What if I miss a DevOps online training class?

There's no way to miss a class in Edureka! You have two options: take a look at the recorded lectures of the class via your LMS or take part in the class that was missed or takes part in the live class. Register now to attend one of the top DevOps certification courses online to ensure that you never miss any class.

What if I have questions after finishing the DevOps course in San Jose?

The support team is always available at all hours of the day. The support team will assist in resolving any issues you encounter during the course or beyond your completion of the DevOps course.

What happens after I sign up? Can I get access to the learning content?

Once you've finished your DevOps certification course and completed your DevOps certification course, the LMS login password is automatically given to you. It will be available throughout the period. You'll be able to access all recordings from the class and PDFs, PPTs, and assignments. Access to our support staff is always available.

Is the course material available to students after DevOps Training in San Jose has been completed?

Yes, you will have access to DevOps certification course content for the rest of your life after you've completed the course. Begin now by enrolling in our top DevOps course in San Jose and reap the benefits of accessing the course materials.

Why should you go for this DevOps course online?

The teaching method has developed because of technological advances and technological advancements that are developing. Nowadays, it is possible to teach learning with technology. DevOps online training offers top-quality and comfortable in its training module. Through our 24-hour assistance line, online students will be assisted by an individual who will assist them throughout the course, even after the class is over. This is among the most critical reasons we ensure that students reach their goals in learning. We also offer all-year access to the current course tools to all our students. So join our best DevOps certification course online now.

What's the required time to complete this DevOps course in San Jose?

DevOps certification training in San Jose offers flexible hours to suit your needs. The weekend classes run for six weeks and include instructor-led, real-time training sessions. They are then followed by live projects to provide you with an opportunity to practice your skills. The most efficient program or the weekday sessions can be completed less because they combine intense training sessions and actual projects that students can complete in the final session. Edureka provides the top DevOps course online that will allow you to ensure that you receive the best training from highly knowledgeable instructors in the USA.

What qualifications do a DevOps engineer holds?

Experience using Linux Fundamentals and knowledge of one scripting language such as Python or Shell can benefit.A DevOps Engineer must be proficient in various development tests, deployment, and strategies. They should be aware of the different DevOps phases and be familiar with various DevOps tools, such as Git, Jenkins, Docker, Selenium, Puppet, Chef, Kubernetes, and Nagios.A DevOps engineer should have experience with developing and maintaining pipelines. Development and maintaining pipelines to help support CI/CD.Understanding the specifics of cloud-based cloud solutions (AWS, Azure, etc.) is a benefit.

DevOps Training in San Jose [#1 Institute for DevOps Course]

Name: DevOps Certification Training Course with Gen AI
Item: DevOps Certification Training Course with Gen AI
Rating: 5
Author: Raghava Beeragudem

Why should you take DevOps Certification Training in San Jose?

Average salary of DevOps Engineer in San Jose is $142,000.

Companies hiring devops professionals in San Jose – Uber, Intel, Mercedes Benz, Cisco & many more

According to Indeed.com, 789+ DevOps jobs available in San Jose

DevOps Fundamentals and CI/CD Overview

Topics Covered:

Evolution of software development methodologies
DevOps culture and organizational impact
Core DevOps principles: collaboration, automation, measurement, sharing
Key DevOps practices and lifecycle
DevOps reference architectures and implementation strategies
Overview of CI/CD pipelines
Value stream mapping and process optimization
Introduction to DevOps toolchain
AI-driven automation concepts in DevOps (e.g., predictive analytics for bottleneck identification)
Industry case studies of successful DevOps transformations

Hands-on Activities:

Assessment of current workflow bottlenecks and improvement opportunities
Value Stream Mapping exercise to identify waste in the software delivery pipeline
Setting up a basic CI pipeline structure diagram
Tool exploration and environment setup for subsequent modules

Skills Covered:

Understanding DevOps culture and CI/CD principles
Mapping and optimizing delivery workflows
Applying AI for workflow automation and predictive analytics

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Version Control with Git and GitHub

Topics Covered:

Git architecture and core concepts
Repository management and Git commands
Branching strategies: GitFlow, GitHub Flow, Trunk-based development
Pull requests and code review processes
Merge conflict resolution techniques
Git hooks for automation
GitHub Actions introduction
AI-powered code review with GitHub Copilot
Repository security best practices

Hands-on Activities:

Create and manage branches, resolve conflicts
Configure protected branches and access controls
Build a simple GitHub Actions workflow
Set up GitHub repositories with automated code review workflows using AI tools
Resolve merge conflicts with AI-assisted suggestions

Skills Covered:

Mastering Git workflows and resolving merge conflicts
Collaborating via GitHub and managing repository security
Using AI tools for automated code reviews and suggestions

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Continuous Integration with Jenkins

Topics Covered:

