GitOps, MLOps, AIOps & FinOps Online Training in Hyderabad
Learn the four "Ops" practices DevOps teams are adopting now — GitOps with Argo CD, MLOps with MLflow and DVC, AIOps for smarter monitoring and FinOps for cloud cost — in live online classes.
G4.7★★★★★on Google 1300+ students trained- Duration
- 30 Days
- Mode
- Live Online
- Batches
- Weekday & Weekend
- Hands-on
- 3 real-time projects
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About GitOps, MLOps, AIOps & FinOps Online Training
Once a team has CI/CD and Kubernetes in place, the next questions are always the same: how do we keep every environment in sync, how do we ship machine learning models safely, how do we cut alert noise, and why is the cloud bill so high? GitOps, MLOps, AIOps and FinOps are the practices that answer them. Our MLOps training in Hyderabad covers all four in one focused 30-day course, in live online classes.
Course highlights
- GitOps with Argo CDGit as the single source of truth, multi-environment deployments, and canary and blue-green releases with Argo Rollouts.
- MLOps end to endDVC, MLflow, Docker model serving, CI/CD for models, drift monitoring and LLMOps basics.
- AIOps with Gen AIAnomaly detection, event correlation, and incident summaries and runbooks written with LLMs like Claude.
- FinOps for cloud costCost visibility, tagging, budgets, rightsizing, Kubecost and Infracost checks in pipelines.
Skills you’ll learn
What Each Practice Means
GitOps makes Git the single source of truth for what runs in your clusters; a tool like Argo CD keeps the cluster matched to the repository. MLOps applies DevOps habits to machine learning: versioned data, tracked experiments, models served as APIs and watched for drift. AIOps uses AI on monitoring data to spot problems early and explain them. FinOps brings engineering and finance together to see, control and reduce cloud spend.
All four use the same base — Git, containers, Kubernetes and monitoring — which is why they are taught together here.
Who Gains Most From This Course
This is an advanced course. It suits engineers who already work with DevOps or cloud and want to move into platform, MLOps or SRE roles, where these practices are now listed in most job descriptions.
Who Should Join This Course?
Because the course is 30 days long, it assumes some DevOps background. These are the people who get the most from it:
DevOps and Cloud Engineers
Engineers who run CI/CD and Kubernetes and want to add GitOps, cost control and smarter monitoring.
Data Scientists and ML Engineers
People who build models and need to deploy, version and monitor them properly in production.
SRE and Operations Teams
Engineers handling alerts and incidents who want to use AIOps to reduce noise and find root causes faster.
Cloud Cost and Platform Owners
Team leads and architects who need to understand and reduce what their cloud spend is going on.
Prerequisites for This Course
This course builds on DevOps basics. You should be comfortable with:
- Linux command line and basic Git usage
- Docker basics and a working idea of Kubernetes
- Any CI/CD tool such as GitHub Actions, GitLab CI, Jenkins or Azure DevOps
- For the MLOps part, a basic idea of what training a model means (no data-science background needed)
GitOps, MLOps, AIOps & FinOps Course Syllabus
The 30-day syllabus has six modules: Git and version control in depth, GitOps with Argo CD and Flux, MLOps from data versioning to drift monitoring and LLMOps, AIOps with observability and Gen AI for operations, FinOps from pricing models to Kubernetes cost, and three real-time projects.
