Why Every Serious IT Professional in Pune Needs DevOps Skills Right Now

Think about what happens when a developer finishes writing a feature. Ten years ago, that code would sit in a queue. Someone would manually test it. Someone else would manually deploy it to a staging server. A few weeks later — if nothing broke — it might make it to production. The whole process was slow, error-prone, and depended entirely on people doing repetitive tasks perfectly every single time.

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DevOps changed that model completely. Today, the moment a developer pushes code to GitHub, an automated pipeline kicks off — it runs tests, scans for security vulnerabilities, checks code quality, builds a Docker container, pushes it to a registry, deploys it to a Kubernetes cluster, and starts monitoring it in production. This entire sequence happens in under 20 minutes without a single person touching a button. That is what DevOps does: it automates the software delivery lifecycle so completely that teams can deploy dozens of times a day with more reliability than they used to achieve with monthly releases.

In Pune's IT ecosystem — which spans product companies, IT services firms, financial technology companies, and manufacturing technology groups — DevOps has shifted from "nice to have" to "non-negotiable." Companies are not just hiring DevOps engineers; they are actively rebuilding their entire engineering culture around DevOps practices. And they are paying well for the people who can lead that transformation. A DevOps engineer with solid Kubernetes and Terraform skills in Pune earns more than most Java developers with double the years of experience.

The Aapvex DevOps programme is built specifically for the Pune job market. We cover the exact tools, practices, and project scenarios that Pune's hiring managers test for in interviews. From your first Jenkins pipeline to your first Kubernetes cluster to your first Terraform-provisioned AWS environment, every lab is designed to be the kind of work you will do in your first DevOps job. Call 7796731656 to speak with a counsellor today.

500+
Students Placed
4.9★
Google Rating
8
Course Modules
₹20L+
Experienced DevOps Salary

What Software Delivery Looks Like Without DevOps — and With It

The clearest way to understand why DevOps matters is to compare the two worlds side by side. This is the conversation you will walk into on day one at your new DevOps job:

❌ Without DevOps

  • Monthly or quarterly releases only
  • Manual deployments — someone stays up all night
  • Testing happens at the end — bugs caught too late
  • Dev and Ops teams blame each other when things break
  • Configuration drift — servers snowflake over time
  • Scaling means raising a ticket and waiting a week
  • Rollback takes hours and requires an all-hands call
  • Monitoring is a separate team's responsibility
  • Infrastructure documented in someone's head

✅ With DevOps

  • Multiple deployments per day, fully automated
  • CI/CD pipeline: commit → test → deploy in 15 minutes
  • Tests run on every commit — bugs caught at the source
  • Dev and Ops share ownership of the full lifecycle
  • Infrastructure as code — environments are identical
  • Kubernetes autoscaling handles load automatically
  • One command rolls back to any previous version
  • Every team owns their service's monitoring and alerts
  • All infrastructure defined in Terraform, version-controlled

The DevOps CI/CD Pipeline — What You Will Build in This Course

A CI/CD pipeline is the backbone of modern software delivery. Here is the exact type of pipeline you will design, build, and run during this programme — the same kind that runs at Infosys, Persistent, ThoughtWorks, and every modern IT team in Pune:

💻Code Commit
Git / GitHub
→
⚙️CI Trigger
Jenkins
→
🧪Unit Tests
JUnit / pytest
→
🔍Code Quality
SonarQube
→
🐳Docker Build
Dockerfile
→
📦Push Image
AWS ECR
→
☸️K8s Deploy
EKS / Helm
→
📊Monitor
Prometheus

Every stage of this pipeline — the Git webhook trigger, the Jenkins Jenkinsfile, the Docker build optimisation, the SonarQube quality gate, the ECR image push, the Kubernetes rolling deployment, and the Prometheus alerting — is built hands-on in our lab environment. You will know exactly how each piece works and how to troubleshoot it when something goes wrong, because it will go wrong in the lab before it goes wrong in your job.