Jenkins architecture and components
Jenkins installation and configuration
Pipeline as Code with Jenkinsfile
Jenkins plugins ecosystem
Parameterized builds and triggers
Automated testing and static code analysis
Pipeline optimization techniques
Jenkins security and credentials management
Multi-branch and pipeline visualization
AI-driven test selection and deployment risk analysis

Hands-on Activities:

Installing and configuring the Jenkins server
Creating declarative and scripted pipelines
Configuring build triggers and webhooks with Git repositories
Setting up automated testing in the CI pipeline
Implementing pipeline visualization
Secure Jenkins with role-based access control
Debugging pipeline failures
Configure Jenkins pipelines with AI-based test case prioritization tools (e.g., Testim.io)
Implement predictive analytics for deployment success rates

Skills Covered:

Designing CI pipelines with Jenkins and Jenkinsfile
Automating testing and integrating static code analysis
Leveraging AI for test case prioritization and pipeline optimization

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Infrastructure as Code (IaC) with Terraform and CloudFormation

Topics Covered:

IaC concepts and benefits
Terraform basics: HCL, providers, state management
AWS CloudFormation fundamentals
State management in Terraform
Modules, variables, and outputs
Security in IaC: secrets management and policy enforcement
Testing infrastructure code
AI-assisted code generation using HashiCorp Waypoint AI and Tabnine
Anomaly detection in infrastructure metrics
Resource cost prediction and optimization using ML models (e.g., AWS Forecast)

Hands-on Activities:

Write Terraform scripts to provision AWS resources
Create CloudFormation templates for infrastructure
Manage Terraform state and remote backends
Integrating Terraform with CI/CD pipeline
Security scanning for infrastructure code
Infrastructure testing with Terratest
Write Terraform scripts with AI-generated suggestions for optimization
Use AI models to predict resource allocation needs in cloud environments

Skills Covered:

Writing and managing reusable Terraform and CloudFormation templates
Integrating IaC into CI/CD workflows
Using AI to auto-generate, validate, and optimize IaC scripts

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Configuration Management with Ansible

Topics Covered:

Configuration management concepts and tools
Ansible architecture and components
YAML syntax for Ansible
Playbooks, roles, and inventories
Variables, templates, and conditionals
Ansible Vault for secrets
Error handling and idempotency
Ansible integration with CI/CD tools
AI-assisted playbook generation using tools like GitHub Copilot, Tabnine, or CodeWhisperer
Natural Language to YAML: Prompt-to-playbook using LLMs (e.g., OpenAI, Codex)
Self-healing scripts with AI triggers and remediation logic

Hands-on Activities:

Writing and executing basic Ansible playbooks
Developing reusable Ansible roles
Create roles for modular automation
Implementing secret management with Ansible Vault
Creating dynamic inventories
Trigger Ansible playbooks from Jenkins
Use GitHub Copilot or CodeWhisperer for assisted playbook authoring

Skills Covered:

Creating and organizing Ansible playbooks and roles
Managing secrets securely with Ansible Vault
Using AI for playbook generation and self-healing logic implementation

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Containerization with Docker

Topics Covered:

Container concepts and Docker architecture
Dockerfile syntax and best practices
Image layering and optimization
Docker networking models
Volume management and data persistence
Docker Compose for multi-container apps
Container registries and image scanning
Runtime security and resource limits
AI-based image scanning (e.g., Trivy) for security vulnerabilities
AI-based Dockerfile generation using tools like GitHub Copilot, Tabnine, or Codex

Hands-on Activities:

Create Dockerfiles and build images
Building, tagging, and pushing images to registries
Deploy multi-container apps with Docker Compose
Setting up a private container registry with security controls
Integrating Docker builds in the CI pipeline
Scan images for vulnerabilities using Trivy
Create Dockerfiles with AI-generated optimizations for performance improvements.

Skills Covered:

Building and optimizing Docker images and Dockerfiles
Managing container lifecycle with Compose and registries
Using AI for vulnerability scanning and Dockerfile optimization

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Container Orchestration with Kubernetes

Topics Covered:

Kubernetes architecture and core components
Pods, ReplicaSets, Deployments, and DaemonSets
Kubernetes Services: ClusterIP, NodePort, LoadBalancer
ConfigMaps, Secrets, and Environment Configuration
Namespaces and RBAC for multi-tenancy and security
Kubernetes CLI (kubectl) for cluster management
Pod lifecycle management and scaling strategies
Rolling updates, rollbacks, and deployment strategies
AI-assisted Deployment Strategies
Using AI to Analyze Pod Health and Recommend Restarts or Scaling

Hands-on Activities:

Set up a Minikube or Kind cluster
Deploy sample applications using YAML manifests
Use kubectl for managing Pods, Services, and Deployments
Implement rolling updates and scale applications
Manage secrets and config using ConfigMaps and Secrets
Apply RBAC policies to restrict access by role and namespace
Integrate a simple AI script to monitor pod resource usage and recommend scaling
Simulate and deploy a predictive health-check model for early pod failure detection

