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

Name: DevOps Certification Training Course with Gen AI
Item: DevOps Certification Training Course with Gen AI
Rating: 5
Author: Vijay Kalkundri

Why should you take DevOps Certification Training in San Francisco??

Average salary of a DevOps Engineer in San Francisco is $137,000.

Companies hiring devops professionals in San Francisco – Google, Amazon, Deutsche Bank, Goldman Sachs & many more

According to Linkedin, 669+ DevOps jobs available in San Francisco

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:

Orchestrating a secure, full-featured CI/CD pipeline
Integrating Git, Jenkins, Terraform, Ansible, Docker, and Kubernetes
Embedding AI tools for enhanced automation, testing, and monitoring

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Testimonial Reviews

Senthil VService Information Developer

The instructor has in-depth knowledge in DevOps tools. He explains the each one very clearly, thank ... Read More

Sidhartha MitraIBM MDM COE Head @ CTS, Kolkata Area, India

Edureka has been an unique and fulfilling experience. The course contents are up-to-date and the ins ... Read More

Puneet Jhajj

I have done Spring Framework and Hadoop framework training from Edureka. I am very happy with the tr ... Read More

Vijay KalkundriPrincipal Engineer at Reflektion, former Senior Test Engineer at Nokia

I had a great experience in taking the Hadoop course from Edureka. It is the only course in the mark ... Read More

Gagan Maheshwari

Thanks a lot for your Android course. Right from the point of the start of the demo class, until the ... Read More

Dheerendra YadavProject Lead at HCL Technologies, Ghaziabad, Uttar Pradesh, India

Earlier I had taken training in different technologies from other institutes and companies but no do ... Read More

Who is DevOps Engineering?

DevOps Engineering combines DevOps practices with AI tools to automate CI/CD, infrastructure, security, and monitoring. It boosts software delivery speed, reliability, and efficiency through smart automation, predictive analytics, and intelligent code generation.

Why is DevOps important in 2025?

DevOps, enhanced with AI, blends culture, tools, and practices to deliver software faster and more reliably.

As per the 2023 State of DevOps Report by Puppet, top teams deploy 46x faster, with 7x fewer failures and 96x quicker recovery, highlighting its impact on speed and stability.

How is AI impacting DevOps?

AI is enhancing DevOps through intelligent automation, predictive analytics, anomaly detection, and smarter CI/CD pipelines. It helps teams detect issues earlier, automate testing, and optimize infrastructure usage.

What are the most commonly used DevOps tools in 2025?

Git, GitHub, Jenkins, GitHub Actions, Docker, Kubernetes, Ansible, Terraform, CloudFormation, Helm, Prometheus, Grafana, ELK Stack, SonarQube, OWASP ZAP, HashiCorp Vault, Snyk, Trivy, Open Policy Agent (OPA).

Can someone without an IT background get into DevOps?

Yes, with the right mindset and willingness to learn, anyone can enter DevOps. While a basic understanding of tech concepts is important, online training can help you build the skills needed to succeed as a DevOps Engineer.

What are the 5 levels of DevOps practice?

DevOps maturity progresses from manual, siloed processes to full automation. It starts with basic tasks done manually, then moves to CI/CD automation, standardized pipelines, integrated security and monitoring (DevSecOps), and finally, self-service systems with autonomous delivery and minimal human input.

What are the 7 C's of DevOps?

Here’s a concise breakdown of the 7 C’s of DevOps:

Continuous Integration – frequent code merges
 Continuous Testing – automated quality checks
 Continuous Delivery – ready-to-release code
 Continuous Deployment – auto-release to production
 Continuous Monitoring – track performance in real time
 Continuous Feedback – improve via user/system insights
Continuous Operations – ensure uptime & stability

What is CI/CD in DevOps?

CI/CD stands for Continuous Integration and Continuous Delivery/Deployment. It’s a set of practices that enables developers to integrate code changes frequently, automatically test them, and deploy them to production reliably and quickly.

What is Infrastructure as Code (IaC)?

Infrastructure as Code (IaC) is the process of managing and provisioning computing infrastructure through machine-readable definition files, rather than physical hardware or interactive configuration tools.

Why is Edureka DevOps Training the Best in the Industry?

Edureka's DevOps training stands out due to its industry-relevant curriculum, hands-on projects, and expert-led live classes. Here's why it's considered one of the best:

Live Instructor-Led Classes
Comprehensive Tool Coverage
100% Hands-On Learning
Real-world projects and lab-based assignments
Flexible Scheduling
Weekend and weekday batch options
Lifetime access to course materials and recorded sessions
The industry-aligned final project to test practical skills
Certification recognized by many tech employers
Career Support

Why should you become a DevOps Engineer with AI expertise?

As modern software delivery demands speed and intelligence, DevOps Engineers with AI skills are highly sought after. The role blends automation, collaboration, and smart tooling to streamline development and operations. You gain hands-on experience across CI/CD, infrastructure as code, and intelligent monitoring while working on AI-powered solutions that shape the future of software engineering.

Does edureka provide DevOps training with a placement assistant?

Yes, Edureka provides DevOps assistance with DevOps training. After completing this training program, you will be able to qualify for a job interview. Edureka provides DevOps Interview Questions, which prepare learners for DevOps interviews and crack interviews in 1st attempt. Edureka also provides a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. More than 70% of Edureka Learners have reported changes in job profile (promotion), work location (onsite), lateral transfers & new job offers.

Can I learn DevOps for free?

Yes, various resources are available on the Internet to learn DevOps's basic concepts. Edureka provides free DevOps tutorial, guides, and blogs on these concepts.

How do I become a DevOps engineer with AI expertise?

Begin with core skills in Linux, networking, and scripting. Learn DevOps principles and master tools like Jenkins, Docker, Kubernetes, and Terraform. Build AI expertise by exploring tools that automate code reviews, testing, monitoring, and infrastructure optimization. Work on real-world projects, pursue certifications, and stay updated on evolving AI and DevOps trends to become a well-rounded, future-ready DevOps engineer.

What is the average salary of a DevOps certified professional?

According to Payscale and Glassdoor, the average salary of a DevOps professional is ₹715,130 in India and $96,418 in the United States.

Average Annual Salary in India

Entry-level (0–2 yrs): ₹6 – ₹9 LPA
Mid-level (3–6 yrs): ₹10 – ₹18 LPA
Senior-level (7+ yrs): ₹20 – ₹30+ LPA

Average Annual Salary in US :

Entry-level: $90,000 – $110,000
Mid-level: $115,000 – $140,000
Senior-level: $145,000 – $170,000+LPA

What are common career paths for someone in DevOps?

The common career paths for someone in DevOps is:

DevOps Architect
DevOps Engineer
Release Manager
Automation engineering
Director
Security
Site Reliability Engineer
Infrastructure Engineer
QA Engineer

What are the other DevOps Programs offered by Edureka?

Here is the list of DevOps Programs offered by Edureka:

What are the day-to-day activities of the DevOps engineer?

Here is the typical Day-to-day activities of a DevOps Engineer:

What are the daily tasks of a DevOps Engineer?
Monitor systems and CI/CD pipelines
Write and update scripts or configuration files
Build, test, and deploy applications
Troubleshoot build or deployment failures
Manage infrastructure as code (IaC)
Use AI tools for log analysis, anomaly detection, and code reviews
Maintain containerized environments

Where do DevOps Engineers hang out online?

DevOps Engineers often hang out in various online communities, forums, and platforms to share knowledge, discuss best practices, and collaborate on projects. Here are some popular online hangouts for DevOps professionals:

Reddit
Edureka Community
Stack Overflow
GitHub
DevOps Chat
LinkedIn Groups
Slack Communities
Discord Servers
Medium
Online and offline Conferences and Meetups
Forums
Twitter

What if I miss an online DevOps training class?

You will always attend a lecture at Edureka! You can choose either of the two options: View the recorded session of the class available in your LMS OR attend the missed session in any other live batch. So enroll now with one of the best DevOps Online Training and never miss a single class.

What types of support are available for technical issues during the DevOps Training?