DevOps Tools You Will Master in This Programme

This is not a course that gives you a surface tour of tools and sends you to YouTube for the rest. Every tool below is covered from first principles through to production-ready implementation. When you walk into a DevOps interview and they ask "have you worked with Kubernetes?" — you will say yes and mean it:

🐧
Linux & Bash
Shell scripting, cron, permissions
🌿
Git & GitHub
Branching, PRs, GitFlow
⚙️
Jenkins
CI/CD pipelines, Jenkinsfile
🐳
Docker
Containers, Compose, registry
☸️
Kubernetes
Pods, deployments, EKS, Helm
📡
Ansible
Playbooks, roles, inventory
🏗️
Terraform
IaC, modules, state management
☁️
AWS
EC2, EKS, ECR, VPC, IAM
📊
Prometheus
Metrics, alerting, PromQL
📈
Grafana
Dashboards, visualisation
🔍
SonarQube
Code quality, security gates
🔄
ArgoCD
GitOps, continuous delivery

Course Curriculum — 8 Modules, Zero Fluff

Every module is structured the same way: concept → hands-on lab → mini-project → interview prep for that topic. By the end of 8 modules, you have built an actual DevOps portfolio — not screenshots, but live running pipelines and infrastructure that any interviewer can watch you demo.

1
Linux Fundamentals & Shell Scripting for DevOps Engineers
Every DevOps tool — Docker, Kubernetes, Ansible, Terraform — runs on Linux and is managed through the terminal. If you are not comfortable at the Linux command line, you will struggle with everything that follows. This module makes sure that by the end of week two, the terminal feels like home.

We start with the Linux filesystem hierarchy — understanding why /etc, /var, /opt, and /home exist and what kinds of files belong in each. File permissions are covered in depth because permission errors are one of the most common causes of broken deployments — you will understand chmod, chown, sticky bits, and umask until you can read a permissions string without thinking. Process management with ps, top, kill, systemctl, and journalctl is practised until troubleshooting a runaway process or a failing service feels routine.

Shell scripting is treated as a professional skill, not an afterthought. We write real automation scripts: a deployment script that pulls a Docker image and restarts a service, a log rotation and archiving script, a disk usage monitoring script that sends an alert when space drops below a threshold, and a server health-check script that can be run across multiple servers using SSH. Variable handling, conditionals, loops, functions, exit codes, and error handling are all covered with the discipline of someone who has debugged production scripts at 2 AM.
Linux CLIBash ScriptingFile Permissionssystemctlcron JobsSSHProcess Management
2
Git, GitHub & Version Control — Branching Strategies & Team Collaboration
Version control is not just a developer tool — it is the foundation of the entire DevOps workflow. Every Jenkinsfile, every Dockerfile, every Kubernetes manifest, every Terraform configuration, every Ansible playbook lives in Git. If you do not understand Git deeply, you cannot do DevOps properly.

We start from the basics — init, add, commit, push, pull — and move quickly into the workflow patterns that matter in real teams. Branching strategies are covered in detail: GitFlow (with its feature, develop, release, and hotfix branches) and the simpler GitHub Flow (short-lived feature branches, pull requests, and direct merges to main) — understanding when each approach is appropriate. Merge conflicts are simulated and resolved — not just explained — because every DevOps engineer hits merge conflicts in their first week on the job.

GitHub is covered as a collaboration and automation platform: pull request workflows, code review processes, branch protection rules (requiring reviews and passing CI checks before merging), GitHub Actions for lightweight automation, and GitHub webhooks that trigger Jenkins pipelines automatically when code is pushed. Git hooks — scripts that run automatically before or after specific Git events — are used to enforce commit message formats and run basic checks locally before code reaches the remote repository. By the end of this module, you will manage a multi-branch repository, run pull request workflows, and have GitHub triggering your first automated pipeline.
Git BranchingGitFlowPull RequestsGitHub ActionsWebhooksMerge ConflictsBranch Protection
3
Jenkins CI/CD — Building Real Automation Pipelines from Scratch
Jenkins is the most widely deployed CI/CD tool in enterprise IT — and knowing how to set up, maintain, and extend a Jenkins pipeline is one of the most valuable practical skills a DevOps engineer can have. Many candidates claim Jenkins experience in their resume; very few can actually build a production-grade Jenkinsfile from scratch. This module makes you one of those who genuinely can.

Jenkins installation and configuration on Ubuntu is covered first — setting up Jenkins master, configuring the JDK, Maven, and Docker tool integrations, managing plugins, and setting up credentials management for GitHub tokens, Docker registry passwords, and AWS access keys. Freestyle jobs are built as an introduction, then immediately replaced with Declarative Pipelines — the Jenkinsfile approach that treats your entire pipeline as version-controlled code. A complete Jenkinsfile is built stage by stage: the GitHub webhook trigger, the Maven/Gradle build stage, the JUnit test stage, the SonarQube quality analysis stage with a configurable quality gate that fails the build if coverage drops below threshold, the Docker image build stage with layer optimisation, the Docker Hub or AWS ECR push stage, and the Kubernetes deployment stage using kubectl or Helm.

Multi-branch pipeline projects — where Jenkins automatically creates and manages pipeline jobs for every branch in your GitHub repository — are configured. Shared Libraries in Jenkins — reusable Groovy code that multiple pipeline jobs can reference — are introduced for the scenario where you are managing pipelines across dozens of microservices and do not want to duplicate code. Pipeline parallelisation — running unit tests, integration tests, and code scans simultaneously rather than sequentially to halve build time — is practised. Email and Slack notifications for build success and failure are configured.
JenkinsDeclarative PipelineJenkinsfileMulti-Branch PipelineSonarQubeShared LibrariesWebhooks
4
Docker — Containers, Images, Compose & Container Best Practices
Docker is the technology that made containerisation mainstream — and it is the single most transformative tool in modern application deployment. Before Docker, "it works on my machine" was an endless source of deployment failures. After Docker, the developer's machine, the staging server, and the production cluster all run exactly the same environment. Every DevOps engineer needs to be genuinely proficient with Docker — not just able to run docker pull, but able to write optimised Dockerfiles, debug container networking issues, and manage multi-service applications with Docker Compose.

We start with the fundamental Docker architecture: the Docker daemon, the Docker client, images, containers, the Union File System that makes image layering work, and the Docker Hub registry. Writing Dockerfiles is covered as a craft — starting with a working Dockerfile and progressively refining it: choosing the right base image (the difference between using ubuntu and alpine for a Python application is an 800MB versus 50MB final image), multi-stage builds that produce a lean production image from a heavier build environment, layer caching strategy to make rebuilds fast, and the security practices of running containers as non-root users and avoiding hardcoded secrets.

Docker Compose is covered for multi-service local development environments — writing a docker-compose.yml that brings up a Python Flask application, a PostgreSQL database, a Redis cache, and an Nginx reverse proxy with a single docker compose up command. Container networking — bridge networks, host networking, and service-to-service communication in Compose — is explored hands-on with debugging exercises. Docker volumes for persistent data are configured for database containers where data must survive container restarts. Docker registries — Docker Hub, AWS ECR, and private Harbor registry — are used for storing and pulling images in pipeline scenarios.
DockerDockerfileMulti-Stage BuildDocker ComposeContainer NetworkingDocker VolumesAWS ECR
5
Kubernetes — Container Orchestration, AWS EKS & Production Deployments
Kubernetes is the operating system of the cloud — and Kubernetes skills are now the most sought-after capability in DevOps hiring across India. If Docker answers "how do I run a container?", Kubernetes answers "how do I run a thousand containers reliably, with automatic failover, rolling updates, secret management, network policies, and horizontal scaling?" This is the module where the most learning happens, and it is the module where Aapvex students most frequently tell us the interview clicked into place.

Kubernetes architecture is covered from first principles: the control plane (API server, etcd, controller manager, scheduler) and worker nodes (kubelet, kube-proxy, container runtime). This is not just theory — understanding what the scheduler does helps you understand why your pod is stuck in Pending, and understanding etcd helps you understand what cluster state actually means. Core objects are built hands-on with real YAML manifests: Pods, ReplicaSets, Deployments (with rolling update and rollback strategies), Services (ClusterIP, NodePort, LoadBalancer), ConfigMaps and Secrets, Ingress controllers with Nginx, HorizontalPodAutoscaler for automatic scaling based on CPU and memory metrics, PersistentVolumes and PersistentVolumeClaims for stateful applications, and ResourceQuotas and LimitRanges for namespace-level resource governance.

AWS EKS (Elastic Kubernetes Service) is the managed Kubernetes platform used by most enterprises — provisioning an EKS cluster using eksctl, configuring kubectl to connect to it, deploying applications, and managing node groups is all done hands-on. Helm — the package manager for Kubernetes — is used to deploy complex applications (databases, monitoring stacks, ingress controllers) with a single command and to package your own applications for repeatable deployment. ArgoCD is introduced as the GitOps continuous delivery tool — watching a Git repository and automatically applying changes to the cluster, making deployment auditable and easily reversible.
KuberneteskubectlAWS EKSHelmArgoCDHPAIngressGitOps
6
Ansible — Configuration Management, Playbooks & Automated Server Management
When you have ten servers, you can SSH in and configure them manually. When you have a hundred servers, that approach fails completely — and when one of those servers has a slightly different configuration than the others, your application behaves differently in ways that take days to debug. Ansible solves this by letting you define the desired state of your infrastructure in YAML playbooks and then enforcing that state across every server simultaneously.

Ansible's agentless architecture is the first thing we explore — understanding why Ansible only needs SSH access to target machines (unlike Puppet and Chef, which require agent software on every managed node) and what this means for adoption in environments where you cannot always install agents. The inventory system — static and dynamic inventories for AWS EC2 that automatically discover running instances by tag — is configured hands-on. Ad-hoc Ansible commands are used to run quick operations across all servers (check disk space, restart a service, copy a file) before moving to the power of playbooks.

Ansible playbooks are written for real DevOps scenarios: a playbook that provisions a fresh Ubuntu server from zero to running Nginx with a deployed application, a playbook that installs and configures the complete Docker and Docker Compose environment across a fleet of servers, a playbook that deploys a new application version with zero downtime using a rolling approach across a server group. Ansible Roles — the modular, reusable structure for organising playbook code — are used to build a reusable server hardening role that enforces security baselines (disabling root login, configuring firewall rules, setting password policies). Ansible Vault is introduced for encrypting sensitive data like passwords and API keys within playbooks. Integration between Ansible and Jenkins is demonstrated — Jenkins triggering Ansible playbooks as a deployment step in a CI/CD pipeline.
AnsiblePlaybooksAnsible RolesAnsible VaultDynamic InventoryConfiguration ManagementIdempotency
7
Terraform — Infrastructure as Code, AWS Provisioning & State Management
Terraform is the tool that made "Infrastructure as Code" a real daily practice rather than an aspirational goal. Before Terraform, provisioning infrastructure meant logging into the AWS console and clicking through forms — a process that was slow, inconsistent, and impossible to version-control. With Terraform, you write code that describes exactly what infrastructure you need, and Terraform creates it — and when you run it again on a fresh account, it creates identical infrastructure. This is a capability that every growing engineering team urgently needs and that Terraform-skilled engineers are specifically hired to provide.

Terraform's architecture is covered from the ground up: the HCL (HashiCorp Configuration Language) syntax, providers (the plugins that talk to AWS, Azure, GCP, and dozens of other platforms), resources (the infrastructure components you are creating — EC2 instances, S3 buckets, VPCs, security groups), data sources (querying existing infrastructure that Terraform does not manage), and output values for sharing information between modules. The Terraform state — the JSON file that tracks what Terraform has created — is explained carefully, including why storing it in an S3 bucket with DynamoDB locking is essential for team environments. The complete plan → apply → destroy workflow is practised until it is second nature.

Terraform modules — reusable, parameterisable blocks of Terraform code — are built for common patterns: a VPC module that creates a multi-AZ network with public and private subnets, NAT gateways, and routing; an EC2 module that provisions an application server with the correct security group and IAM role; an EKS module that provisions a production-ready Kubernetes cluster. The entire AWS infrastructure for one of the course projects — VPC, subnets, security groups, EC2 instances, an Application Load Balancer, an ECR registry, and an EKS cluster — is provisioned entirely with Terraform, giving students a complete real-world IaC portfolio piece.
TerraformHCLAWS ProviderTerraform ModulesRemote StateVPC ProvisioningEKS with Terraform
8
Monitoring, Observability & SRE Practices — Prometheus, Grafana & Alerting
Deploying an application is not the end of a DevOps engineer's job — it is the beginning of the responsibility to keep it running reliably. Monitoring and observability are what give you visibility into how your application is actually performing in production, what is about to break before it breaks, and why something broke after it breaks. This module covers the monitoring stack used by DevOps and SRE teams at Pune's leading technology companies.

The three pillars of observability — metrics, logs, and traces — are introduced conceptually before diving into the tools. Prometheus is set up as the metrics collection engine: understanding the pull-based architecture (Prometheus scrapes metrics from your applications and infrastructure rather than applications pushing to a central server), configuring scrape targets, writing PromQL queries to compute things like "CPU usage averaged over the last 5 minutes by namespace" and "HTTP error rate as a percentage of total requests," and setting up alerting rules that trigger when thresholds are breached. The Node Exporter (for system metrics) and cAdvisor (for container metrics) are deployed and integrated with Prometheus. Grafana dashboards are built from scratch — importing community dashboards for Kubernetes cluster health, then building custom dashboards for application-specific metrics that business stakeholders can actually read. Alertmanager is configured to route critical alerts to Slack and email with proper grouping, inhibition rules, and routing trees. The ELK Stack (Elasticsearch, Logstash, Kibana) is introduced for centralised log aggregation — a fundamental requirement for debugging issues across distributed microservices.

SRE (Site Reliability Engineering) principles are introduced as the cultural framework: SLOs (Service Level Objectives), SLIs (Service Level Indicators), error budgets, and the reliability versus feature velocity tradeoff that defines SRE decision-making. A complete incident response simulation — alert fires, engineer investigates using Grafana dashboards, identifies root cause in application logs, rolls back deployment using ArgoCD — is run as the final module exercise.
PrometheusGrafanaPromQLAlertmanagerELK StackSRESLO / SLIcAdvisor

Real DevOps Projects You Will Build During the Course

These are not toy demos. Every project below runs on real AWS infrastructure, uses real tools, and would be something you could legitimately discuss and demo in any DevOps interview in Pune:

🚀 End-to-End CI/CD Pipeline — Java Web App

Complete Jenkins pipeline: GitHub webhook trigger → Maven build → JUnit tests → SonarQube scan → Docker build → ECR push → Kubernetes deploy to AWS EKS. Every stage in a Jenkinsfile.

🐳 Microservices App with Docker Compose

Multi-container application (Node.js API + React frontend + PostgreSQL + Redis + Nginx) orchestrated with Docker Compose. Custom bridge network, named volumes, environment variable management.

☸️ Kubernetes Production Cluster on EKS

Full EKS cluster with Helm-deployed applications, HPA for autoscaling, Ingress with SSL termination, Secrets management, ArgoCD for GitOps deployments, and Prometheus/Grafana monitoring.

🏗️ AWS Infrastructure with Terraform

Complete production AWS environment provisioned entirely with Terraform: VPC, subnets, security groups, EC2, ALB, RDS, ECR, and EKS cluster. Remote state in S3 with DynamoDB locking.

