exam prep. By the time you attempt these certifications, you've already built, deployed, debugged, and scaled production systems.

DevOps Core

AZ-400

Microsoft Azure DevOps Engineer Expert

IssuerMicrosoft

Exam Format40–60 MCQ · 120 mins

Our Pass Rate93%

Role ImpactDevOps Engineer

Curriculum Coverage96%

Foundation

AZ-104

Microsoft Azure Administrator

IssuerMicrosoft

Exam Format40–60 MCQ · 120 mins

Our Pass Rate94%

Role ImpactCloud / DevOps Engineer

Curriculum Coverage94%

Hands-On Expert

CKA

Certified Kubernetes Administrator

IssuerCloud Native Computing Foundation

Exam FormatHands-on Lab · 2hrs

Our Pass Rate92%

Role ImpactKubernetes / Platform Engineer

Curriculum Coverage95%

Automation Focus

Terraform

HashiCorp Certified: Terraform Associate

IssuerHashiCorp

Exam Format60 MCQ · 60 mins

Our Pass Rate96%

Role ImpactDevOps / IaC Engineer

Curriculum Coverage97%

👨‍💻

Rajeev Ranjan

DevOps & DevSecOps Engineer · Cloud & Infrastructure Specialist

6+ Years Industry Experience

Rajeev has worked on building and securing production-grade systems across cloud and enterprise environments. His expertise spans CI/CD pipelines, Kubernetes, infrastructure automation using Terraform, and DevSecOps integration across the SDLC. He has designed scalable architectures on AWS and Azure, automated deployments for high-availability systems, and implemented security practices in real-world DevOps pipelines. At Eduvoxy, he brings real production scenarios — not theory — into every session.

50+Pipelines Built

100+Students Mentored

4.9★Rating

You Don't Just Get a Mentor.
You Get a Practitioner.

Rajeev isn't just teaching DevOps — he's actively building and managing real systems. Every 1:1 session is based on real production issues, deployment failures, and debugging scenarios — the same situations you'll face in your job.

🎯

Mock Technical Interviews

After every module, a live session where Rajeev simulates real DevOps interviews — pipelines, Kubernetes debugging, and cloud scenarios.

📋

Hands-on Performance Reviews

Detailed feedback on your deployments, pipelines, and infrastructure setups — with exact improvements required for production readiness.

🗺️

Personalised DevOps Roadmap

Get a clear path — AWS, Azure, Kubernetes, certifications, and job roles — tailored to your background and goals.

🔗

Industry Exposure & Referrals

Top performers get guidance for real job opportunities and exposure to hiring expectations across DevOps and cloud roles.

Upcoming Cohort

Seats Are
Limited.

◈ DevOps Career Track · Cohort 01

DevOps Engineer Program — From Zero to Production

🗓 Sep 08, 2026

⏱ 14 Weeks

📅 Sat–Sun 10AM + Wed 9PM IST

👥 Batch: 28 students max

00Days

00Hours

00Mins

00Secs

Secure My Seat (PRO) → Talk to Counsellor

22 Seats Left

Out of 28 total seats this cohort

● Filling Fast

DevOps Alumni

What Graduates
Say.

✓ AWS SAA Cleared · DevOps Engineer @ MNC

"The Kubernetes and CI/CD modules alone were worth it. I was deploying real applications on a live cluster with auto-scaling and zero downtime — not just following tutorials. My AWS certification felt easy after this."

✓ AZ-104 Cleared · Cloud Engineer

"I came from a networking background, but the real shift happened when I started debugging failed deployments and cloud outages in AWS & Azure labs. The 1:1 sessions showed me how real engineers think — not just how tools work."

✓ CKA Cleared · Platform Engineer

"The capstone was harder than my interviews. After building a complete CI/CD → Docker → Kubernetes → Cloud system and handling failures, every interview felt practical. This is not a course — it's real experience."

DevOps Track · Pricing

One Track.
Three Ways In.

All plans include the full 18-week DevOps curriculum — CI/CD, Docker, Kubernetes, AWS, Azure, and Terraform — along with production labs and lifetime recordings. Plans differ only in mentorship, career support, and job readiness acceleration.

Starter

Core DevOps training · Limited mentorship

₹17,999₹22,999

Save ₹5,000

Pay once · Own forever

✓18-week live curriculum

✓Production DevOps labs (CI/CD, Docker, Cloud)

✓Lifetime session recordings

✓Eduvoxy completion certificate

✓Career roadmap session (1×)

◐1:1 mentor — 2 sessions only

–Mock interviews

–Resume & LinkedIn rebuild

–Hiring partner referrals

–50% industry cert discount

Enroll — Starter →

or from ₹6,500/mo · 0% EMI

★ Most Popular

Pro

Full DevOps career support · Most students choose this

₹24,999 ₹29,999

Save ₹5,000

Pay once · Own forever

✓18-week live curriculum

✓Production DevOps labs (Kubernetes, Cloud, CI/CD)

✓Lifetime session recordings

✓Eduvoxy completion certificate

✓Career roadmap session

✓1:1 mentor — after every module

✓Mock interviews (every module)

✓Resume & LinkedIn rebuild

✓Hiring partner referrals

✓50% industry cert discount

Enroll — Pro →

or from ₹9,000/mo · 0% EMI

Elite

White-glove DevOps mentorship · Dedicated mentor

₹34,999₹39,999

Save ₹5,000

Pay once · Own forever

✓Everything in Pro

✓Dedicated mentor — same person always

✓Priority lab access

✓90-day placement SLA

✓Salary negotiation coaching

✓Exclusive hiring partner intros

✓Annual career check-in (forever)

–

Enroll — Elite →

or from ₹12,500/mo · 0% EMI

🔒Secure checkout · Razorpay

↩️7-day full refund — no questions

📞Free counselling call before you pay

🎓DevOps-ready outcomes · Real production experience

Not sure which plan is right for you?

Most career-changers choose Pro. Starter works if you're supplementing existing experience. Elite is for candidates who want maximum support and the fastest path to an offer.

Talk to a Counsellor →

Still Have Questions?

Most answers are below. If yours isn't, talk to a counsellor — no sales pressure, just honest answers.

💬 Chat with a Counsellor →

Do I need prior DevOps experience?

+

No prior DevOps experience is required. However, basic familiarity with Linux, networking, or programming helps. We start from fundamentals and gradually move into CI/CD, Docker, Kubernetes, and cloud. If you're unsure, talk to us — we'll tell you honestly whether you're ready.

Are the sessions recorded? What if I miss one?

+

Every session is recorded and uploaded within a few hours. You get lifetime access — no expiry. You can rewatch anytime. That said, attending live sessions is highly recommended for real-time debugging, discussions, and 1:1 interactions.

What exactly will I build during the program?

+

You’ll build a complete production-ready system — from CI/CD pipelines to Docker containers, Kubernetes deployments, and cloud infrastructure on AWS/Azure. By the end, you’ll have a real project that you can show in interviews.

What happens in the 1:1 mentor sessions?

+

After each module, your mentor reviews your work — pipelines, deployments, infrastructure — and challenges your approach. You’ll also go through real interview-style questions, debugging scenarios, and get actionable feedback to improve before the next module.

Is the lab really browser-based? Do I need a powerful system?

+

Yes — everything runs in the browser. No local setup, no VM, no heavy system required. You get instant access to real DevOps environments — Kubernetes clusters, cloud setups, and CI/CD pipelines — from your browser.

Which certifications does this program prepare me for?

+

The curriculum is aligned with AWS SAA, Azure AZ-104, Kubernetes CKA, and Terraform Associate. More importantly, you’ll gain hands-on experience that actually helps you clear these certifications — not just theory.

Will I be job-ready after this program?

+

If you complete all labs, projects, and mentorship sessions seriously — yes. You’ll have real-world experience in CI/CD, Kubernetes, cloud, and infrastructure automation. But like any skill, outcomes depend on your effort.

Does Eduvoxy guarantee placement?

+

No — and anyone promising guaranteed placement isn’t being honest. What we do provide: mock interviews, portfolio building, resume optimization, and referrals to hiring partners for top performers. We prepare you for real hiring — not just promises.

How is this different from other DevOps courses?

+

Most courses teach tools in isolation. We train you to run production systems — handling failures, debugging issues, and deploying real applications. That’s the difference between learning DevOps and actually doing DevOps.

Can I switch careers into DevOps with this?

+

Yes — many learners come from support, networking, or development backgrounds. The key is consistency. If you complete the labs and understand the systems, you can transition into DevOps or cloud roles.

Can I pay in instalments (EMI)?

+

Yes, we offer 0% EMI options with flexible payment plans. You can also speak to a counsellor for current offers or scholarship options if needed.

AI & Emerging Tech

Security & Reliability

Engineering Tracks

Cloud & Infrastructure

Become a
DevOps
Engineer.

Not Just Trained.
Production-Ready.

8 Modules.
Real Production Scenarios.

Production-Realistic.
Browser-Based.

Clear the Cert.
Already Think Like an Engineer.

Why Eduvoxy
Outclasses the Rest

You Don't Just Get a Mentor.
You Get a Practitioner.

Seats Are
Limited.

What Graduates
Say.

One Track.
Three Ways In.

Still Have Questions?

AI & Emerging Tech

Security & Reliability

Engineering Tracks

Cloud & Infrastructure

Become a DevOps Engineer.

Not Just Trained.Production-Ready.

8 Modules.Real Production Scenarios.

Production-Realistic.Browser-Based.

Clear the Cert.Already Think Like an Engineer.

You Don't Just Get a Mentor.You Get a Practitioner.

Seats AreLimited.

What GraduatesSay.

One Track.Three Ways In.

Still Have Questions?

Become a
DevOps
Engineer.

Not Just Trained.
Production-Ready.

8 Modules.
Real Production Scenarios.

Production-Realistic.
Browser-Based.

Clear the Cert.
Already Think Like an Engineer.

You Don't Just Get a Mentor.
You Get a Practitioner.

Seats Are
Limited.

What Graduates
Say.

One Track.
Three Ways In.