- Version control concepts, Git installation and configuration
- Repositories, staging, commits and history
- Branching, merging, rebasing and resolving conflicts
- Tags, stash, cherry-pick, reset and revert
- Branching strategies: Git Flow, GitHub Flow, trunk-based development
- GitHub and GitLab: pull and merge requests, code reviews, branch protection
- Git hooks and CI basics with GitHub Actions and GitLab CI
- GitOps principles: Git as the single source of truth, declarative, pull-based delivery
- GitOps vs traditional CI/CD push model
- Kubernetes manifests, Helm charts and Kustomize for GitOps
- Argo CD: installation, applications, sync policies, rollbacks
- Flux CD overview
- Managing multiple environments (dev, test, prod) and secrets in GitOps
- Infrastructure GitOps with Terraform
- Progressive delivery: canary and blue-green with Argo Rollouts
- ML lifecycle: data, training, evaluation, deployment, monitoring
- MLOps vs DevOps, and MLOps maturity levels
- Data versioning with DVC
- Experiment tracking and model registry with MLflow
- Packaging models with Docker and serving them as APIs
- ML pipelines with Kubeflow and Azure Machine Learning
- CI/CD for ML models using GitHub Actions and Azure DevOps
- Model monitoring: data drift, model drift and retraining
- LLMOps basics: deploying and monitoring LLM-based apps
- AIOps concepts: using AI for IT operations
- Observability foundations: metrics, logs and traces
- Prometheus, Grafana and the ELK stack
- Anomaly detection and alert noise reduction
- Event correlation and root cause analysis
- AIOps platforms: Azure Monitor with AI insights, Dynatrace, Datadog overview
- Gen AI for operations: log analysis, incident summaries and runbooks with LLMs like Claude
- Automated remediation and self-healing systems
- FinOps principles, lifecycle (Inform, Optimize, Operate) and team roles
- Cloud pricing models: pay-as-you-go, reserved instances, savings plans, spot
- Cost visibility: Azure Cost Management and AWS Cost Explorer
- Tagging strategy and cost allocation, showback and chargeback
- Budgets, alerts and anomaly detection
- Rightsizing, auto-scaling and removing idle resources
- Kubernetes cost monitoring with Kubecost
- Cost checks in pipelines with Infracost and Terraform
- FinOps reports and dashboards for management
- 1. Git and GitOps deployment: Set up a Git branching workflow with pull requests and CI checks, then deploy a microservices app to Kubernetes using Argo CD across dev, test and prod environments
- 2. End-to-end MLOps pipeline: Version data with DVC, track training in MLflow, serve the model in Docker, deploy it through CI/CD and monitor it for drift
- 3. AIOps and FinOps platform: Monitor the deployed apps with Prometheus, Grafana and ELK with anomaly alerts and AI-generated incident summaries, and add a FinOps dashboard with tagging, budgets, cost reports and rightsizing
Real-Time Projects
The three projects connect, so by the end you have one working platform that uses all four practices.
Git and GitOps Deployment
A Git branching workflow with pull requests and CI checks, then a microservices app deployed to Kubernetes with Argo CD across dev, test and prod.
End-to-End MLOps Pipeline
Version data with DVC, track training in MLflow, serve the model in Docker, deploy it through CI/CD and monitor it for drift.
AIOps and FinOps Platform
Monitor the apps with Prometheus, Grafana and ELK with anomaly alerts and AI-written incident summaries, plus a FinOps dashboard with tagging, budgets and rightsizing.
Built on Your Own Setup
Everything runs on your own Git repository and cluster, so you can show the working platform in interviews.
How AI Fits Into These Practices
AI runs through this course in two ways. In MLOps you deploy and monitor models, including the basics of LLMOps for apps built on large language models. In AIOps you use AI on your own monitoring data: anomaly detection, event correlation, and LLMs like Claude to summarise incidents, read logs and draft runbooks. We also cover where automated remediation helps and where a human should still approve the fix.
Career Opportunities After This Course
These skills are asked for in platform, MLOps and SRE roles. Typical roles:
We help you add these projects to your resume in a way interviewers understand, run mock interviews on each practice, and support you with placement assistance after the course.
Course Fee and Batches
The GitOps, MLOps, AIOps and FinOps course fee depends on the batch type and current offers. Call us on +91 90327 34343 or message us on WhatsApp for the exact fee and the next batch date. EMI is available.
All batches are live online with weekday and weekend options. Every class is recorded, so you can catch up if you miss one, and students joining from the USA, UK or Canada get time slots that suit their time zone.
Why Learn These Practices at VR IT Solutions?
Four Practices, One Platform
Instead of four separate short courses, you build one connected platform where GitOps, MLOps, AIOps and FinOps work together.
Short and Focused
30 days, built for working engineers who already know DevOps basics and want the next level without starting over.
Live Online With Recordings
Live classes, recordings of every session for revision, and backup classes when needed.
Interview and Job Support
Resume help, mock interviews and placement assistance after the course.
From your first class to your first project at work
We stay with you after the course ends — through interviews, placement, and your first months on the job.
- Free demo classMeet the trainer and see how classes run before you pay.
- Live trainingLive online classes, with hands-on practice every session.
- Real-time projectWork through a real implementation scenario from start to finish.
- Course certificateGet your course completion certificate from VR IT Solutions.
- Resume & mock interviewsResume review and practice interviews with experienced professionals.
- Placement assistanceInterview referrals and guidance until you get placed.
- Job supportStuck on a task in your new job? Our trainers help you solve it.
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I have Join VRIT Solutions to transform my future. VRIT is the right place to sharpen your Salesforce training skills while gaining cutting-edge experience through real time examples and live projects. Faculty covered in real time examples and practical oriented I joined this course in 2025 and now working in a reputed healthcare company.I would strongly recommended to chose VR IT Solutions for Salesforce online training .
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Preparing for GitOps, MLOps, AIOps & FinOps interviews?
Read free interview questions and real-time scenarios with answers. Our students get all 181+ in the Job Ready Hub.
Batch timings
Pick a slot that fits around college or work. New batches start every month.
Book your slot- Morning7 – 9 AM
- Afternoon12 – 2 PM
- Evening6 – 8 PM
- WeekendSat & Sun
- Fast trackOn request
- One-to-one training
- Backup classes
- Free resume preparation
- Mock interviews
- Job support
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Get your course completion certificate
- Issued by VR IT Solutions when you complete the course and the real-time project
- Every certificate has its own certificate ID
- Add it to your resume and LinkedIn profile
GitOps, MLOps, AIOps & FinOps Online Training in USA, UK & Canada
Looking for GitOps, MLOps, AIOps & FinOps online training from the USA, UK or Canada? Join our live online batches from anywhere — classes run in time slots that suit your time zone, every session is recorded for revision, and you get the same real-time project, certificate and placement support as our Hyderabad students.
- USAEST & PST evening slots
- UKGMT / BST slots
- CanadaEST & CST slots
- WeekendSat & Sun, all time zones
Visit our Ameerpet centre
- 506/A, Aditya Enclave, Nilagiri Block, 5th Floor, Ameerpet, Hyderabad – 500016
- Monday to Saturday, 9 AM – 7 PM
- +91 90327 34343
- info@vritsol.com
GitOps, MLOps, AIOps & FinOps Training FAQs | VR IT Solutions
GitOps manages deployments from Git, MLOps manages machine learning models in production, AIOps uses AI on monitoring data to find and explain problems, and FinOps manages cloud cost. This course covers all four.
It is live online only, with weekday and weekend batches. Every session is recorded.
The course runs for 30 days in six modules, including three real-time projects.
Yes, basic Linux, Git, Docker, Kubernetes and CI/CD knowledge is expected. If you are new to DevOps, start with our Azure DevOps, AWS DevOps or Multi-Cloud DevOps course.
No. We explain the ML lifecycle in simple terms. The focus is on versioning, deploying and monitoring models, not on building them.
Argo CD, Flux, Helm, Kustomize, Argo Rollouts, DVC, MLflow, Kubeflow, Azure Machine Learning, Prometheus, Grafana, ELK, Datadog and Dynatrace overviews, Azure Cost Management, AWS Cost Explorer, Kubecost and Infracost.
Absolutely. VR IT Solutions offers free demo sessions for all courses. You can attend a live class, interact with the trainer, and get a feel for the training quality before making any commitment. Just reach out to our team and we will schedule one for you.
We provide end-to-end placement assistance — from building a job-ready resume to conducting mock interviews with industry experts. Our team actively shares job openings, refers students to hiring companies, and supports you until you land your first role.
Yes. Every trainer at VR IT Solutions has between 8 and 13 years of hands-on industry experience. They have worked on real enterprise projects and bring that practical knowledge directly into the classroom, which makes a significant difference when you face real job interviews.
Course Training
Industry-certified · Real-time projects · 100% Placement Support
Call us: +91-9032734343