Skills Covered:

Managing deployments, updates, and scaling in Kubernetes
Securing workloads with RBAC and secrets
Integrating AI to monitor pod health and recommend scaling actions

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Kubernetes Networking, Storage, and Advanced Tooling

Topics Covered:

Labels, Selectors, Annotations, and Service Discovery
Types of Services: ClusterIP, NodePort, LoadBalancer, Headless
Persistent Volumes (PVs), Persistent Volume Claims (PVCs), Storage Classes
Ephemeral vs. Projected Volumes and Access Modes
StatefulSets for stateful workloads
Helm: Kubernetes package manager and Helm Charts
Prometheus setup and metrics scraping for Pods, Nodes, and Deployments
Grafana dashboards for monitoring Kubernetes environments
Alerting with Grafana and using Prometheus exporters
Security best practices and Pod Security Policies

Hands-on Activities:

Deploy Services and explore networking with demonstrations
Create and mount Persistent Volumes and use PVCs
Deploy stateful applications with StatefulSets
Use Helm to deploy pre-packaged applications
Install Prometheus and Grafana for monitoring
Create dashboards and set alerts based on Kubernetes metrics

Skills Covered:

Configuring persistent storage and Kubernetes Services
Deploying applications using Helm charts
Visualizing cluster performance with Prometheus and Grafana

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Monitoring and Logging with Prometheus, Grafana, and ELK Stack

Topics Covered:

Monitoring principles and the four golden signals
Prometheus architecture and data model
Prometheus setup and PromQL queries
Grafana dashboard creation
ELK Stack components (Elasticsearch, Logstash, Kibana)
Log aggregation strategies
Alerting and notification configuration
SLIs, SLOs, and SLAs
Performance analysis techniques
Distributed tracing concepts

Hands-on Activities:

Setting up Prometheus and Grafana for application monitoring
Implementing custom metrics in applications
Designing comprehensive Grafana dashboards
Configuring the ELK Stack for log aggregation
Creating logging pipelines with Logstash
Implementing alerting rules and notification channels
Log querying and analysis in Kibana
Monitoring infrastructure and application health
Use OpenAI to classify log messages and flag potential errors

Skills Covered:

Setting up monitoring and log aggregation pipelines
Creating actionable Grafana dashboards and alerts
Applying AI for anomaly detection in metrics and logs

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DevSecOps: Security Integration in DevOps Pipelines

Topics Covered:

Security as Code concept
DevSecOps principles and implementation approaches
Static Application Security Testing (SAST)
Dynamic Application Security Testing (DAST)
Software composition analysis (SCA)
Container and infrastructure security scanning
Secrets management (HashiCorp Vault, AWS Secrets Manager)
Security policy as code (OPA, Kyverno)
Compliance as Code
Security monitoring and intrusion detection
Incident response and audit trails

Hands-on Activities:

Integrating SAST tools (SonarQube) in the CI pipeline
Implementing DAST with OWASP ZAP in the deployment pipeline
Setting up secrets management with HashiCorp Vault
Perform dependency vulnerability scanning with Snyk or similar
Implementing security policies with Open Policy Agent
Automated compliance checking with InSpec

Skills Covered:

Automating SAST, DAST, and compliance checks
Securing credentials and implementing policy-as-code
Performing vulnerability scanning and incident response

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Generative AI Integration in DevOps

Topics Covered:

Gen AI concepts: LLMs, transformers, and diffusion models
AI coding assistants (GitHub Copilot, Amazon CodeWhisperer)
Prompt engineering for infrastructure and automation scripts
AI for automated documentation and test generation
Ethical considerations and AI governance in DevOps

Hands-on Activities:

Generate Terraform and Ansible scripts using ChatGPT
Create AI-assisted Dockerfiles and Kubernetes manifests
Automate test case generation with AI tools
Implement AI-powered chatops in Slack or MS Teams

Skills Covered:

Generating infrastructure code using AI assistants
Automating documentation and test generation with GenAI
Integrating AI chatops and prompt-based automation

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End-to-End AI-Enhanced CI/CD Pipeline

Project Scope:

Use Git/GitHub for version control and collaboration
Build a Jenkins pipeline integrating Terraform, Ansible, Docker, and Kubernetes
Incorporate AI tools for code generation, testing, and monitoring
Implement security gates and automated compliance checks
Deploy a containerized application with monitoring and alerting

Hands-on Activities:

Designing a comprehensive CI/CD pipeline architecture
Implementing complete pipelines with Jenkins or GitHub Actions
Integrating all tooling components: VCS, testing, security scanning, IaC, configuration management
Building a containerized application deployment with Kubernetes
Implementing monitoring and alerting
Creating pipeline documentation and runbooks

Skills Covered: