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Advanced Cloud Program

Complete Cloud Learning Pathway

Cloud Computing Training

Expert
Trainers

Hands-On
Experience

Real-World
Projects

Career
Growth

Industry
Certificates

This Cloud Computing Professional Program is designed as a complete learning pathway aligned with major industry cloud certifications and enterprise requirements. The curriculum provides comprehensive hands-on training in AWS, Microsoft Azure, Google Cloud Platform, DevOps, Infrastructure as Code, Kubernetes, Cloud Security, Data Engineering, Artificial Intelligence, and FinOps.

The program is highly suitable for students, corporate trainees, cloud computing aspirants, working IT professionals, DevOps professionals, software developers, system administrators, and career switchers.

Objective of the Program

Understand cloud computing fundamentals

Work with AWS, Azure, and Google Cloud

Design and deploy cloud-based applications

Apply DevOps and CI/CD practices

Automate infrastructure using Infrastructure as Code

Build and manage Docker containers

Comprehensively Align with the Leading Cloud Certifications

AWS

Cloud Certifications

AZURE

Microsoft Cloud

GCP

Google Cloud

CKA

Kubernetes Administrator

Terraform & DevOps
CLOUD COMPUTING PROGRAM

Cloud - Course Content

01

Module 1: Computing & OS Fundamentals

Theory

  • CPU, memory, storage & I/O
  • Linux fundamentals
  • Filesystem & permissions
  • Processes & shell scripting
  • Package management & systemd
  • Logs & SSH

Practical

  • Linux VM provisioning
  • Linux terminal & commands
  • User and permission management
  • Bash automation scripts
  • SSH configuration
  • Basic VM hardening
02

Module 2: Networking Fundamentals

Theory

  • OSI & TCP/IP models
  • IP addressing & subnetting
  • DNS
  • HTTP/HTTPS & TLS
  • Routing & switching
  • Load balancing & CDN
  • Firewalls, VPN & NAT

Practical

  • VPC/VNet configuration
  • Subnet creation
  • Route table configuration
  • Security group setup
  • Network connectivity testing
03

Module 3: Virtualization & Cloud Concepts

Theory

  • Hypervisors
  • Virtual machines vs containers
  • IaaS, PaaS, SaaS & FaaS
  • Public, private, hybrid & multi-cloud
  • Shared responsibility model
  • CapEx, OpEx & TCO
  • AWS, Azure & GCP fundamentals

Practical

  • VM deployment
  • Container vs VM comparison
  • Cloud service comparison
  • Deploy sample workloads across AWS, Azure & GCP
04

Module 4: Cloud Account & Well-Architected Foundations

Theory

  • AWS Organizations
  • Azure Management Groups
  • GCP Resource Manager
  • Well-Architected Framework
  • Security & reliability principles
  • Billing, budgets & tagging

Practical

  • Cloud account setup
  • Organization and resource management
  • Budget configuration
  • Resource tagging
  • Basic Well-Architected review

Assessment

  • Linux & networking practical
  • Cloud account configuration
  • Written assessment
05

Module 5: Cloud Compute

Theory

  • AWS EC2
  • Azure Virtual Machines
  • GCP Compute Engine
  • Auto Scaling
  • Load balancers
  • Spot & preemptible instances
  • Serverless computing

Practical

  • Cloud VM deployment
  • Auto Scaling configuration
  • Load balancer setup
  • Lambda/Functions deployment
  • Auto-scaling web application
06

Module 6: Cloud Storage

Theory

  • Object storage
  • Block storage
  • File storage
  • Storage classes
  • Lifecycle policies
  • Versioning & replication
  • Backup & disaster recovery
  • RPO & RTO

Practical

  • S3/Blob/Cloud Storage setup
  • Static website deployment
  • Lifecycle configuration
  • Versioning
  • Backup implementation
07

Module 7: Cloud Databases

Theory

  • Relational databases
  • NoSQL databases
  • Managed database services
  • Database replication
  • Read replicas
  • Connection pooling
  • Redis caching
  • Database selection

Practical

  • Managed SQL database deployment
  • NoSQL database setup
  • Database backup configuration
  • Redis caching
  • Database connectivity
08

Module 8: IAM & Multi-Cloud Networking

Theory

  • IAM users, roles & policies
  • Least privilege
  • SSO, SAML & OIDC
  • VPC peering
  • Transit Gateway
  • Direct Connect, ExpressRoute & Cloud Interconnect
  • Hybrid & multi-cloud architecture

