Learn DevOps in San Jose with hands-on work across Linux, Git, Jenkins, Maven, SonarQube, JFrog, Docker, Kubernetes, Terraform, Ansible, Prometheus, Grafana, ELK Stack, AquaTrivy, AWS, and Microsoft Azure. This course is built around real CI/CD pipelines, infrastructure as code, monitoring, security scanning, and production deployment practice.
14,200+ (Placed)
Freshers to IT
7,100+ (Placed)
Non-IT to Tech
5,800+ (Placed)
Career Gap Fillers
6,400+ (Placed)
Upskilling Success
24,999₹
In 60 Days + Placement
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This course is designed to help you move from training into real DevOps job roles in San Jose. Learning the tools is only part of the outcome; you also need a resume that shows infrastructure, automation, deployment, and monitoring work clearly. Inventateq supports that transition with practical placement help tied to the roles this course prepares you for.
San Jose has strong demand for DevOps, cloud, platform, and infrastructure talent across technology companies, product teams, and cloud-heavy operations groups. Pay grows with hands-on experience in automation, deployment reliability, security, and multi-cloud work.
Average DevOps Salary by Experience in San Jose
San Jose has strong demand for DevOps, cloud, platform, and infrastructure talent across technology companies, product teams, and cloud-heavy operations groups. Pay grows with hands-on experience in automation, deployment reliability, security, and multi-cloud work.
Average DevOps Salary by Experience in San Jose
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Inventateq teaches DevOps through practical implementation, not just concepts. The syllabus moves from Linux administration and Shell Scripting into Git, Jenkins, Docker, Kubernetes, Terraform, Ansible, monitoring, logging, and security, so learners see how each part fits into a working delivery pipeline.
We stand apart through our commitment to:
Live online DevOps training for San Jose learners covers the same practical syllabus with instructor-led sessions, demonstrations, and lab-based assignments. It works well if you want to study from home while still getting real-time guidance on CI/CD, cloud, and deployment topics.
Best for developers who want to learn build, deploy, and release automation.
Useful for admins moving into Linux automation, monitoring, and deployment work.
Helps cloud learners connect AWS, Azure, infrastructure, and DevOps delivery.
Good for managers who need practical visibility into DevOps workflows and tools.
Suitable for learners who want a structured entry into DevOps roles from a technical base.
Duration: 80 Hours
Training Type: Hands-on practical implementation
Mode: Offline classroom and live online options
Focus: CI/CD, cloud, automation, monitoring, and security
No prior DevOps experience is required if you are willing to learn step by step.
Rated 4.9/5
Inventateq keeps DevOps training practical, structured, and job-focused. Learners work through the full stack of server administration, scripting, CI/CD, containers, orchestration, infrastructure as code, monitoring, logging, and security with tools used in real teams.
By the end of the course, learners understand how to automate builds, deploy applications, manage containers, provision infrastructure, and monitor production systems. The work is practical and aligned with the tools and workflows used in DevOps teams.
Learn how to connect Git, Maven, SonarQube, JFrog, Jenkins, Docker, and Kubernetes into a working delivery flow.
Use Terraform and Ansible to provision environments and keep them consistent across deployments.
Handle users, permissions, services, logs, networking, storage, and security hardening on Linux systems.
Work with Docker images, Compose, registries, Kubernetes workloads, and cluster updates.
Use Prometheus, Grafana, ELK Stack, and alerting tools to track system health and fix issues.
Use hardening, scanning, and access control practices to keep deployments safer.
The certificate validates that you have completed practical DevOps training across Linux, automation, CI/CD, cloud deployment, containers, orchestration, monitoring, and security. It helps show employers that you have worked with the tools and concepts expected in DevOps and cloud operations roles.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Earn this certificate upon successful completion of our training program.
Yes, the course is structured to start with Linux and Shell Scripting before moving into CI/CD, containers, and cloud tooling. That makes it easier for beginners to build a base before working on more advanced DevOps topics. You should be comfortable learning technical concepts step by step.
The course includes practical implementation across pipelines, containerization, deployment, monitoring, logging, and infrastructure automation. You work through an end-to-end DevOps flow from code to build, scan, package, deploy, and monitor. The capstone work is designed to reflect real production-style practices.
Yes, placement support is part of the program. Inventateq helps with resume preparation, interview practice, and role guidance for DevOps, Cloud Engineer, SRE, and infrastructure jobs. The support is practical and focused on helping you present your project work clearly.
If you have no hands-on technical background, the course may still be possible if you are ready to work through systems and cloud fundamentals. The Linux and scripting modules are important foundations, and the rest of the course builds from there. A basic comfort with technology and consistent practice will help a lot.
Yes, live online training is available for learners in San Jose. The online format covers the same syllabus, labs, and mentor support as classroom training. It is useful if you want flexibility while still learning in a structured, instructor-led format.
The program duration is 80 hours, with hands-on practical implementation included. That gives enough time to cover the major DevOps tools and workflows in a guided order. The pace is designed to balance theory, demonstration, and lab practice.
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