📡 Ansible Server Automation Fleet

Ansible playbooks and roles automating full server provisioning — from fresh Ubuntu to production-ready application server. Dynamic EC2 inventory, Vault-encrypted secrets, rolling deployments.

📊 Full Observability Stack (Capstone)

Prometheus + Grafana + ELK Stack deployed on Kubernetes. Custom dashboards for app and infra metrics. Alertmanager routing to Slack. SLO tracking. Incident simulation and response exercise.

DevOps Career Paths & Salary After This Course

DevOps skills open doors across the entire technology sector in Pune. Here are the roles our graduates most commonly land — and the salary ranges you can realistically expect based on what companies are paying right now:

DevOps Engineer

₹4.5–8 LPA (Fresher) · ₹12–22 LPA (3–5 yrs)

Builds and maintains CI/CD pipelines, manages container infrastructure, handles deployments and monitoring. The most common entry point into a DevOps career. Very high demand across all company types in Pune.

Site Reliability Engineer (SRE)

₹8–14 LPA (Entry) · ₹18–35 LPA (experienced)

Google-originated role that applies software engineering to operations problems. Focuses on reliability, scalability, and incident response. Particularly common at product companies and large financial technology firms.

Cloud DevOps / Platform Engineer

₹8–15 LPA (Entry) · ₹20–38 LPA (senior)

Manages cloud-native infrastructure — Kubernetes platforms, Terraform pipelines, cloud cost optimisation. Strong Terraform and EKS skills are the core requirement. Found at Pune's IT services and product companies.

Build & Release Engineer

₹5–9 LPA (Entry) · ₹12–20 LPA (experienced)

Specialist in CI/CD tools and release engineering. Manages Jenkins infrastructure, build toolchains, and release processes. Good entry path for candidates from a testing or developer background.

DevSecOps Engineer

₹10–18 LPA (Entry) · ₹22–40 LPA (senior)

DevOps with a security specialisation — integrating SAST, DAST, vulnerability scanning, and compliance checks into CI/CD pipelines. The fastest-growing DevOps specialisation as security becomes a pipeline-level concern.

DevOps Architect / Engineering Manager

₹25–50 LPA · Senior leadership

Designs DevOps strategy and toolchain for large engineering organisations. Leads DevOps teams, drives cultural transformation, and makes technology platform decisions. Typically 7–10 years of experience.

Who Should Join This DevOps Course in Pune?

Prerequisites: Basic familiarity with any operating system (Windows or Linux), some exposure to any programming or scripting language, and a genuine interest in how software systems work. Prior Linux experience is helpful but not required — we cover Linux from the ground up in Module 1.

Why Students Choose Aapvex for DevOps Training in Pune

Hands-On from Day One, Not Slide-Deck Training: Every student in our DevOps programme gets access to a cloud-based lab environment from the very first session. You do not watch someone else configure a Jenkins pipeline — you configure it yourself, break it, fix it, and then break it a different way. That learning sticks in a way that watching videos simply does not.

Complete Toolchain, Not Cherry-Picked Topics: Some DevOps courses cover Docker and Kubernetes well but skim over Ansible and Terraform. Others focus on AWS but barely touch monitoring. Our programme covers the complete DevOps toolchain that real teams use — because a DevOps engineer who can handle 80% of the pipeline but cannot manage the infrastructure or read the monitoring is still a bottleneck.

Projects That Are Interview Proof: Every project you build in this programme runs on real AWS infrastructure with real tools. You can show the GitHub repository, the Jenkins dashboard, the Kubernetes cluster, the Terraform code, and the Grafana dashboards to any interviewer. When they ask "tell me about a time you built a CI/CD pipeline" — you have a real, detailed, technically deep answer. That is what gets you the job and the salary you are aiming for.

Small Batches, Senior Trainers: Maximum 15–20 students. Our DevOps trainers are working DevOps practitioners — not people who read the documentation last month. When you hit a tricky Kubernetes scheduling issue or a Terraform state lock problem, they have seen it before and can walk you through it from experience. Call 7796731656 to speak with the team.

What Our DevOps Graduates Say

"I spent three years as a Java backend developer and kept seeing DevOps Engineers joining my team and earning more than I was despite having less coding experience. I finally decided to do something about it. The Aapvex DevOps course was genuinely the best professional investment I have made. The Jenkins module alone was worth the fee — by week four I had built a complete multi-stage pipeline with SonarQube and Docker that I immediately showed in interviews. The Kubernetes module was challenging but the trainer had seen every possible error and walked me through each one patiently. I joined Persistent Systems as a DevOps Engineer at ₹14 LPA — a ₹5 LPA increase from my developer role. If you are thinking about it, stop thinking and call 7796731656."
— Vikram N., DevOps Engineer, Persistent Systems, Pune — (₹9 LPA Java Dev → ₹14 LPA DevOps)
"I was a Linux system administrator for four years and knew my way around a terminal but had never touched Docker or Kubernetes. The Aapvex course was perfectly paced for someone like me — the Linux module was a quick refresh, and then things got genuinely interesting from Docker onwards. The Terraform module was the one that surprised me most — I had always thought of infrastructure as something you manage manually, and seeing an entire AWS VPC and EKS cluster come up from a single terraform apply was honestly a bit magical. Got placed at a Bangalore-based SaaS company as a Cloud DevOps Engineer at ₹16 LPA. The Aapvex placement team was also excellent — two mock interviews, resume review, and a direct referral that got me the interview."
— Sneha R., Cloud DevOps Engineer, SaaS Company (Aapvex graduate, Pune batch)

Batch Schedule & Flexible Learning Options

All batches are capped at 15–20 students. To check the next available batch date and reserve your seat, call 7796731656 or WhatsApp 7796731656 right now.