Practical

  • IAM configuration
  • Role and policy creation
  • SSO implementation
  • VPC peering
  • Multi-tier network setup
  • 3-tier application deployment

Assessment

  • Compute + database + storage + IAM project
  • Multi-cloud networking practical
09

Module 9: Git & CI/CD

Theory

  • Git fundamentals
  • Branching & pull requests
  • Trunk-based development
  • CI/CD concepts
  • GitHub Actions
  • GitLab CI
  • Jenkins
  • Cloud CI/CD services

Practical

  • Git repository management
  • Branching workflow
  • Automated testing
  • CI pipeline creation
  • Automated application deployment
10

Module 10: Infrastructure as Code

Theory

  • Infrastructure as Code
  • Terraform
  • State management
  • Terraform modules
  • Workspaces
  • CloudFormation & Bicep
  • GitOps
  • Policy as Code

Practical

  • Terraform installation
  • Cloud infrastructure provisioning
  • Terraform module creation
  • State management
  • Infrastructure automation
  • GitOps workflow
11

Module 11: Docker & Containers

Theory

  • Docker architecture
  • Images & containers
  • Dockerfiles
  • Image layers
  • Multi-stage builds
  • Container registries
  • Container security

Practical

  • Docker image creation
  • Container management
  • Multi-container application
  • Push images to registry
  • Container image scanning
12

Module 12: Kubernetes

Theory

  • Kubernetes architecture
  • Pods & deployments
  • Services & ingress
  • ConfigMaps & Secrets
  • Helm
  • HPA & VPA
  • Cluster Autoscaler
  • EKS, AKS & GKE

Practical

  • Kubernetes cluster setup
  • Application deployment
  • Services & ingress configuration
  • Helm deployment
  • Kubernetes autoscaling
  • CI/CD with Kubernetes

Assessment

  • Containerized microservices project
  • Managed Kubernetes deployment
13

Module 13: Cloud-Native Architecture

Theory

  • Microservices architecture
  • Event-driven architecture
  • Message queues
  • Kafka
  • API gateways
  • Service mesh
  • Serverless architecture

Practical

  • Monolith-to-microservices conversion
  • Message queue configuration
  • API gateway setup
  • Event-driven application
14

Module 14: Observability & Reliability

Theory

  • Metrics, logs & traces
  • Prometheus & Grafana
  • OpenTelemetry
  • CloudWatch, Azure Monitor & Cloud Monitoring
  • SLI, SLO & SLA
  • Error budgets
  • Incident response
  • Chaos engineering

Practical

  • Application monitoring
  • Centralized logging
  • Prometheus & Grafana setup
  • Distributed tracing
  • Alert configuration
15

Module 15: Cloud Security & Zero Trust

Theory

  • Cloud security fundamentals
  • Shared responsibility
  • Encryption & KMS
  • Secrets management
  • Zero Trust
  • Network segmentation
  • WAF & DDoS protection
  • SOC 2, ISO 27001, HIPAA & GDPR
  • CSPM & CNAPP

Practical

  • IAM security configuration
  • Encryption implementation
  • Secrets management
  • Network segmentation
  • WAF configuration
  • Cloud security audit
  • Security misconfiguration remediation
16

Module 16: FinOps & Cost Optimization

Theory

  • FinOps framework
  • Inform, optimize & operate
  • Cloud billing & cost visibility
  • Right-sizing
  • Reserved instances
  • Savings plans
  • Spot instances
  • Tagging & cost allocation
  • Showback & chargeback

Practical

  • Cloud budget configuration
  • Cost analysis
  • Resource tagging
  • Right-sizing resources
  • Cost optimization report
  • Cost dashboard

Assessment

  • Architecture review
  • Security audit
  • Cost optimization assessment
17

Module 17: Data Engineering

Theory

  • Data lakes
  • Data warehouses
  • Lakehouse architecture
  • ETL & ELT
  • Snowflake, BigQuery & Redshift
  • AWS Glue & Azure Data Factory
  • Apache Spark

Practical

  • Cloud data lake creation
  • ETL pipeline
  • Data transformation
  • Spark data processing
  • Data warehouse integration
18

Module 18: Streaming & Real-Time Data

Theory

  • Kafka
  • Kinesis
  • Event Hubs
  • Pub/Sub
  • Stream processing
  • Spark Structured Streaming
  • Apache Flink basics

Practical

  • Real-time data ingestion
  • Kafka pipeline
  • Stream processing
  • Real-time analytics
  • Dashboard creation
19

Module 19: MLOps

Theory

  • ML lifecycle
  • SageMaker
  • Azure Machine Learning
  • Vertex AI
  • Model training & deployment
  • Model versioning
  • Model monitoring
  • Drift detection
  • ML CI/CD