Edureka offers robust technical support for its DevOps program, including:

24/7 Lifetime Support: You can access support anytime during and after the training, ensuring help is available for any issues you encounter
Instructor Interaction: During live sessions, instructors are available to address questions and technical issues in real-time.
Dedicated Technical Support Team: If you face any platform or software-related issues, their support team is ready to assist

Who are the instructors for this training program?

The instructors for this DevOps training program are typically experienced professionals in the field. They are:

Experienced DevOps professionals with expertise in CI/CD, cloud platforms, automation tools, and AI in DevOps
Focused on practical, industry-relevant training, emphasizing AI-driven automation and predictive analytics
Selected for both teaching ability and hands-on experience, bridging the gap between theory and real-world application
Sharing best practices and insights, including the role of AI in enhancing DevOps efficiency and security

Is the training material accessible to the students even after the online DevOps training is over?

Yes, the access to the DevOps certification material will be available for lifetime once you have enrolled into the training. So enroll now with our best DevOps training and enjoy the benefit of lifetime access to the learning material.

What if I have queries after I complete this DevOps online training?

Your access to the Support Team is for a lifetime and will be available 24/7. The team will help you in resolving queries during and after the DevOps training program.

Where can I get real-time project experiences on DevOps?

DevOps real time projects are available on multiple sources like:

Online Platform like GitHub, GitLab etc.
Edureka DevOps training provides real time projects and case studies.
Participating in Hackathons.
Engage in Open Sources communities like kubernetes, jenkins.
Meetup and workshops also provide hands-on experience on DevOps.

How soon after Signing up would I get access to the Learning Content?

Post-enrolment of the DevOps program, the LMS access will instantly be provided to you and available for a lifetime. You can access the complete set of previous class recordings, PPTs, PDFs, and assignments. Moreover, access to our 24x7 support team will also be granted instantly. You can start learning right away.

View course curriculum

Video Reviews

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DevOps Training Bootcamp in San Francisco

Why should you take DevOps Certification Training in San Francisco??

Instructor-led DevOps Certification Training live online classes

Financing Options

DevOps Certification in San Francisco Curriculum

DevOps Fundamentals and CI/CD Overview

Version Control with Git and GitHub

Continuous Integration with Jenkins

Infrastructure as Code (IaC) with Terraform and CloudFormation

Configuration Management with Ansible

Containerization with Docker

Container Orchestration with Kubernetes

Kubernetes Networking, Storage, and Advanced Tooling

Monitoring and Logging with Prometheus, Grafana, and ELK Stack

DevSecOps: Security Integration in DevOps Pipelines

Generative AI Integration in DevOps

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

DevOps Training in San Francisco Description

About Edureka Devops Training Course and Key Features

Why learn AI-Enhanced DevOps?

Why move to AI-integrated DevOps?

What are the prerequisites for this DevOps Certification Course?

Why adopt an AI-driven DevOps approach?

Why should you become a DevOps Engineer with AI expertise?

What will participants learn during the DevOps Certification Training?

Who should take the DevOps Certification Course?

Testimonial Reviews

Video Reviews

DevOps Training in San Francisco FAQs

Who is DevOps Engineering?

Why is DevOps important in 2025?

How is AI impacting DevOps?

What are the most commonly used DevOps tools in 2025?

Can someone without an IT background get into DevOps?

What are the 5 levels of DevOps practice?

What are the 7 C's of DevOps?

What is CI/CD in DevOps?

What is Infrastructure as Code (IaC)?

Why is Edureka DevOps Training the Best in the Industry?

Why should you become a DevOps Engineer with AI expertise?

Does edureka provide DevOps training with a placement assistant?

Can I learn DevOps for free?

How do I become a DevOps engineer with AI expertise?

What is the average salary of a DevOps certified professional?

What are common career paths for someone in DevOps?

What are the other DevOps Programs offered by Edureka?

What are the day-to-day activities of the DevOps engineer?

Where do DevOps Engineers hang out online?

What if I miss an online DevOps training class?

What types of support are available for technical issues during the DevOps Training?

Who are the instructors for this training program?

Is the training material accessible to the students even after the online DevOps training is over?

What if I have queries after I complete this DevOps online training?

Where can I get real-time project experiences on DevOps?

How soon after Signing up would I get access to the Learning Content?

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