Frequently Asked Questions — DevOps Course in Pune

What is the fee for the DevOps course at Aapvex Pune?
The DevOps course fee starts from ₹15,999. No-cost EMI options are available on select plans. Call 7796731656 or WhatsApp us for exact current batch pricing and to ask about any running discounts. The counsellor will walk you through the complete fee structure and payment options on the call.
I am a Java developer — is the DevOps course right for me?
Absolutely, and Java developers are actually among the best placed to succeed in DevOps. You already understand the software lifecycle — now you will learn to automate the deployment side of it. The CI/CD pipeline we build in Jenkins uses Maven (Java's build tool), so your existing knowledge directly applies. Developers who add DevOps skills typically see a ₹4–8 LPA salary increase within 6–12 months. Many of our top-performing graduates were Java developers before joining this course.
What is the salary of a DevOps engineer in Pune in 2025?
At the fresher level, DevOps engineers in Pune earn between ₹4.5 and ₹8 LPA depending on the company type (product companies pay more than service firms for the same skills). With 2–3 years of real experience — particularly with Kubernetes, Terraform, and AWS — the range moves to ₹10–20 LPA. Senior DevOps engineers and cloud architects with 5+ years earn ₹22–40 LPA. DevOps consistently ranks among the top five highest-paying technology roles in India.
Is Docker and Kubernetes covered in detail — or just introduced?
Both are covered as full dedicated modules — not just introductions. Docker gets a complete module covering Dockerfile writing and optimisation, multi-stage builds, Docker Compose for multi-service applications, container networking, volumes, and AWS ECR. Kubernetes gets a full module covering all core workload objects (Pods, Deployments, Services, ConfigMaps, Secrets), Ingress, HPA autoscaling, PersistentVolumes, AWS EKS managed cluster, Helm chart management, and ArgoCD GitOps. By the end, you can genuinely set up and manage a production Kubernetes cluster.
What is the difference between DevOps and Cloud computing?
Cloud computing refers to renting infrastructure (servers, storage, networking) from providers like AWS, Azure, or GCP instead of buying physical hardware. DevOps is the set of practices and tools for automating software delivery and infrastructure management — which typically happens on the cloud. The two are deeply interrelated: most DevOps work today involves managing cloud infrastructure. This course covers both — AWS as the cloud platform and Terraform, Docker, Kubernetes, Jenkins, and Ansible as the DevOps automation layer on top of it.
Do I need to buy AWS? What are the lab costs?
For classroom students, Aapvex provides a shared lab environment with pre-configured AWS infrastructure for all practical exercises — you do not need to create your own AWS account for in-class labs. For home practice, we guide you through setting up a free-tier AWS account. Some advanced labs (particularly EKS clusters) do incur small AWS costs if you run them independently at home — typically ₹500–1,500 over the full course for at-home practice. Online students get access to a provisioned cloud lab for all sessions.
Is Terraform covered for AWS — or just in theory?
Terraform is covered for actual AWS infrastructure provisioning — not theory. Module 7 takes you from writing your first main.tf through to provisioning a complete AWS environment: VPC with public and private subnets, security groups, EC2 instances, Application Load Balancer, RDS database, ECR registry, and an EKS cluster — all with Terraform code stored in GitHub with remote state in S3. This is the exact kind of Terraform work that companies in Pune are doing and that interviewers ask about in detail.
What is the difference between Ansible and Terraform?
This is one of the most common interview questions for DevOps roles, and it is important to have a clear answer. Terraform is an infrastructure provisioning tool — it creates infrastructure resources (servers, networks, databases, load balancers) from scratch. Ansible is a configuration management tool — once infrastructure exists, Ansible configures it (installs software, manages files, runs commands). In practice, you use Terraform to create an EC2 instance and Ansible to configure it — they are complementary tools, not competing ones. Many real-world DevOps pipelines use both.
Does the course cover SRE (Site Reliability Engineering)?
Yes. Module 8 introduces SRE principles — SLOs, SLIs, error budgets, toil reduction, and the reliability versus feature velocity tradeoff — alongside the monitoring toolchain (Prometheus, Grafana, Alertmanager, ELK) that SRE teams use. An incident response simulation is run as the module's capstone exercise. SRE is increasingly the senior career path from DevOps, particularly at product companies and financial technology firms, and having SRE concepts in your vocabulary significantly improves interview performance at these companies.
Which companies hire DevOps engineers in Pune and what do they pay?
Infosys (DevOps practice), TCS (Cloud & DevOps unit), Persistent Systems (platform engineering), Zensar, KPIT, ThoughtWorks, Capgemini, Accenture, Barclays Technology, Deutsche Bank Technology, Mastercard Technology, Volkswagen India IT hub, Bajaj Finserv Tech, and dozens of funded SaaS and product startups in Pune's Hinjewadi, Kharadi, Baner, and Magarpatta corridors. Fresher roles start at ₹4.5–8 LPA; experienced DevOps engineers with Kubernetes and Terraform skills earn ₹12–22 LPA.
What placement support does Aapvex provide after the DevOps course?
100% placement support, which means: (1) Resume building tailored specifically for DevOps roles — we know what Pune's DevOps interviewers look for and we structure your resume accordingly. (2) Two to three technical mock interviews with real DevOps interview question patterns — covering Linux, Git, Jenkins, Docker, Kubernetes, Ansible, and Terraform. (3) LinkedIn profile optimisation. (4) Interview shortlisting support through our company network. (5) Access to our private alumni jobs group where current openings from 100+ companies are shared. We stay involved until you are placed.
How do I enrol in the DevOps course at Aapvex Pune?
Three options: (1) Call or WhatsApp 7796731656 — a counsellor will talk you through batch dates, fees, and what to expect. (2) Fill the Contact form — we will call back within 2 hours. (3) Walk into our Pune training centre for a free 30-minute counselling session — no pressure, no commitment, just honest advice on whether this programme is the right fit for your background and goals.