Practical

  • Model training
  • Model deployment
  • Managed ML endpoint
  • Model monitoring
  • MLOps pipeline
20

Module 20: Generative AI & LLM Ops

Theory

  • Foundation models
  • Amazon Bedrock
  • Azure OpenAI
  • Vertex AI
  • Prompt engineering
  • Embeddings
  • Vector databases
  • RAG
  • AI agents
  • Guardrails
  • Cost & latency optimization

Practical

  • LLM application
  • Embedding generation
  • Vector database setup
  • RAG pipeline
  • AI application deployment
  • Basic AI guardrails

Assessment

  • Cloud-based RAG application
  • AI architecture review
21

Module 21: DevOps / SRE Specialization

Theory

  • Advanced Kubernetes
  • Operators & service mesh
  • Canary & blue-green deployment
  • SRE practices
  • On-call & incident management
  • Platform engineering
  • Internal developer platforms

Practical

  • Advanced Kubernetes deployment
  • Progressive delivery
  • Service mesh implementation
  • Incident management simulation
  • Platform engineering project
22

Module 22: Cloud Security Engineering Specialization

Theory

  • Cloud threat modeling
  • Cloud penetration-testing basics
  • Advanced IAM
  • CNAPP
  • Security automation
  • Compliance automation

Practical

  • Cloud threat modeling
  • IAM security assessment
  • Cloud security testing
  • CNAPP implementation
  • Compliance automation
23

Module 23: Data & AI Engineering Specialization

Theory

  • Advanced Spark & Databricks
  • Data mesh
  • LLM fine-tuning
  • RAG architecture
  • AI governance
  • Responsible AI

Practical

  • Advanced Spark pipeline
  • Databricks project
  • RAG implementation
  • AI governance assessment
24

Module 24: Solutions Architecture Specialization

Theory

  • Multi-cloud architecture
  • Hybrid cloud
  • Cloud migration
  • 6 R's migration strategy
  • Enterprise landing zones
  • Disaster recovery

Practical

  • Multi-cloud architecture design
  • Migration planning
  • Landing zone design
  • Disaster recovery implementation

“Building Strong Technical Foundations through Practical Learning and Research-Driven Training.”

TOP CLOUD COMPUTING LEARNING PLATFORMS

Best Preparation Platforms for Cloud Computing

Microsoft Learn

https://learn.microsoft.com/

Google Cloud Skills Boost

https://www.cloudskillsboost.google/

AWS Skill Builder

https://skillbuilder.aws/

Terraform Tutorials

https://developer.hashicorp.com/terraform/tutorials

Docker

https://www.docker.com/

Kubernetes Training

https://kubernetes.io/training/

Killercoda

https://killercoda.com/

LocalStack

https://www.localstack.cloud/

KodeKloud

https://kodekloud.com/

Cloud Academy

https://cloudacademy.com/

Pluralsight

https://www.pluralsight.com/
Explore Cloud Project Titles

“S-Logix Builds Industry-Ready Professionals through Advanced Technical Training Programs.”

Essential Cloud Computing Certification

AWS Certified DevOps Engineer – Professional

The AWS Certified DevOps Engineer – Professional is an advanced cloud certification offered by Amazon Web Services (AWS). It validates the ability to develop, deploy, operate, and automate applications and infrastructure on AWS.

The certification focuses on CI/CD, Infrastructure as Code, monitoring, security, automation, reliability, and scalable cloud operations.

Skills Required

  • DevOps practices
  • CI/CD pipelines
  • Infrastructure as Code
  • Cloud automation
  • Docker and Kubernetes
  • Monitoring and logging
  • Deployment strategies
  • Security and compliance

Roles and Opportunities

  • DevOps Engineer
  • Site Reliability Engineer
  • Cloud Engineer
  • Platform Engineer
  • Cloud Automation Engineer

Certification by

  • Amazon Web Services (AWS) is a leading global cloud computing provider offering infrastructure, platform, database, security, AI/ML, and other cloud services.
Essential Cloud Computing Certification

AWS Certified Security – Specialty

The AWS Certified Security – Specialty validates expertise in securing AWS workloads, applications, data, and infrastructure.

Skills Required

  • Cloud security
  • IAM
  • Data encryption
  • Network security
  • Security monitoring
  • Incident response

Roles and Opportunities

  • Cloud Security Engineer
  • Cloud Security Architect
  • Security Engineer
  • Security Consultant

Certification by

  • Amazon Web Services (AWS)
Essential Cloud Computing Certification

Google Professional Data Engineer

The Google Professional Data Engineer certification validates the ability to design, build, and manage data processing systems on Google Cloud.

Skills Required

  • Data engineering
  • Data pipelines
  • Data warehouses
  • Data lakes
  • BigQuery
  • Data governance

Roles and Opportunities

  • Cloud Data Engineer
  • Data Engineer
  • Data Architect
  • Analytics Engineer

Certification by

  • Google Cloud
Essential Cloud Computing Certification

AWS Certified Solutions Architect – Professional

The AWS Certified Solutions Architect – Professional is an advanced certification focused on designing complex, scalable, secure, and highly available AWS cloud architectures.

Skills Required

  • Cloud architecture
  • High availability
  • Scalability
  • Cloud migration
  • Disaster recovery
  • Security architecture
  • Cost optimization

Roles and Opportunities

  • Cloud Solutions Architect
  • Cloud Architect
  • Solutions Engineer
  • Cloud Consultant

Certification by

  • Amazon Web Services (AWS)
Essential Cloud Computing Certification

Certified Kubernetes Administrator (CKA)

The Certified Kubernetes Administrator (CKA) is a hands-on certification focused on deploying, managing, configuring, and troubleshooting Kubernetes environments.

Skills Required

  • Kubernetes administration
  • Cluster management
  • Container orchestration
  • Networking
  • Storage
  • Security
  • Troubleshooting

Roles and Opportunities

  • Kubernetes Administrator
  • DevOps Engineer
  • Cloud Engineer
  • Site Reliability Engineer
  • Platform Engineer

Certification by

  • Cloud Native Computing Foundation (CNCF) and The Linux Foundation
Explore Cloud Internship Program

Cloud Computing Tools & Platforms

Enterprise-grade cloud technologies and platforms used for cloud infrastructure, infrastructure as code, DevOps, containerization, Kubernetes, cloud security, monitoring, data engineering, AI/ML, automation, and FinOps.

1. Cloud Compute & Infrastructure

Virtual Machines Serverless Computing Cloud Infrastructure Application Deployment
Tool Purpose Industry Usage
AWS EC2 Virtual compute Enterprise workloads
AWS Lambda Serverless computing Event-driven applications
Azure VMs Virtual compute Enterprise applications
Azure Functions Serverless computing Application automation
GCP Compute Engine Virtual compute Cloud infrastructure
Google Cloud Run Container-based serverless Cloud-native applications
Cloud compute platforms provide scalable infrastructure for deploying enterprise applications, APIs, microservices, and serverless workloads.

2. Infrastructure as Code (IaC)

Infrastructure Provisioning Cloud Automation Multi-Cloud Deployment Configuration Management
Tool Purpose Industry Usage
Terraform Multi-cloud infrastructure as code Enterprise provisioning
CloudFormation AWS infrastructure automation AWS environments
Bicep Azure infrastructure as code Azure deployments
Infrastructure as Code tools enable organizations to provision, manage, and version cloud infrastructure consistently through automated and repeatable configurations.

3. Containers & Kubernetes

Containerization Container Orchestration Microservices Application Scalability
Tool Purpose Industry Usage
Docker Containerization Application packaging
Kubernetes Container orchestration Cloud-native applications
Amazon EKS Managed Kubernetes AWS workloads
Azure AKS Managed Kubernetes Azure workloads
Google GKE Managed Kubernetes GCP workloads
Helm Kubernetes package management Application deployment
Container and Kubernetes technologies provide scalable platforms for deploying, managing, and orchestrating modern cloud-native applications.

4. CI/CD & DevOps

Continuous Integration Continuous Deployment GitOps Release Automation
Tool Purpose Industry Usage
GitHub Actions CI/CD automation DevOps pipelines
Jenkins Automation server Enterprise CI/CD
Azure DevOps Development & CI/CD Enterprise delivery
ArgoCD GitOps continuous delivery Kubernetes environments
CI/CD and DevOps platforms automate software testing, application deployment, infrastructure delivery, and release management.

5. Observability & Monitoring

Metrics Logging Distributed Tracing Performance Monitoring
Tool Purpose Industry Usage
Prometheus Metrics monitoring Kubernetes environments
Grafana Visualization & dashboards Cloud observability
OpenTelemetry Telemetry & tracing Cloud-native systems
CloudWatch AWS monitoring & logging AWS operations
Azure Monitor Cloud monitoring Azure operations
Observability tools provide visibility into application performance, infrastructure health, logs, metrics, traces, and production incidents.

6. Cloud Security

Identity & Access Management Encryption Security Monitoring Policy Enforcement
Tool Purpose Industry Usage
IAM Identity & access management Cloud security
KMS Encryption & key management Data protection
Security Hub Security posture management AWS security operations
Defender for Cloud Cloud security management Azure / Multi-cloud
OPA Policy as code Cloud governance
Cloud security technologies protect identities, data, workloads, and infrastructure while supporting security governance, compliance, and policy enforcement.

7. Data Engineering & Analytics

Data Warehousing Data Streaming Big Data Processing Workflow Orchestration
Tool Purpose Industry Usage
Snowflake Cloud data warehouse Enterprise analytics
BigQuery Serverless data warehouse Big data analytics
Redshift Cloud data warehouse AWS analytics
Kafka Event streaming Real-time data
Spark Distributed data processing Data engineering
Airflow Workflow orchestration Data pipelines
Cloud data technologies enable organizations to build scalable data pipelines, streaming platforms, data warehouses, and analytics solutions.

8. AI/ML & Generative AI

Machine Learning Generative AI LLM Applications Vector Search
Tool Purpose Industry Usage
SageMaker Machine learning platform MLOps & AI
Vertex AI AI/ML platform Enterprise AI
Azure ML Machine learning platform Azure AI workloads
Bedrock Generative AI services LLM applications
Azure OpenAI Enterprise Generative AI AI applications
Pinecone / pgvector Vector databases RAG applications
Cloud AI/ML platforms support machine learning, Generative AI, LLM applications, embeddings, vector search, and Retrieval-Augmented Generation (RAG).

9. FinOps & Cloud Cost Management

Cost Visibility Budget Management Cost Optimization Cloud Governance
Tool Purpose Industry Usage
AWS Cost Explorer Cloud cost analysis AWS FinOps
Azure Cost Management Cloud cost analysis Azure FinOps
Native Billing Tools Cloud billing & cost tracking Multi-cloud cost management
Tagging Policies Resource cost allocation Cost governance
FinOps technologies help organizations monitor cloud spending, optimize resource usage, control budgets, allocate costs, and establish cloud cost governance.
Explore Cloud Industry Projects

“S-Logix Helps Students Transform Curiosity into Career-Ready Expertise.”

Industry Focused Training

Hands-On Learning & Real-World Experience

Gain practical exposure through industry-oriented projects, internship opportunities, and real-time development experience designed to prepare students for professional careers.

Real-World Projects

Students will work on two major projects based on their own area of interest and industry requirements.

Project Internship

Candidates who successfully complete the course will become eligible for project internship opportunities.

6-Month Duration

Learn through real-time projects developed according to live client requirements and professional workflows.

Apply Now
ADVANCED CYBERSECURITY TRAINING

Become a Cloud Expert

Master cloud computing, cloud infrastructure, DevOps, containerization, Kubernetes, cloud security, automation, and scalable cloud-native application deployment with industry-focused practical training.

01

Course Advantages

  • Gain in-demand cloud computing skills required by top IT companies and organizations.
  • Learn cloud infrastructure, DevOps, containerization, Kubernetes, and cloud deployment techniques.
  • Build hands-on experience with industry-standard cloud platforms, tools, and technologies.
  • Improve career opportunities with high-demand cloud computing and DevOps job roles worldwide.
02

Who Can Apply

  • B.E / B.Tech / M.E / M.Tech / B.Sc / M.Sc / BCA / MCA / Masters graduates aspiring for a career in cloud computing, DevOps, and cloud technologies.
  • Aspiring professionals aiming to build skills in cloud infrastructure, cloud deployment, and DevOps practices.
  • Students interested in cloud platforms, containerization, Kubernetes, and cloud-native application development.
  • IT professionals looking to upgrade their cloud computing, automation, and cloud platform expertise.
03

Contact Information

Address

S-Logix (OPC) Private Limited
2nd Floor, #7A, High School Road,
Secretariat Colony, Ambattur,
Chennai – 600053, Tamil Nadu, India
(Landmark: SRM School)

Call Us Now +91 81240 01111 +91 97109 99001
FUTURE READY TRAINING

“Training with Purpose, Internships with Impact, and Learning with Innovation.”

S-Logix Cloud Computing training programs are designed to help students build strong cloud technology knowledge through practical learning, live projects, and real-time industry exposure. Students gain hands-on experience in cloud platforms, infrastructure, DevOps, containerization, and cloud-native technologies while improving problem-solving, creativity, teamwork, and professional skills required for successful technology careers.

Explore Now